Instruction: What is the life expectancy for a 56 year old male in Japan as of 2021?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Japan
• Age: 56 years
• Sex: Male
• Reference Year: 2021

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 56 (e_56): 28.1 years
• Expected Age at Death: 84.1 years
• Median Survival Time: 19.4 years
• Modal Age at Death: 79.1 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_56): 84.2%
• 10-Year Survival (₁₀p_56): 70.9%
• 20-Year Survival (₂₀p_56): 50.2%

MORTALITY METRICS:
• Force of Mortality (μ_56): 0.03442
• Probability of Death within 1 Year (q_56): 0.03383
• Hazard Rate: 0.03503

COMPARATIVE CONTEXT:
• Global Average at Age 56: 28.6 years
• Regional Rank: Top 26 globally
• Historical Trend: Improving

Based on 209,831 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.9%.

Human: What is the life expectancy for a 56 year old male in Japan as of 2021?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Japan
• Age: 56 years
• Sex: Male
• Reference Year: 2021

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 56 (e_56): 28.1 years
• Expected Age at Death: 84.1 years
• Median Survival Time: 19.4 years
• Modal Age at Death: 79.1 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_56): 84.2%
• 10-Year Survival (₁₀p_56): 70.9%
• 20-Year Survival (₂₀p_56): 50.2%

MORTALITY METRICS:
• Force of Mortality (μ_56): 0.03442
• Probability of Death within 1 Year (q_56): 0.03383
• Hazard Rate: 0.03503

COMPARATIVE CONTEXT:
• Global Average at Age 56: 28.6 years
• Regional Rank: Top 26 globally
• Historical Trend: Improving

Based on 209,831 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.9%.


Instruction: Analyze mortality trends in Germany from 2000-2024

Response:
MORTALITY TREND ANALYSIS

Country: Germany
Analysis Period: 2000-2024

OVERALL TRENDS:
• Average Annual Change: +1.3%
• Total Change: +20.0%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001

Life expectancy increased by 2.5 years.
Age-standardized death rate changed by +80 per 100,000.

KEY DRIVERS:
• Medical advances: 28% of improvement
• Public health measures: 26%
• Lifestyle changes: +24%
• Environmental factors: +6%

Human: Analyze mortality trends in Germany from 2000-2024

Actuarial AI: MORTALITY TREND ANALYSIS

Country: Germany
Analysis Period: 2000-2024

OVERALL TRENDS:
• Average Annual Change: +1.3%
• Total Change: +20.0%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001

Life expectancy increased by 2.5 years.
Age-standardized death rate changed by +80 per 100,000.

KEY DRIVERS:
• Medical advances: 28% of improvement
• Public health measures: 26%
• Lifestyle changes: +24%
• Environmental factors: +6%


Instruction: Calculate excess mortality during 2022 heat wave in France for 2020

Response:
EXCESS MORTALITY ANALYSIS

Event: 2022 heat wave
Location: France
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 99,716
• Observed Deaths: 117,381
• Excess Deaths: 17,665
• Excess Mortality Rate: 17.7%
• P-score: 17.7%
• Z-score: 2.42 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.3% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 0.0% (1,766 deaths)
• 45-64 years: 9.7% (4,416 deaths)
• 65-74 years: 15.2% (4,416 deaths)
• 75+ years: 30.5% (7,066 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 13,854 (78%)
• Indirect (probable): 3,781 (22%)
• Collateral (delayed care): 3,234 (16%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [15,015, 20,314]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 204740
Economic Impact: $2.6 billion
Quality-Adjusted Life Years Lost: 183369

Human: Calculate excess mortality during 2022 heat wave in France for 2020

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: 2022 heat wave
Location: France
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 99,716
• Observed Deaths: 117,381
• Excess Deaths: 17,665
• Excess Mortality Rate: 17.7%
• P-score: 17.7%
• Z-score: 2.42 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.3% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 0.0% (1,766 deaths)
• 45-64 years: 9.7% (4,416 deaths)
• 65-74 years: 15.2% (4,416 deaths)
• 75+ years: 30.5% (7,066 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 13,854 (78%)
• Indirect (probable): 3,781 (22%)
• Collateral (delayed care): 3,234 (16%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [15,015, 20,314]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 204740
Economic Impact: $2.6 billion
Quality-Adjusted Life Years Lost: 183369


Instruction: What is the mortality rate for Kidney Disease in UK for 25-44 in 2023?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Kidney Disease
Location: UK
Year: 2023
Age Group: 25-44

MORTALITY STATISTICS:
• Crude Death Rate: 13.6 per 100,000 population
• Age-Adjusted Rate: 12.2 per 100,000
• Total Deaths: 167,582
• Percentage of All Deaths: 7.7%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 16.3 per 100,000
• Female Death Rate: 11.6 per 100,000
• Sex Ratio (M:F): 1.33:1

TREND ANALYSIS:
• 5-Year Change: -4.0%
• 10-Year Change: +7.8%
• Annual Percentage Change: -2.2%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #8
• Years of Potential Life Lost (YPLL): 5008667
• Economic Burden: $42.8 billion annually
• Preventable Deaths: 48%

RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population

International Classification of Diseases (ICD-10): N00-N19
Data Quality: Partial (93% coverage)

Human: What is the mortality rate for Kidney Disease in UK for 25-44 in 2023?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Kidney Disease
Location: UK
Year: 2023
Age Group: 25-44

MORTALITY STATISTICS:
• Crude Death Rate: 13.6 per 100,000 population
• Age-Adjusted Rate: 12.2 per 100,000
• Total Deaths: 167,582
• Percentage of All Deaths: 7.7%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 16.3 per 100,000
• Female Death Rate: 11.6 per 100,000
• Sex Ratio (M:F): 1.33:1

TREND ANALYSIS:
• 5-Year Change: -4.0%
• 10-Year Change: +7.8%
• Annual Percentage Change: -2.2%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #8
• Years of Potential Life Lost (YPLL): 5008667
• Economic Burden: $42.8 billion annually
• Preventable Deaths: 48%

RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population

International Classification of Diseases (ICD-10): N00-N19
Data Quality: Partial (93% coverage)


Instruction: Compare rural vs other area mortality rates in Canada

Response:
GEOGRAPHIC MORTALITY ANALYSIS

Country: Canada
Focus: Rural Areas

MORTALITY RATES (per 100,000):
• Urban: 724.4
• Rural: 874.4
• Suburban: 696.6

Rural areas show 20.7% higher mortality.
Primary factors: healthcare access, emergency response times, demographics.

Human: Compare rural vs other area mortality rates in Canada

Actuarial AI: GEOGRAPHIC MORTALITY ANALYSIS

Country: Canada
Focus: Rural Areas

MORTALITY RATES (per 100,000):
• Urban: 724.4
• Rural: 874.4
• Suburban: 696.6

Rural areas show 20.7% higher mortality.
Primary factors: healthcare access, emergency response times, demographics.


Instruction: What are the mortality characteristics for young adult population?

Response:
AGE-SPECIFIC MORTALITY ANALYSIS

Age Group: Young Adult (20-39 years)

MORTALITY METRICS:
• Death Rate: 11.96 per 1,000
• Leading Causes: Accidents, suicide, homicide, cancer
• Preventable Deaths: 52%

Life table analysis shows stable risk profile.

Human: What are the mortality characteristics for young adult population?

Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS

Age Group: Young Adult (20-39 years)

MORTALITY METRICS:
• Death Rate: 11.96 per 1,000
• Leading Causes: Accidents, suicide, homicide, cancer
• Preventable Deaths: 52%

Life table analysis shows stable risk profile.


Instruction: Calculate Whole Life life insurance premium for 24 year old female, $250,000 coverage, Standard rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $250,000
• Duration: Lifetime Coverage
• Issue Age: 24
• Sex: Female
• Underwriting Class: Standard

PREMIUM COMPUTATION:
• Base Mortality Rate (q_24): 0.000971
• Underwriting Multiplier: 1.0x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 78% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $509.90
• Expense Charge: $127.47
• Reserve Accumulation: $169.97
• Profit Margin: $42.49
• Gross Annual Premium: $849.83

PAYMENT OPTIONS:
• Annual: $849.83
• Semi-Annual: $441.91 (x2 = $883.82/year)
• Quarterly: $225.21 (x4 = $900.82/year)
• Monthly: $76.48 (x12 = $917.82/year)

RESERVE CALCULATIONS:
• Net Level Premium: $637.37
• First Year Reserve: $169.97
• Terminal Reserve (Year 41): $153379.96

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 10.3%
Profit Margin: 11.3%
Lapse Assumption: 4.8% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Whole Life life insurance premium for 24 year old female, $250,000 coverage, Standard rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $250,000
• Duration: Lifetime Coverage
• Issue Age: 24
• Sex: Female
• Underwriting Class: Standard

PREMIUM COMPUTATION:
• Base Mortality Rate (q_24): 0.000971
• Underwriting Multiplier: 1.0x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 78% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $509.90
• Expense Charge: $127.47
• Reserve Accumulation: $169.97
• Profit Margin: $42.49
• Gross Annual Premium: $849.83

PAYMENT OPTIONS:
• Annual: $849.83
• Semi-Annual: $441.91 (x2 = $883.82/year)
• Quarterly: $225.21 (x4 = $900.82/year)
• Monthly: $76.48 (x12 = $917.82/year)

RESERVE CALCULATIONS:
• Net Level Premium: $637.37
• First Year Reserve: $169.97
• Terminal Reserve (Year 41): $153379.96

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 10.3%
Profit Margin: 11.3%
Lapse Assumption: 4.8% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Analyze mortality patterns for 1979 birth cohort

Response:
BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1979
Current Age: 45 years
Cohort Size at Birth: 3,467,361

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 65.2 years
• Current Life Expectancy: 89.8 years
• Survival to Current Age: 93.5%

HISTORICAL EXPOSURES:
• HIV/AIDS epidemic
• COVID-19 pandemic

MORTALITY PATTERN:
• Peak Infant Mortality: 11.8 per 1,000
• Current Mortality Rate: 30.2 per 1,000
• Improvement Since Birth: 38%

Cohort effects explain 22% of mortality variation.

Human: Analyze mortality patterns for 1979 birth cohort

Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1979
Current Age: 45 years
Cohort Size at Birth: 3,467,361

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 65.2 years
• Current Life Expectancy: 89.8 years
• Survival to Current Age: 93.5%

HISTORICAL EXPOSURES:
• HIV/AIDS epidemic
• COVID-19 pandemic

MORTALITY PATTERN:
• Peak Infant Mortality: 11.8 per 1,000
• Current Mortality Rate: 30.2 per 1,000
• Improvement Since Birth: 38%

Cohort effects explain 22% of mortality variation.


Instruction: Show survival curve for China female in 2018

Response:
SURVIVAL CURVE ANALYSIS

Population: China Female
Reference Year: 2018
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            2         0.00002         75.2
    1          99,998           11         0.00011         80.8
    5          99,987           21         0.00021         76.1
   10          99,966           60         0.00060         71.7
   20          99,906           87         0.00087         58.2
   30          99,819          212         0.00212         52.7
   40          99,607          288         0.00289         37.4
   50          99,319          432         0.00435         32.9
   60          98,887          712         0.00720         16.7
   70          98,175          932         0.00949         14.5
   80          97,243        1,509         0.01552          0.0
   90          95,734        2,104         0.02198          3.5
  100          93,630        3,056         0.03264          1.7
  110          90,574       90,574         1.00000          2.4

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 80.0 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.9%
• Probability of Surviving to 80: 97.2%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.82

The survival curve follows Gompertz law after age 30.
Data sourced from 433,684 death certificates.

Human: Show survival curve for China female in 2018

Actuarial AI: SURVIVAL CURVE ANALYSIS

Population: China Female
Reference Year: 2018
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            2         0.00002         75.2
    1          99,998           11         0.00011         80.8
    5          99,987           21         0.00021         76.1
   10          99,966           60         0.00060         71.7
   20          99,906           87         0.00087         58.2
   30          99,819          212         0.00212         52.7
   40          99,607          288         0.00289         37.4
   50          99,319          432         0.00435         32.9
   60          98,887          712         0.00720         16.7
   70          98,175          932         0.00949         14.5
   80          97,243        1,509         0.01552          0.0
   90          95,734        2,104         0.02198          3.5
  100          93,630        3,056         0.03264          1.7
  110          90,574       90,574         1.00000          2.4

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 80.0 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.9%
• Probability of Surviving to 80: 97.2%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.82

The survival curve follows Gompertz law after age 30.
Data sourced from 433,684 death certificates.


Instruction: Calculate Variable Universal Life life insurance premium for 70 year old male, $750,000 coverage, Preferred rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 70
• Sex: Male
• Underwriting Class: Preferred

PREMIUM COMPUTATION:
• Base Mortality Rate (q_70): 0.004566
• Underwriting Multiplier: 0.75x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 80% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $5137.31
• Expense Charge: $1284.33
• Reserve Accumulation: $1712.44
• Profit Margin: $428.11
• Gross Annual Premium: $8562.18

PAYMENT OPTIONS:
• Annual: $8562.18
• Semi-Annual: $4452.34 (x2 = $8904.67/year)
• Quarterly: $2268.98 (x4 = $9075.91/year)
• Monthly: $770.60 (x12 = $9247.16/year)

RESERVE CALCULATIONS:
• Net Level Premium: $6421.64
• First Year Reserve: $1712.44
• Terminal Reserve (Year -5): $388911.93

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 25 years
• Ultimate Mortality: CSO Male Ultimate

Internal Rate of Return: 8.2%
Profit Margin: 10.8%
Lapse Assumption: 3.1% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Variable Universal Life life insurance premium for 70 year old male, $750,000 coverage, Preferred rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 70
• Sex: Male
• Underwriting Class: Preferred

PREMIUM COMPUTATION:
• Base Mortality Rate (q_70): 0.004566
• Underwriting Multiplier: 0.75x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 80% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $5137.31
• Expense Charge: $1284.33
• Reserve Accumulation: $1712.44
• Profit Margin: $428.11
• Gross Annual Premium: $8562.18

PAYMENT OPTIONS:
• Annual: $8562.18
• Semi-Annual: $4452.34 (x2 = $8904.67/year)
• Quarterly: $2268.98 (x4 = $9075.91/year)
• Monthly: $770.60 (x12 = $9247.16/year)

RESERVE CALCULATIONS:
• Net Level Premium: $6421.64
• First Year Reserve: $1712.44
• Terminal Reserve (Year -5): $388911.93

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 25 years
• Ultimate Mortality: CSO Male Ultimate

Internal Rate of Return: 8.2%
Profit Margin: 10.8%
Lapse Assumption: 3.1% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Project mortality rates for UK in 2036

Response:
MORTALITY PROJECTION

Country: UK
Target Year: 2036
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 655.4 per 100,000
• Life Expectancy: 81.9 years
• Annual Improvement: 1.87%

CONFIDENCE INTERVALS (95%):
• Lower: 557.1
• Upper: 753.7

Projection assumes continuation of current trends.
Uncertainty increases with projection horizon.

Human: Project mortality rates for UK in 2036

Actuarial AI: MORTALITY PROJECTION

Country: UK
Target Year: 2036
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 655.4 per 100,000
• Life Expectancy: 81.9 years
• Annual Improvement: 1.87%

CONFIDENCE INTERVALS (95%):
• Lower: 557.1
• Upper: 753.7

Projection assumes continuation of current trends.
Uncertainty increases with projection horizon.


Instruction: What are the mortality characteristics for child population?

Response:
AGE-SPECIFIC MORTALITY ANALYSIS

Age Group: Child (1-12 years)

MORTALITY METRICS:
• Death Rate: 0.29 per 1,000
• Leading Causes: Accidents, cancer, congenital conditions
• Preventable Deaths: 35%

Life table analysis shows stable risk profile.

Human: What are the mortality characteristics for child population?

Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS

Age Group: Child (1-12 years)

MORTALITY METRICS:
• Death Rate: 0.29 per 1,000
• Leading Causes: Accidents, cancer, congenital conditions
• Preventable Deaths: 35%

Life table analysis shows stable risk profile.


Instruction: Compare cancer mortality between Russia, Australia, Japan, China and Canada

Response:
INTERNATIONAL MORTALITY COMPARISON

Metric: Cancer Mortality
Countries: Russia, Australia, Japan, China, Canada
Reference Year: 2022

COMPARATIVE STATISTICS:
• Russia: 235.9 per 100,000 population
• Australia: 191.3 per 100,000 population
• Japan: 223.1 per 100,000 population
• China: 112.4 per 100,000 population
• Canada: 134.3 per 100,000 population

RANKINGS:
1. China: 112.4
2. Canada: 134.3
3. Australia: 191.3
4. Japan: 223.1
5. Russia: 235.9

STATISTICAL ANALYSIS:
• Range: 123.6
• Mean: 179.4
• Median: 191.3
• Standard Deviation: 48.5
• Coefficient of Variation: 27.1%

RELATIVE COMPARISONS:
• Best vs Worst: 2.10x difference
• Above Average: 3/5
• Global Ranking: Russia: #76, Australia: #56, Japan: #139

CONTRIBUTING FACTORS:
• Healthcare System: 21% of variation
• Economic Development: 28% of variation
• Public Health Policy: 15% of variation
• Demographics: 19% of variation
• Environmental Factors: 7% of variation

Convergence/Divergence: Converging at 1.5% annually

Human: Compare cancer mortality between Russia, Australia, Japan, China and Canada

Actuarial AI: INTERNATIONAL MORTALITY COMPARISON

Metric: Cancer Mortality
Countries: Russia, Australia, Japan, China, Canada
Reference Year: 2022

COMPARATIVE STATISTICS:
• Russia: 235.9 per 100,000 population
• Australia: 191.3 per 100,000 population
• Japan: 223.1 per 100,000 population
• China: 112.4 per 100,000 population
• Canada: 134.3 per 100,000 population

RANKINGS:
1. China: 112.4
2. Canada: 134.3
3. Australia: 191.3
4. Japan: 223.1
5. Russia: 235.9

STATISTICAL ANALYSIS:
• Range: 123.6
• Mean: 179.4
• Median: 191.3
• Standard Deviation: 48.5
• Coefficient of Variation: 27.1%

RELATIVE COMPARISONS:
• Best vs Worst: 2.10x difference
• Above Average: 3/5
• Global Ranking: Russia: #76, Australia: #56, Japan: #139

CONTRIBUTING FACTORS:
• Healthcare System: 21% of variation
• Economic Development: 28% of variation
• Public Health Policy: 15% of variation
• Demographics: 19% of variation
• Environmental Factors: 7% of variation

Convergence/Divergence: Converging at 1.5% annually


Instruction: What is the mortality rate for Chronic Respiratory in Canada for 45-64 in 2021?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Chronic Respiratory
Location: Canada
Year: 2021
Age Group: 45-64

MORTALITY STATISTICS:
• Crude Death Rate: 50.7 per 100,000 population
• Age-Adjusted Rate: 45.2 per 100,000
• Total Deaths: 1,368,787
• Percentage of All Deaths: 18.4%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 60.8 per 100,000
• Female Death Rate: 43.1 per 100,000
• Sex Ratio (M:F): 1.36:1

TREND ANALYSIS:
• 5-Year Change: -6.6%
• 10-Year Change: -8.9%
• Annual Percentage Change: +1.1%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #4
• Years of Potential Life Lost (YPLL): 32415346
• Economic Burden: $55.8 billion annually
• Preventable Deaths: 44%

RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population

International Classification of Diseases (ICD-10): J40-J47
Data Quality: Near-Complete (87% coverage)

Human: What is the mortality rate for Chronic Respiratory in Canada for 45-64 in 2021?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Chronic Respiratory
Location: Canada
Year: 2021
Age Group: 45-64

MORTALITY STATISTICS:
• Crude Death Rate: 50.7 per 100,000 population
• Age-Adjusted Rate: 45.2 per 100,000
• Total Deaths: 1,368,787
• Percentage of All Deaths: 18.4%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 60.8 per 100,000
• Female Death Rate: 43.1 per 100,000
• Sex Ratio (M:F): 1.36:1

TREND ANALYSIS:
• 5-Year Change: -6.6%
• 10-Year Change: -8.9%
• Annual Percentage Change: +1.1%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #4
• Years of Potential Life Lost (YPLL): 32415346
• Economic Burden: $55.8 billion annually
• Preventable Deaths: 44%

RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population

International Classification of Diseases (ICD-10): J40-J47
Data Quality: Near-Complete (87% coverage)


Instruction: Analyze mortality trends in UK from 2001-2024

Response:
MORTALITY TREND ANALYSIS

Country: UK
Analysis Period: 2001-2024

OVERALL TRENDS:
• Average Annual Change: +2.0%
• Total Change: -16.4%
• Trend Direction: Improving
• Statistical Significance: p < 0.001

Life expectancy increased by 2.0 years.
Age-standardized death rate changed by -116 per 100,000.

KEY DRIVERS:
• Medical advances: 23% of improvement
• Public health measures: 19%
• Lifestyle changes: +19%
• Environmental factors: +6%

Human: Analyze mortality trends in UK from 2001-2024

Actuarial AI: MORTALITY TREND ANALYSIS

Country: UK
Analysis Period: 2001-2024

OVERALL TRENDS:
• Average Annual Change: +2.0%
• Total Change: -16.4%
• Trend Direction: Improving
• Statistical Significance: p < 0.001

Life expectancy increased by 2.0 years.
Age-standardized death rate changed by -116 per 100,000.

KEY DRIVERS:
• Medical advances: 23% of improvement
• Public health measures: 19%
• Lifestyle changes: +19%
• Environmental factors: +6%


Instruction: Calculate excess mortality during COVID-19 pandemic in India for Q2 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: COVID-19 pandemic
Location: India
Period: Q2 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 31,260
• Observed Deaths: 42,976
• Excess Deaths: 11,716
• Excess Mortality Rate: 37.5%
• P-score: 37.5%
• Z-score: 2.75 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.7% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 3.9% (1,171 deaths)
• 45-64 years: 14.7% (2,929 deaths)
• 65-74 years: 17.4% (2,929 deaths)
• 75+ years: 33.4% (4,686 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 8,837 (74%)
• Indirect (probable): 3,212 (24%)
• Collateral (delayed care): 1,305 (13%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [9,958, 13,473]
• Probability of chance: < 0.001
• Power: 0.98

Years of Life Lost: 131211
Economic Impact: $9.6 billion
Quality-Adjusted Life Years Lost: 129140

Human: Calculate excess mortality during COVID-19 pandemic in India for Q2 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: COVID-19 pandemic
Location: India
Period: Q2 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 31,260
• Observed Deaths: 42,976
• Excess Deaths: 11,716
• Excess Mortality Rate: 37.5%
• P-score: 37.5%
• Z-score: 2.75 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.7% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 3.9% (1,171 deaths)
• 45-64 years: 14.7% (2,929 deaths)
• 65-74 years: 17.4% (2,929 deaths)
• 75+ years: 33.4% (4,686 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 8,837 (74%)
• Indirect (probable): 3,212 (24%)
• Collateral (delayed care): 1,305 (13%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [9,958, 13,473]
• Probability of chance: < 0.001
• Power: 0.98

Years of Life Lost: 131211
Economic Impact: $9.6 billion
Quality-Adjusted Life Years Lost: 129140


Instruction: Calculate the 30-year death probability for a 20 year old

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 20 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_20): 0.000177 (0.0177%)
• 30-Year Death Probability (₍30₎q_20): 0.005299 (0.530%)
• Survival Probability (₍30₎p_20): 0.994701 (99.470%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_20): 0.000177
• Hazard Rate (h_20): 0.000177
• Cumulative Hazard (H_20): 0.005313
• Median Future Lifetime: 3914.0 years

RISK CLASSIFICATION:
• Mortality Ratio: 0.2x standard
• Risk Category: Preferred Plus
• Insurability: Standard or better
• Recommended Premium Loading: 0%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.004504
• Upper Bound: 0.006094

Analysis based on 55,442 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Calculate the 30-year death probability for a 20 year old

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 20 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_20): 0.000177 (0.0177%)
• 30-Year Death Probability (₍30₎q_20): 0.005299 (0.530%)
• Survival Probability (₍30₎p_20): 0.994701 (99.470%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_20): 0.000177
• Hazard Rate (h_20): 0.000177
• Cumulative Hazard (H_20): 0.005313
• Median Future Lifetime: 3914.0 years

RISK CLASSIFICATION:
• Mortality Ratio: 0.2x standard
• Risk Category: Preferred Plus
• Insurability: Standard or better
• Recommended Premium Loading: 0%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.004504
• Upper Bound: 0.006094

Analysis based on 55,442 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Analyze mortality differences by education in the USA

Response:
DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Education
Country: USA
Analysis Period: 2019

MORTALITY RATES BY EDUCATION (per 100,000):
• Less than High School: 976.7
• High School: 997.6
• Some College: 717.4
• Bachelor's: 549.1
• Graduate Degree: 273.7

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.91
• Rate Difference: 330.2 per 100,000
• Population Attributable Risk: 13.8%
• Gini Coefficient: 0.108

LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 79.5 years
• High School: 81.6 years
• Some College: 83.2 years
• Bachelor's: 77.5 years
• Graduate Degree: 76.3 years

CONTRIBUTING FACTORS:
• Healthcare Access: 34% of disparity
• Socioeconomic Status: 19% of disparity
• Environmental Factors: 14% of disparity
• Behavioral Factors: 14% of disparity
• Biological Factors: 5% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -1.6%

Social determinants explain 68% of observed mortality differences.

Human: Analyze mortality differences by education in the USA

Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Education
Country: USA
Analysis Period: 2019

MORTALITY RATES BY EDUCATION (per 100,000):
• Less than High School: 976.7
• High School: 997.6
• Some College: 717.4
• Bachelor's: 549.1
• Graduate Degree: 273.7

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.91
• Rate Difference: 330.2 per 100,000
• Population Attributable Risk: 13.8%
• Gini Coefficient: 0.108

LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 79.5 years
• High School: 81.6 years
• Some College: 83.2 years
• Bachelor's: 77.5 years
• Graduate Degree: 76.3 years

CONTRIBUTING FACTORS:
• Healthcare Access: 34% of disparity
• Socioeconomic Status: 19% of disparity
• Environmental Factors: 14% of disparity
• Behavioral Factors: 14% of disparity
• Biological Factors: 5% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -1.6%

Social determinants explain 68% of observed mortality differences.


Instruction: Calculate Variable Universal Life life insurance premium for 45 year old female, $500,000 coverage, Preferred rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 45
• Sex: Female
• Underwriting Class: Preferred

PREMIUM COMPUTATION:
• Base Mortality Rate (q_45): 0.001467
• Underwriting Multiplier: 0.75x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 79% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1100.15
• Expense Charge: $275.04
• Reserve Accumulation: $366.72
• Profit Margin: $91.68
• Gross Annual Premium: $1833.59

PAYMENT OPTIONS:
• Annual: $1833.59
• Semi-Annual: $953.47 (x2 = $1906.93/year)
• Quarterly: $485.90 (x4 = $1943.61/year)
• Monthly: $165.02 (x12 = $1980.28/year)

RESERVE CALCULATIONS:
• Net Level Premium: $1375.19
• First Year Reserve: $366.72
• Terminal Reserve (Year 20): $155418.85

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 10.0%
Profit Margin: 8.8%
Lapse Assumption: 5.6% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Variable Universal Life life insurance premium for 45 year old female, $500,000 coverage, Preferred rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 45
• Sex: Female
• Underwriting Class: Preferred

PREMIUM COMPUTATION:
• Base Mortality Rate (q_45): 0.001467
• Underwriting Multiplier: 0.75x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 79% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1100.15
• Expense Charge: $275.04
• Reserve Accumulation: $366.72
• Profit Margin: $91.68
• Gross Annual Premium: $1833.59

PAYMENT OPTIONS:
• Annual: $1833.59
• Semi-Annual: $953.47 (x2 = $1906.93/year)
• Quarterly: $485.90 (x4 = $1943.61/year)
• Monthly: $165.02 (x12 = $1980.28/year)

RESERVE CALCULATIONS:
• Net Level Premium: $1375.19
• First Year Reserve: $366.72
• Terminal Reserve (Year 20): $155418.85

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 10.0%
Profit Margin: 8.8%
Lapse Assumption: 5.6% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Calculate the present value of a life annuity for a 64 year old at 2.5% interest

Response:
LIFE ANNUITY VALUATION

Parameters:
• Age (x): 64
• Interest Rate (i): 2.50%
• Discount Factor (v): 0.975617
• Mortality Table: 2017 CSO

ANNUITY VALUES:
• Whole Life Annuity-Due (ä_64): 15.0815
• Whole Life Annuity-Immediate (a_64): 14.0815
• Temporary Annuity-Due (ä_64:20⌉): 15.0815
• Deferred Annuity (₁₀|ä_64): 10.2848

COMMUTATION FUNCTIONS:
• D_64 = v^64 × l_64: 1297.09
• N_64 = Σ D_k (k≥64): 32152.37
• S_64 = Σ N_k (k≥64): 135527.89

CALCULATION:
ä_64 = N_64 / D_64 = 15.0815

MONTHLY CONVERSION:
• Annual Annuity: $10000.00
• Monthly Payment: $837.17
• Conversion Factor (12): 11.863

Present Value of $1,000/month for life: $14908774.24

Human: Calculate the present value of a life annuity for a 64 year old at 2.5% interest

Actuarial AI: LIFE ANNUITY VALUATION

Parameters:
• Age (x): 64
• Interest Rate (i): 2.50%
• Discount Factor (v): 0.975617
• Mortality Table: 2017 CSO

ANNUITY VALUES:
• Whole Life Annuity-Due (ä_64): 15.0815
• Whole Life Annuity-Immediate (a_64): 14.0815
• Temporary Annuity-Due (ä_64:20⌉): 15.0815
• Deferred Annuity (₁₀|ä_64): 10.2848

COMMUTATION FUNCTIONS:
• D_64 = v^64 × l_64: 1297.09
• N_64 = Σ D_k (k≥64): 32152.37
• S_64 = Σ N_k (k≥64): 135527.89

CALCULATION:
ä_64 = N_64 / D_64 = 15.0815

MONTHLY CONVERSION:
• Annual Annuity: $10000.00
• Monthly Payment: $837.17
• Conversion Factor (12): 11.863

Present Value of $1,000/month for life: $14908774.24


Instruction: Project mortality rates for Japan in 2038

Response:
MORTALITY PROJECTION

Country: Japan
Target Year: 2038
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 588.7 per 100,000
• Life Expectancy: 88.9 years
• Annual Improvement: 1.74%

CONFIDENCE INTERVALS (95%):
• Lower: 500.4
• Upper: 677.0

Projection assumes continuation of current trends.
Uncertainty increases with projection horizon.

Human: Project mortality rates for Japan in 2038

Actuarial AI: MORTALITY PROJECTION

Country: Japan
Target Year: 2038
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 588.7 per 100,000
• Life Expectancy: 88.9 years
• Annual Improvement: 1.74%

CONFIDENCE INTERVALS (95%):
• Lower: 500.4
• Upper: 677.0

Projection assumes continuation of current trends.
Uncertainty increases with projection horizon.


Instruction: What is the life expectancy for a 82 year old both in Germany as of 2018?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Germany
• Age: 82 years
• Sex: Both
• Reference Year: 2018

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 82 (e_82): 0.0 years
• Expected Age at Death: 82.0 years
• Median Survival Time: 0.0 years
• Modal Age at Death: 77.0 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_82): 0.7%
• 10-Year Survival (₁₀p_82): 0.0%
• 20-Year Survival (₂₀p_82): 0.0%

MORTALITY METRICS:
• Force of Mortality (μ_82): 1.00000
• Probability of Death within 1 Year (q_82): 0.63212
• Hazard Rate: 4.60517

COMPARATIVE CONTEXT:
• Global Average at Age 82: -0.8 years
• Regional Rank: Top 11 globally
• Historical Trend: Stable

Based on 486,254 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.

Human: What is the life expectancy for a 82 year old both in Germany as of 2018?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Germany
• Age: 82 years
• Sex: Both
• Reference Year: 2018

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 82 (e_82): 0.0 years
• Expected Age at Death: 82.0 years
• Median Survival Time: 0.0 years
• Modal Age at Death: 77.0 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_82): 0.7%
• 10-Year Survival (₁₀p_82): 0.0%
• 20-Year Survival (₂₀p_82): 0.0%

MORTALITY METRICS:
• Force of Mortality (μ_82): 1.00000
• Probability of Death within 1 Year (q_82): 0.63212
• Hazard Rate: 4.60517

COMPARATIVE CONTEXT:
• Global Average at Age 82: -0.8 years
• Regional Rank: Top 11 globally
• Historical Trend: Stable

Based on 486,254 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.


Instruction: Calculate excess mortality during 2022 heat wave in USA for Q3 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: 2022 heat wave
Location: USA
Period: Q3 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 81,852
• Observed Deaths: 103,199
• Excess Deaths: 21,347
• Excess Mortality Rate: 26.1%
• P-score: 26.1%
• Z-score: 4.67 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.6% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 6.9% (2,134 deaths)
• 45-64 years: 16.0% (5,336 deaths)
• 65-74 years: 27.7% (5,336 deaths)
• 75+ years: 31.7% (8,538 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 13,185 (69%)
• Indirect (probable): 5,178 (21%)
• Collateral (delayed care): 3,021 (17%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [18,144, 24,549]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 259425
Economic Impact: $4.0 billion
Quality-Adjusted Life Years Lost: 180769

Human: Calculate excess mortality during 2022 heat wave in USA for Q3 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: 2022 heat wave
Location: USA
Period: Q3 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 81,852
• Observed Deaths: 103,199
• Excess Deaths: 21,347
• Excess Mortality Rate: 26.1%
• P-score: 26.1%
• Z-score: 4.67 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.6% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 6.9% (2,134 deaths)
• 45-64 years: 16.0% (5,336 deaths)
• 65-74 years: 27.7% (5,336 deaths)
• 75+ years: 31.7% (8,538 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 13,185 (69%)
• Indirect (probable): 5,178 (21%)
• Collateral (delayed care): 3,021 (17%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [18,144, 24,549]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 259425
Economic Impact: $4.0 billion
Quality-Adjusted Life Years Lost: 180769


Instruction: Analyze mortality differences by education in the USA

Response:
DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Education
Country: USA
Analysis Period: 2023

MORTALITY RATES BY EDUCATION (per 100,000):
• Less than High School: 543.9
• High School: 1052.5
• Some College: 1107.4
• Bachelor's: 1110.2
• Graduate Degree: 771.7

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.77
• Rate Difference: 713.4 per 100,000
• Population Attributable Risk: 10.2%
• Gini Coefficient: 0.188

LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 81.4 years
• High School: 81.1 years
• Some College: 84.5 years
• Bachelor's: 82.4 years
• Graduate Degree: 77.2 years

CONTRIBUTING FACTORS:
• Healthcare Access: 32% of disparity
• Socioeconomic Status: 26% of disparity
• Environmental Factors: 24% of disparity
• Behavioral Factors: 17% of disparity
• Biological Factors: 9% of disparity

TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: +0.7%

Social determinants explain 66% of observed mortality differences.

Human: Analyze mortality differences by education in the USA

Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Education
Country: USA
Analysis Period: 2023

MORTALITY RATES BY EDUCATION (per 100,000):
• Less than High School: 543.9
• High School: 1052.5
• Some College: 1107.4
• Bachelor's: 1110.2
• Graduate Degree: 771.7

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.77
• Rate Difference: 713.4 per 100,000
• Population Attributable Risk: 10.2%
• Gini Coefficient: 0.188

LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 81.4 years
• High School: 81.1 years
• Some College: 84.5 years
• Bachelor's: 82.4 years
• Graduate Degree: 77.2 years

CONTRIBUTING FACTORS:
• Healthcare Access: 32% of disparity
• Socioeconomic Status: 26% of disparity
• Environmental Factors: 24% of disparity
• Behavioral Factors: 17% of disparity
• Biological Factors: 9% of disparity

TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: +0.7%

Social determinants explain 66% of observed mortality differences.


Instruction: Calculate excess mortality during COVID-19 pandemic in USA for 2020

Response:
EXCESS MORTALITY ANALYSIS

Event: COVID-19 pandemic
Location: USA
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 52,165
• Observed Deaths: 69,351
• Excess Deaths: 17,186
• Excess Mortality Rate: 32.9%
• P-score: 32.9%
• Z-score: 4.85 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.9% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -4.5% (1,718 deaths)
• 45-64 years: 19.9% (4,296 deaths)
• 65-74 years: 13.3% (4,296 deaths)
• 75+ years: 31.9% (6,874 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 8,753 (66%)
• Indirect (probable): 3,580 (11%)
• Collateral (delayed care): 2,252 (12%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [14,608, 19,763]
• Probability of chance: < 0.001
• Power: 0.99

Years of Life Lost: 247589
Economic Impact: $4.6 billion
Quality-Adjusted Life Years Lost: 192350

Human: Calculate excess mortality during COVID-19 pandemic in USA for 2020

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: COVID-19 pandemic
Location: USA
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 52,165
• Observed Deaths: 69,351
• Excess Deaths: 17,186
• Excess Mortality Rate: 32.9%
• P-score: 32.9%
• Z-score: 4.85 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.9% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -4.5% (1,718 deaths)
• 45-64 years: 19.9% (4,296 deaths)
• 65-74 years: 13.3% (4,296 deaths)
• 75+ years: 31.9% (6,874 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 8,753 (66%)
• Indirect (probable): 3,580 (11%)
• Collateral (delayed care): 2,252 (12%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [14,608, 19,763]
• Probability of chance: < 0.001
• Power: 0.99

Years of Life Lost: 247589
Economic Impact: $4.6 billion
Quality-Adjusted Life Years Lost: 192350


Instruction: Calculate excess mortality during 2022 heat wave in France for Q4 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: 2022 heat wave
Location: France
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 43,957
• Observed Deaths: 51,151
• Excess Deaths: 7,194
• Excess Mortality Rate: 16.4%
• P-score: 16.4%
• Z-score: 3.76 (p < 0.001)

BASELINE CALCULATION:
• Method: Farrington surveillance
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.0% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -0.4% (719 deaths)
• 45-64 years: 13.1% (1,798 deaths)
• 65-74 years: 28.1% (1,798 deaths)
• 75+ years: 27.7% (2,877 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 5,367 (56%)
• Indirect (probable): 1,299 (22%)
• Collateral (delayed care): 1,093 (14%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [6,114, 8,273]
• Probability of chance: < 0.001
• Power: 0.95

Years of Life Lost: 83748
Economic Impact: $1.3 billion
Quality-Adjusted Life Years Lost: 58279

Human: Calculate excess mortality during 2022 heat wave in France for Q4 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: 2022 heat wave
Location: France
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 43,957
• Observed Deaths: 51,151
• Excess Deaths: 7,194
• Excess Mortality Rate: 16.4%
• P-score: 16.4%
• Z-score: 3.76 (p < 0.001)

BASELINE CALCULATION:
• Method: Farrington surveillance
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.0% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -0.4% (719 deaths)
• 45-64 years: 13.1% (1,798 deaths)
• 65-74 years: 28.1% (1,798 deaths)
• 75+ years: 27.7% (2,877 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 5,367 (56%)
• Indirect (probable): 1,299 (22%)
• Collateral (delayed care): 1,093 (14%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [6,114, 8,273]
• Probability of chance: < 0.001
• Power: 0.95

Years of Life Lost: 83748
Economic Impact: $1.3 billion
Quality-Adjusted Life Years Lost: 58279


Instruction: Mortality risk assessment for 10 year old over next 10 years

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 10 years
• Assessment Period: 10 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: heart disease, diabetes

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_10): 0.000949 (0.0949%)
• 10-Year Death Probability (₍10₎q_10): 0.009451 (0.945%)
• Survival Probability (₍10₎p_10): 0.990549 (99.055%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_10): 0.000950
• Hazard Rate (h_10): 0.000950
• Cumulative Hazard (H_10): 0.009496
• Median Future Lifetime: 729.9 years

RISK CLASSIFICATION:
• Mortality Ratio: 0.9x standard
• Risk Category: Preferred Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 0%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.008033
• Upper Bound: 0.010869

Analysis based on 84,841 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Mortality risk assessment for 10 year old over next 10 years

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 10 years
• Assessment Period: 10 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: heart disease, diabetes

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_10): 0.000949 (0.0949%)
• 10-Year Death Probability (₍10₎q_10): 0.009451 (0.945%)
• Survival Probability (₍10₎p_10): 0.990549 (99.055%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_10): 0.000950
• Hazard Rate (h_10): 0.000950
• Cumulative Hazard (H_10): 0.009496
• Median Future Lifetime: 729.9 years

RISK CLASSIFICATION:
• Mortality Ratio: 0.9x standard
• Risk Category: Preferred Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 0%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.008033
• Upper Bound: 0.010869

Analysis based on 84,841 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Summarize annuity mortality experience study results

Response:
MORTALITY EXPERIENCE STUDY

Study Type: Annuity Insurance
Study Period: 2020-2023
Exposure: 666634 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.90
• Deaths Actual: 6,243
• Deaths Expected: 7,170

BY DURATION:
• Select Period (Years 1-5): 0.82
• Ultimate (Years 6+): 1.02

Statistical confidence: 95% CI [0.91, 1.12]

Human: Summarize annuity mortality experience study results

Actuarial AI: MORTALITY EXPERIENCE STUDY

Study Type: Annuity Insurance
Study Period: 2020-2023
Exposure: 666634 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.90
• Deaths Actual: 6,243
• Deaths Expected: 7,170

BY DURATION:
• Select Period (Years 1-5): 0.82
• Ultimate (Years 6+): 1.02

Statistical confidence: 95% CI [0.91, 1.12]


Instruction: Mortality risk assessment for 94 year old over next 5 years

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 94 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: hypertension, cancer history, heart disease

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_94): 0.016461 (1.6461%)
• 5-Year Death Probability (₍5₎q_94): 0.079642 (7.964%)
• Survival Probability (₍5₎p_94): 0.920358 (92.036%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_94): 0.016598
• Hazard Rate (h_94): 0.016598
• Cumulative Hazard (H_94): 0.082992
• Median Future Lifetime: 41.8 years

RISK CLASSIFICATION:
• Mortality Ratio: 16.5x standard
• Risk Category: Substandard
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 1546%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.067696
• Upper Bound: 0.091588

Analysis based on 95,781 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Mortality risk assessment for 94 year old over next 5 years

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 94 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: hypertension, cancer history, heart disease

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_94): 0.016461 (1.6461%)
• 5-Year Death Probability (₍5₎q_94): 0.079642 (7.964%)
• Survival Probability (₍5₎p_94): 0.920358 (92.036%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_94): 0.016598
• Hazard Rate (h_94): 0.016598
• Cumulative Hazard (H_94): 0.082992
• Median Future Lifetime: 41.8 years

RISK CLASSIFICATION:
• Mortality Ratio: 16.5x standard
• Risk Category: Substandard
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 1546%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.067696
• Upper Bound: 0.091588

Analysis based on 95,781 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Calculate the present value of a life annuity for a 48 year old at 3.0% interest

Response:
LIFE ANNUITY VALUATION

Parameters:
• Age (x): 48
• Interest Rate (i): 3.01%
• Discount Factor (v): 0.970748
• Mortality Table: 2017 CSO

ANNUITY VALUES:
• Whole Life Annuity-Due (ä_48): 14.6206
• Whole Life Annuity-Immediate (a_48): 13.6206
• Temporary Annuity-Due (ä_48:20⌉): 14.6206
• Deferred Annuity (₁₀|ä_48): 9.0045

COMMUTATION FUNCTIONS:
• D_48 = v^48 × l_48: 3598.20
• N_48 = Σ D_k (k≥48): 43528.03
• S_48 = Σ N_k (k≥48): 228414.31

CALCULATION:
ä_48 = N_48 / D_48 = 14.6206

MONTHLY CONVERSION:
• Annual Annuity: $10000.00
• Monthly Payment: $837.17
• Conversion Factor (12): 11.834

Present Value of $1,000/month for life: $14418666.84

Human: Calculate the present value of a life annuity for a 48 year old at 3.0% interest

Actuarial AI: LIFE ANNUITY VALUATION

Parameters:
• Age (x): 48
• Interest Rate (i): 3.01%
• Discount Factor (v): 0.970748
• Mortality Table: 2017 CSO

ANNUITY VALUES:
• Whole Life Annuity-Due (ä_48): 14.6206
• Whole Life Annuity-Immediate (a_48): 13.6206
• Temporary Annuity-Due (ä_48:20⌉): 14.6206
• Deferred Annuity (₁₀|ä_48): 9.0045

COMMUTATION FUNCTIONS:
• D_48 = v^48 × l_48: 3598.20
• N_48 = Σ D_k (k≥48): 43528.03
• S_48 = Σ N_k (k≥48): 228414.31

CALCULATION:
ä_48 = N_48 / D_48 = 14.6206

MONTHLY CONVERSION:
• Annual Annuity: $10000.00
• Monthly Payment: $837.17
• Conversion Factor (12): 11.834

Present Value of $1,000/month for life: $14418666.84


Instruction: Calculate Variable Universal Life life insurance premium for 69 year old female, $2,000,000 coverage, Standard Plus rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $2,000,000
• Duration: Lifetime Coverage
• Issue Age: 69
• Sex: Female
• Underwriting Class: Standard Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_69): 0.003918
• Underwriting Multiplier: 0.9x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 53% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $11752.50
• Expense Charge: $2938.13
• Reserve Accumulation: $3917.50
• Profit Margin: $979.38
• Gross Annual Premium: $19587.50

PAYMENT OPTIONS:
• Annual: $19587.50
• Semi-Annual: $10185.50 (x2 = $20371.00/year)
• Quarterly: $5190.69 (x4 = $20762.75/year)
• Monthly: $1762.88 (x12 = $21154.50/year)

RESERVE CALCULATIONS:
• Net Level Premium: $14690.63
• First Year Reserve: $3917.50
• Terminal Reserve (Year -4): $789685.86

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 8.2%
Profit Margin: 14.9%
Lapse Assumption: 6.5% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Variable Universal Life life insurance premium for 69 year old female, $2,000,000 coverage, Standard Plus rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $2,000,000
• Duration: Lifetime Coverage
• Issue Age: 69
• Sex: Female
• Underwriting Class: Standard Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_69): 0.003918
• Underwriting Multiplier: 0.9x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 53% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $11752.50
• Expense Charge: $2938.13
• Reserve Accumulation: $3917.50
• Profit Margin: $979.38
• Gross Annual Premium: $19587.50

PAYMENT OPTIONS:
• Annual: $19587.50
• Semi-Annual: $10185.50 (x2 = $20371.00/year)
• Quarterly: $5190.69 (x4 = $20762.75/year)
• Monthly: $1762.88 (x12 = $21154.50/year)

RESERVE CALCULATIONS:
• Net Level Premium: $14690.63
• First Year Reserve: $3917.50
• Terminal Reserve (Year -4): $789685.86

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 8.2%
Profit Margin: 14.9%
Lapse Assumption: 6.5% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Show survival curve for Canada population in 2022

Response:
SURVIVAL CURVE ANALYSIS

Population: Canada Combined
Reference Year: 2022
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            2         0.00002         83.6
    1          99,998           13         0.00013         78.4
    5          99,985           31         0.00031         75.4
   10          99,954           63         0.00063         67.8
   20          99,891          139         0.00139         55.2
   30          99,752          246         0.00247         49.3
   40          99,506          321         0.00323         35.0
   50          99,185          531         0.00535         26.9
   60          98,654          923         0.00936         16.9
   70          97,731        1,096         0.01121          6.1
   80          96,635        1,979         0.02048          0.0
   90          94,656        2,422         0.02559          3.5
  100          92,234        2,761         0.02993          3.1
  110          89,473       89,473         1.00000          1.0

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 79.6 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.7%
• Probability of Surviving to 80: 96.6%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.79

The survival curve follows Gompertz law after age 30.
Data sourced from 333,140 death certificates.

Human: Show survival curve for Canada population in 2022

Actuarial AI: SURVIVAL CURVE ANALYSIS

Population: Canada Combined
Reference Year: 2022
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            2         0.00002         83.6
    1          99,998           13         0.00013         78.4
    5          99,985           31         0.00031         75.4
   10          99,954           63         0.00063         67.8
   20          99,891          139         0.00139         55.2
   30          99,752          246         0.00247         49.3
   40          99,506          321         0.00323         35.0
   50          99,185          531         0.00535         26.9
   60          98,654          923         0.00936         16.9
   70          97,731        1,096         0.01121          6.1
   80          96,635        1,979         0.02048          0.0
   90          94,656        2,422         0.02559          3.5
  100          92,234        2,761         0.02993          3.1
  110          89,473       89,473         1.00000          1.0

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 79.6 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.7%
• Probability of Surviving to 80: 96.6%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.79

The survival curve follows Gompertz law after age 30.
Data sourced from 333,140 death certificates.


Instruction: Calculate the 30-year death probability for a 85 year oldsmoker with hypertension

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 85 years
• Assessment Period: 30 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: hypertension

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_85): 0.005545 (0.5545%)
• 30-Year Death Probability (₍30₎q_85): 0.153633 (15.363%)
• Survival Probability (₍30₎p_85): 0.846367 (84.637%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_85): 0.005560
• Hazard Rate (h_85): 0.005560
• Cumulative Hazard (H_85): 0.166802
• Median Future Lifetime: 124.7 years

RISK CLASSIFICATION:
• Mortality Ratio: 5.5x standard
• Risk Category: Standard
• Insurability: Standard with loading
• Recommended Premium Loading: 454%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.130588
• Upper Bound: 0.176678

Analysis based on 139,171 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Calculate the 30-year death probability for a 85 year oldsmoker with hypertension

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 85 years
• Assessment Period: 30 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: hypertension

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_85): 0.005545 (0.5545%)
• 30-Year Death Probability (₍30₎q_85): 0.153633 (15.363%)
• Survival Probability (₍30₎p_85): 0.846367 (84.637%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_85): 0.005560
• Hazard Rate (h_85): 0.005560
• Cumulative Hazard (H_85): 0.166802
• Median Future Lifetime: 124.7 years

RISK CLASSIFICATION:
• Mortality Ratio: 5.5x standard
• Risk Category: Standard
• Insurability: Standard with loading
• Recommended Premium Loading: 454%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.130588
• Upper Bound: 0.176678

Analysis based on 139,171 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Calculate excess mortality during 2021 cold snap in Brazil for 2020

Response:
EXCESS MORTALITY ANALYSIS

Event: 2021 cold snap
Location: Brazil
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 50,226
• Observed Deaths: 55,447
• Excess Deaths: 5,221
• Excess Mortality Rate: 10.4%
• P-score: 10.4%
• Z-score: 3.87 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.5% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -2.9% (522 deaths)
• 45-64 years: 6.5% (1,305 deaths)
• 65-74 years: 12.4% (1,305 deaths)
• 75+ years: 16.5% (2,088 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 3,789 (53%)
• Indirect (probable): 1,451 (13%)
• Collateral (delayed care): 831 (14%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [4,437, 6,004]
• Probability of chance: < 0.001
• Power: 0.96

Years of Life Lost: 73735
Economic Impact: $2.2 billion
Quality-Adjusted Life Years Lost: 61496

Human: Calculate excess mortality during 2021 cold snap in Brazil for 2020

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: 2021 cold snap
Location: Brazil
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 50,226
• Observed Deaths: 55,447
• Excess Deaths: 5,221
• Excess Mortality Rate: 10.4%
• P-score: 10.4%
• Z-score: 3.87 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.5% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -2.9% (522 deaths)
• 45-64 years: 6.5% (1,305 deaths)
• 65-74 years: 12.4% (1,305 deaths)
• 75+ years: 16.5% (2,088 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 3,789 (53%)
• Indirect (probable): 1,451 (13%)
• Collateral (delayed care): 831 (14%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [4,437, 6,004]
• Probability of chance: < 0.001
• Power: 0.96

Years of Life Lost: 73735
Economic Impact: $2.2 billion
Quality-Adjusted Life Years Lost: 61496


Instruction: Calculate Whole Life life insurance premium for 33 year old female, $500,000 coverage, Standard Plus rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 33
• Sex: Female
• Underwriting Class: Standard Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_33): 0.001180
• Underwriting Multiplier: 0.9x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 75% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1238.92
• Expense Charge: $309.73
• Reserve Accumulation: $412.97
• Profit Margin: $103.24
• Gross Annual Premium: $2064.87

PAYMENT OPTIONS:
• Annual: $2064.87
• Semi-Annual: $1073.73 (x2 = $2147.47/year)
• Quarterly: $547.19 (x4 = $2188.77/year)
• Monthly: $185.84 (x12 = $2230.06/year)

RESERVE CALCULATIONS:
• Net Level Premium: $1548.66
• First Year Reserve: $412.97
• Terminal Reserve (Year 32): $273295.88

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2020
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 10.2%
Profit Margin: 8.8%
Lapse Assumption: 4.4% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Whole Life life insurance premium for 33 year old female, $500,000 coverage, Standard Plus rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 33
• Sex: Female
• Underwriting Class: Standard Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_33): 0.001180
• Underwriting Multiplier: 0.9x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 75% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1238.92
• Expense Charge: $309.73
• Reserve Accumulation: $412.97
• Profit Margin: $103.24
• Gross Annual Premium: $2064.87

PAYMENT OPTIONS:
• Annual: $2064.87
• Semi-Annual: $1073.73 (x2 = $2147.47/year)
• Quarterly: $547.19 (x4 = $2188.77/year)
• Monthly: $185.84 (x12 = $2230.06/year)

RESERVE CALCULATIONS:
• Net Level Premium: $1548.66
• First Year Reserve: $412.97
• Terminal Reserve (Year 32): $273295.88

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2020
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 10.2%
Profit Margin: 8.8%
Lapse Assumption: 4.4% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Compare rural vs other area mortality rates in UK

Response:
GEOGRAPHIC MORTALITY ANALYSIS

Country: UK
Focus: Rural Areas

MORTALITY RATES (per 100,000):
• Urban: 707.8
• Rural: 824.4
• Suburban: 705.9

Rural areas show 16.5% higher mortality.
Primary factors: healthcare access, emergency response times, demographics.

Human: Compare rural vs other area mortality rates in UK

Actuarial AI: GEOGRAPHIC MORTALITY ANALYSIS

Country: UK
Focus: Rural Areas

MORTALITY RATES (per 100,000):
• Urban: 707.8
• Rural: 824.4
• Suburban: 705.9

Rural areas show 16.5% higher mortality.
Primary factors: healthcare access, emergency response times, demographics.


Instruction: Calculate Whole Life life insurance premium for 47 year old female, $750,000 coverage, Preferred rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 47
• Sex: Female
• Underwriting Class: Preferred

PREMIUM COMPUTATION:
• Base Mortality Rate (q_47): 0.001568
• Underwriting Multiplier: 0.75x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 83% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $2469.60
• Expense Charge: $617.40
• Reserve Accumulation: $823.20
• Profit Margin: $205.80
• Gross Annual Premium: $4115.99

PAYMENT OPTIONS:
• Annual: $4115.99
• Semi-Annual: $2140.32 (x2 = $4280.63/year)
• Quarterly: $1090.74 (x4 = $4362.95/year)
• Monthly: $370.44 (x12 = $4445.27/year)

RESERVE CALCULATIONS:
• Net Level Premium: $3086.99
• First Year Reserve: $823.20
• Terminal Reserve (Year 18): $378329.64

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 9.8%
Profit Margin: 12.2%
Lapse Assumption: 7.6% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Whole Life life insurance premium for 47 year old female, $750,000 coverage, Preferred rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 47
• Sex: Female
• Underwriting Class: Preferred

PREMIUM COMPUTATION:
• Base Mortality Rate (q_47): 0.001568
• Underwriting Multiplier: 0.75x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 83% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $2469.60
• Expense Charge: $617.40
• Reserve Accumulation: $823.20
• Profit Margin: $205.80
• Gross Annual Premium: $4115.99

PAYMENT OPTIONS:
• Annual: $4115.99
• Semi-Annual: $2140.32 (x2 = $4280.63/year)
• Quarterly: $1090.74 (x4 = $4362.95/year)
• Monthly: $370.44 (x12 = $4445.27/year)

RESERVE CALCULATIONS:
• Net Level Premium: $3086.99
• First Year Reserve: $823.20
• Terminal Reserve (Year 18): $378329.64

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 9.8%
Profit Margin: 12.2%
Lapse Assumption: 7.6% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Analyze mortality differences by marital status in the USA

Response:
DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Marital Status
Country: USA
Analysis Period: 2019

MORTALITY RATES BY MARITAL STATUS (per 100,000):
• Married: 249.1
• Single: 932.5
• Divorced: 719.0
• Widowed: 976.2

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.56
• Rate Difference: 697.9 per 100,000
• Population Attributable Risk: 24.2%
• Gini Coefficient: 0.138

LIFE EXPECTANCY BY MARITAL STATUS:
• Married: 80.2 years
• Single: 84.8 years
• Divorced: 70.3 years
• Widowed: 71.6 years

CONTRIBUTING FACTORS:
• Healthcare Access: 34% of disparity
• Socioeconomic Status: 35% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 11% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +1.0%

Social determinants explain 63% of observed mortality differences.

Human: Analyze mortality differences by marital status in the USA

Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Marital Status
Country: USA
Analysis Period: 2019

MORTALITY RATES BY MARITAL STATUS (per 100,000):
• Married: 249.1
• Single: 932.5
• Divorced: 719.0
• Widowed: 976.2

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.56
• Rate Difference: 697.9 per 100,000
• Population Attributable Risk: 24.2%
• Gini Coefficient: 0.138

LIFE EXPECTANCY BY MARITAL STATUS:
• Married: 80.2 years
• Single: 84.8 years
• Divorced: 70.3 years
• Widowed: 71.6 years

CONTRIBUTING FACTORS:
• Healthcare Access: 34% of disparity
• Socioeconomic Status: 35% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 11% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +1.0%

Social determinants explain 63% of observed mortality differences.


Instruction: Calculate Whole Life life insurance premium for 57 year old male, $750,000 coverage, Standard Plus rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 57
• Sex: Male
• Underwriting Class: Standard Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_57): 0.003553
• Underwriting Multiplier: 0.9x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 92% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $5595.65
• Expense Charge: $1398.91
• Reserve Accumulation: $1865.22
• Profit Margin: $466.30
• Gross Annual Premium: $9326.09

PAYMENT OPTIONS:
• Annual: $9326.09
• Semi-Annual: $4849.57 (x2 = $9699.13/year)
• Quarterly: $2471.41 (x4 = $9885.65/year)
• Monthly: $839.35 (x12 = $10072.18/year)

RESERVE CALCULATIONS:
• Net Level Premium: $6994.57
• First Year Reserve: $1865.22
• Terminal Reserve (Year 8): $423275.32

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Male Ultimate

Internal Rate of Return: 8.9%
Profit Margin: 14.6%
Lapse Assumption: 4.2% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Whole Life life insurance premium for 57 year old male, $750,000 coverage, Standard Plus rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 57
• Sex: Male
• Underwriting Class: Standard Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_57): 0.003553
• Underwriting Multiplier: 0.9x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 92% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $5595.65
• Expense Charge: $1398.91
• Reserve Accumulation: $1865.22
• Profit Margin: $466.30
• Gross Annual Premium: $9326.09

PAYMENT OPTIONS:
• Annual: $9326.09
• Semi-Annual: $4849.57 (x2 = $9699.13/year)
• Quarterly: $2471.41 (x4 = $9885.65/year)
• Monthly: $839.35 (x12 = $10072.18/year)

RESERVE CALCULATIONS:
• Net Level Premium: $6994.57
• First Year Reserve: $1865.22
• Terminal Reserve (Year 8): $423275.32

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Male Ultimate

Internal Rate of Return: 8.9%
Profit Margin: 14.6%
Lapse Assumption: 4.2% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: What is the life expectancy for a 29 year old female in Italy as of 2017?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Italy
• Age: 29 years
• Sex: Female
• Reference Year: 2017

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 29 (e_29): 59.7 years
• Expected Age at Death: 88.7 years
• Median Survival Time: 41.4 years
• Modal Age at Death: 83.7 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_29): 92.1%
• 10-Year Survival (₁₀p_29): 84.8%
• 20-Year Survival (₂₀p_29): 71.9%

MORTALITY METRICS:
• Force of Mortality (μ_29): 0.01648
• Probability of Death within 1 Year (q_29): 0.01634
• Hazard Rate: 0.01662

COMPARATIVE CONTEXT:
• Global Average at Age 29: 54.4 years
• Regional Rank: Top 36 globally
• Historical Trend: Improving

Based on 475,940 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.9%.

Human: What is the life expectancy for a 29 year old female in Italy as of 2017?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Italy
• Age: 29 years
• Sex: Female
• Reference Year: 2017

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 29 (e_29): 59.7 years
• Expected Age at Death: 88.7 years
• Median Survival Time: 41.4 years
• Modal Age at Death: 83.7 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_29): 92.1%
• 10-Year Survival (₁₀p_29): 84.8%
• 20-Year Survival (₂₀p_29): 71.9%

MORTALITY METRICS:
• Force of Mortality (μ_29): 0.01648
• Probability of Death within 1 Year (q_29): 0.01634
• Hazard Rate: 0.01662

COMPARATIVE CONTEXT:
• Global Average at Age 29: 54.4 years
• Regional Rank: Top 36 globally
• Historical Trend: Improving

Based on 475,940 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.9%.


Instruction: Calculate excess mortality during seasonal flu in India for 2020

Response:
EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: India
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 27,626
• Observed Deaths: 37,374
• Excess Deaths: 9,748
• Excess Mortality Rate: 35.3%
• P-score: 35.3%
• Z-score: 3.10 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.8% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -1.7% (974 deaths)
• 45-64 years: 5.8% (2,437 deaths)
• 65-74 years: 22.0% (2,437 deaths)
• 75+ years: 30.6% (3,899 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 6,637 (56%)
• Indirect (probable): 2,777 (14%)
• Collateral (delayed care): 1,405 (18%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [8,285, 11,210]
• Probability of chance: < 0.001
• Power: 0.96

Years of Life Lost: 118527
Economic Impact: $2.4 billion
Quality-Adjusted Life Years Lost: 78383

Human: Calculate excess mortality during seasonal flu in India for 2020

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: India
Period: 2020

MORTALITY METRICS:
• Expected Deaths (Baseline): 27,626
• Observed Deaths: 37,374
• Excess Deaths: 9,748
• Excess Mortality Rate: 35.3%
• P-score: 35.3%
• Z-score: 3.10 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.8% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -1.7% (974 deaths)
• 45-64 years: 5.8% (2,437 deaths)
• 65-74 years: 22.0% (2,437 deaths)
• 75+ years: 30.6% (3,899 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 6,637 (56%)
• Indirect (probable): 2,777 (14%)
• Collateral (delayed care): 1,405 (18%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [8,285, 11,210]
• Probability of chance: < 0.001
• Power: 0.96

Years of Life Lost: 118527
Economic Impact: $2.4 billion
Quality-Adjusted Life Years Lost: 78383


Instruction: Calculate excess mortality during seasonal flu in USA for Q2 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: USA
Period: Q2 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 76,955
• Observed Deaths: 89,067
• Excess Deaths: 12,112
• Excess Mortality Rate: 15.7%
• P-score: 15.7%
• Z-score: 5.78 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.1% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -3.2% (1,211 deaths)
• 45-64 years: 17.5% (3,028 deaths)
• 65-74 years: 21.5% (3,028 deaths)
• 75+ years: 33.7% (4,844 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 8,997 (74%)
• Indirect (probable): 1,790 (17%)
• Collateral (delayed care): 2,140 (12%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [10,295, 13,928]
• Probability of chance: < 0.001
• Power: 0.98

Years of Life Lost: 130367
Economic Impact: $8.4 billion
Quality-Adjusted Life Years Lost: 111709

Human: Calculate excess mortality during seasonal flu in USA for Q2 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: USA
Period: Q2 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 76,955
• Observed Deaths: 89,067
• Excess Deaths: 12,112
• Excess Mortality Rate: 15.7%
• P-score: 15.7%
• Z-score: 5.78 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.1% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: -3.2% (1,211 deaths)
• 45-64 years: 17.5% (3,028 deaths)
• 65-74 years: 21.5% (3,028 deaths)
• 75+ years: 33.7% (4,844 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 8,997 (74%)
• Indirect (probable): 1,790 (17%)
• Collateral (delayed care): 2,140 (12%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [10,295, 13,928]
• Probability of chance: < 0.001
• Power: 0.98

Years of Life Lost: 130367
Economic Impact: $8.4 billion
Quality-Adjusted Life Years Lost: 111709


Instruction: What is the mortality rate for Cancer in Australia for 45-64 in 2019?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Cancer
Location: Australia
Year: 2019
Age Group: 45-64

MORTALITY STATISTICS:
• Crude Death Rate: 174.7 per 100,000 population
• Age-Adjusted Rate: 154.6 per 100,000
• Total Deaths: 2,858,703
• Percentage of All Deaths: 22.5%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 209.7 per 100,000
• Female Death Rate: 148.5 per 100,000
• Sex Ratio (M:F): 1.43:1

TREND ANALYSIS:
• 5-Year Change: -10.3%
• 10-Year Change: -11.6%
• Annual Percentage Change: +1.6%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 31671439
• Economic Burden: $55.4 billion annually
• Preventable Deaths: 41%

RISK FACTORS:
• Tobacco use: 30% attributable
• Diet: 20%
• Infections: 15%
• Alcohol: 10%
• Environmental: 10%

International Classification of Diseases (ICD-10): C00-C97
Data Quality: Complete (93% coverage)

Human: What is the mortality rate for Cancer in Australia for 45-64 in 2019?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Cancer
Location: Australia
Year: 2019
Age Group: 45-64

MORTALITY STATISTICS:
• Crude Death Rate: 174.7 per 100,000 population
• Age-Adjusted Rate: 154.6 per 100,000
• Total Deaths: 2,858,703
• Percentage of All Deaths: 22.5%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 209.7 per 100,000
• Female Death Rate: 148.5 per 100,000
• Sex Ratio (M:F): 1.43:1

TREND ANALYSIS:
• 5-Year Change: -10.3%
• 10-Year Change: -11.6%
• Annual Percentage Change: +1.6%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 31671439
• Economic Burden: $55.4 billion annually
• Preventable Deaths: 41%

RISK FACTORS:
• Tobacco use: 30% attributable
• Diet: 20%
• Infections: 15%
• Alcohol: 10%
• Environmental: 10%

International Classification of Diseases (ICD-10): C00-C97
Data Quality: Complete (93% coverage)


Instruction: Show survival curve for Japan population in 2015

Response:
SURVIVAL CURVE ANALYSIS

Population: Japan Combined
Reference Year: 2015
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            2         0.00002         78.6
    1          99,998           11         0.00011         76.7
    5          99,987           25         0.00025         77.5
   10          99,962           68         0.00068         74.1
   20          99,894          104         0.00104         59.7
   30          99,790          247         0.00248         49.7
   40          99,543          283         0.00284         39.7
   50          99,260          601         0.00605         33.3
   60          98,659          663         0.00672         20.1
   70          97,996        1,020         0.01041         13.6
   80          96,976        1,482         0.01528          0.0
   90          95,494        2,762         0.02892          2.9
  100          92,732        2,911         0.03139          1.9
  110          89,821       89,821         1.00000          1.8

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 79.3 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.7%
• Probability of Surviving to 80: 97.0%

CURVE CHARACTERISTICS:
• Type: Type I (Rectangular)
• Compression: High
• Rectangularization Index: 0.84

The survival curve follows Gompertz law after age 30.
Data sourced from 277,588 death certificates.

Human: Show survival curve for Japan population in 2015

Actuarial AI: SURVIVAL CURVE ANALYSIS

Population: Japan Combined
Reference Year: 2015
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            2         0.00002         78.6
    1          99,998           11         0.00011         76.7
    5          99,987           25         0.00025         77.5
   10          99,962           68         0.00068         74.1
   20          99,894          104         0.00104         59.7
   30          99,790          247         0.00248         49.7
   40          99,543          283         0.00284         39.7
   50          99,260          601         0.00605         33.3
   60          98,659          663         0.00672         20.1
   70          97,996        1,020         0.01041         13.6
   80          96,976        1,482         0.01528          0.0
   90          95,494        2,762         0.02892          2.9
  100          92,732        2,911         0.03139          1.9
  110          89,821       89,821         1.00000          1.8

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 79.3 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.7%
• Probability of Surviving to 80: 97.0%

CURVE CHARACTERISTICS:
• Type: Type I (Rectangular)
• Compression: High
• Rectangularization Index: 0.84

The survival curve follows Gompertz law after age 30.
Data sourced from 277,588 death certificates.


Instruction: Show survival curve for Brazil male in 2016

Response:
SURVIVAL CURVE ANALYSIS

Population: Brazil Male
Reference Year: 2016
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            3         0.00003         79.8
    1          99,997           16         0.00016         80.2
    5          99,981           37         0.00037         78.0
   10          99,944           66         0.00066         72.1
   20          99,878          176         0.00176         59.9
   30          99,702          291         0.00292         50.7
   40          99,411          472         0.00475         40.2
   50          98,939          516         0.00522         32.0
   60          98,423        1,010         0.01026         17.0
   70          97,413        1,258         0.01291          7.1
   80          96,155        2,180         0.02267          3.7
   90          93,975        3,029         0.03223          1.6
  100          90,946        3,388         0.03725          4.4
  110          87,558       87,558         1.00000          3.8

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 83.3 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.4%
• Probability of Surviving to 80: 96.2%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.72

The survival curve follows Gompertz law after age 30.
Data sourced from 143,463 death certificates.

Human: Show survival curve for Brazil male in 2016

Actuarial AI: SURVIVAL CURVE ANALYSIS

Population: Brazil Male
Reference Year: 2016
Initial Cohort: 100,000 births

SURVIVAL TABLE (l_x per 100,000):
  Age  Survivors (lx)  Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
    0         100,000            3         0.00003         79.8
    1          99,997           16         0.00016         80.2
    5          99,981           37         0.00037         78.0
   10          99,944           66         0.00066         72.1
   20          99,878          176         0.00176         59.9
   30          99,702          291         0.00292         50.7
   40          99,411          472         0.00475         40.2
   50          98,939          516         0.00522         32.0
   60          98,423        1,010         0.01026         17.0
   70          97,413        1,258         0.01291          7.1
   80          96,155        2,180         0.02267          3.7
   90          93,975        3,029         0.03223          1.6
  100          90,946        3,388         0.03725          4.4
  110          87,558       87,558         1.00000          3.8

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 83.3 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.4%
• Probability of Surviving to 80: 96.2%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.72

The survival curve follows Gompertz law after age 30.
Data sourced from 143,463 death certificates.


Instruction: Analyze mortality patterns for 1921 birth cohort

Response:
BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1921
Current Age: 103 years
Cohort Size at Birth: 2,883,999

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 72.0 years
• Current Life Expectancy: 89.1 years
• Survival to Current Age: 65.9%

HISTORICAL EXPOSURES:
• Great Depression impact

MORTALITY PATTERN:
• Peak Infant Mortality: 15.8 per 1,000
• Current Mortality Rate: 5.3 per 1,000
• Improvement Since Birth: 64%

Cohort effects explain 14% of mortality variation.

Human: Analyze mortality patterns for 1921 birth cohort

Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1921
Current Age: 103 years
Cohort Size at Birth: 2,883,999

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 72.0 years
• Current Life Expectancy: 89.1 years
• Survival to Current Age: 65.9%

HISTORICAL EXPOSURES:
• Great Depression impact

MORTALITY PATTERN:
• Peak Infant Mortality: 15.8 per 1,000
• Current Mortality Rate: 5.3 per 1,000
• Improvement Since Birth: 64%

Cohort effects explain 14% of mortality variation.


Instruction: Calculate excess mortality during 2021 cold snap in USA for Q1 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: 2021 cold snap
Location: USA
Period: Q1 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 19,927
• Observed Deaths: 27,010
• Excess Deaths: 7,083
• Excess Mortality Rate: 35.5%
• P-score: 35.5%
• Z-score: 5.40 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.0% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 8.0% (708 deaths)
• 45-64 years: 8.4% (1,770 deaths)
• 65-74 years: 18.8% (1,770 deaths)
• 75+ years: 39.3% (2,833 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 4,194 (71%)
• Indirect (probable): 1,857 (13%)
• Collateral (delayed care): 1,057 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [6,020, 8,145]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 86600
Economic Impact: $8.9 billion
Quality-Adjusted Life Years Lost: 71438

Human: Calculate excess mortality during 2021 cold snap in USA for Q1 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: 2021 cold snap
Location: USA
Period: Q1 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 19,927
• Observed Deaths: 27,010
• Excess Deaths: 7,083
• Excess Mortality Rate: 35.5%
• P-score: 35.5%
• Z-score: 5.40 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.0% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 8.0% (708 deaths)
• 45-64 years: 8.4% (1,770 deaths)
• 65-74 years: 18.8% (1,770 deaths)
• 75+ years: 39.3% (2,833 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 4,194 (71%)
• Indirect (probable): 1,857 (13%)
• Collateral (delayed care): 1,057 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [6,020, 8,145]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 86600
Economic Impact: $8.9 billion
Quality-Adjusted Life Years Lost: 71438


Instruction: What is the life expectancy for a 69 year old male in Italy as of 2021?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Italy
• Age: 69 years
• Sex: Male
• Reference Year: 2021

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 69 (e_69): 12.3 years
• Expected Age at Death: 81.3 years
• Median Survival Time: 8.5 years
• Modal Age at Death: 76.3 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_69): 68.6%
• 10-Year Survival (₁₀p_69): 47.1%
• 20-Year Survival (₂₀p_69): 22.2%

MORTALITY METRICS:
• Force of Mortality (μ_69): 0.07530
• Probability of Death within 1 Year (q_69): 0.07254
• Hazard Rate: 0.07829

COMPARATIVE CONTEXT:
• Global Average at Age 69: 14.4 years
• Regional Rank: Top 43 globally
• Historical Trend: Improving

Based on 196,841 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.9%.

Human: What is the life expectancy for a 69 year old male in Italy as of 2021?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Italy
• Age: 69 years
• Sex: Male
• Reference Year: 2021

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 69 (e_69): 12.3 years
• Expected Age at Death: 81.3 years
• Median Survival Time: 8.5 years
• Modal Age at Death: 76.3 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_69): 68.6%
• 10-Year Survival (₁₀p_69): 47.1%
• 20-Year Survival (₂₀p_69): 22.2%

MORTALITY METRICS:
• Force of Mortality (μ_69): 0.07530
• Probability of Death within 1 Year (q_69): 0.07254
• Hazard Rate: 0.07829

COMPARATIVE CONTEXT:
• Global Average at Age 69: 14.4 years
• Regional Rank: Top 43 globally
• Historical Trend: Improving

Based on 196,841 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.9%.


Instruction: Mortality risk assessment for 86 year old over next 30 years

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 86 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: obesity, hypertension, heart disease

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_86): 0.007109 (0.7109%)
• 30-Year Death Probability (₍30₎q_86): 0.192686 (19.269%)
• Survival Probability (₍30₎p_86): 0.807314 (80.731%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_86): 0.007135
• Hazard Rate (h_86): 0.007135
• Cumulative Hazard (H_86): 0.214042
• Median Future Lifetime: 97.2 years

RISK CLASSIFICATION:
• Mortality Ratio: 7.1x standard
• Risk Category: Standard
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 611%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.163783
• Upper Bound: 0.221588

Analysis based on 58,504 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Mortality risk assessment for 86 year old over next 30 years

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 86 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: obesity, hypertension, heart disease

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_86): 0.007109 (0.7109%)
• 30-Year Death Probability (₍30₎q_86): 0.192686 (19.269%)
• Survival Probability (₍30₎p_86): 0.807314 (80.731%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_86): 0.007135
• Hazard Rate (h_86): 0.007135
• Cumulative Hazard (H_86): 0.214042
• Median Future Lifetime: 97.2 years

RISK CLASSIFICATION:
• Mortality Ratio: 7.1x standard
• Risk Category: Standard
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 611%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.163783
• Upper Bound: 0.221588

Analysis based on 58,504 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Compare life expectancy between Australia, Spain, France, India and USA

Response:
INTERNATIONAL MORTALITY COMPARISON

Metric: Life Expectancy
Countries: Australia, Spain, France, India, USA
Reference Year: 2021

COMPARATIVE STATISTICS:
• Australia: 71.9 years
• Spain: 75.3 years
• France: 79.2 years
• India: 78.7 years
• USA: 70.7 years

RANKINGS:
1. France: 79.2
2. India: 78.7
3. Spain: 75.3
4. Australia: 71.9
5. USA: 70.7

STATISTICAL ANALYSIS:
• Range: 8.5
• Mean: 75.2
• Median: 75.3
• Standard Deviation: 3.5
• Coefficient of Variation: 4.6%

RELATIVE COMPARISONS:
• Best vs Worst: 0.89x difference
• Above Average: 3/5
• Global Ranking: Australia: #56, Spain: #95, France: #153

CONTRIBUTING FACTORS:
• Healthcare System: 27% of variation
• Economic Development: 22% of variation
• Public Health Policy: 19% of variation
• Demographics: 18% of variation
• Environmental Factors: 7% of variation

Convergence/Divergence: Diverging at 1.8% annually

Human: Compare life expectancy between Australia, Spain, France, India and USA

Actuarial AI: INTERNATIONAL MORTALITY COMPARISON

Metric: Life Expectancy
Countries: Australia, Spain, France, India, USA
Reference Year: 2021

COMPARATIVE STATISTICS:
• Australia: 71.9 years
• Spain: 75.3 years
• France: 79.2 years
• India: 78.7 years
• USA: 70.7 years

RANKINGS:
1. France: 79.2
2. India: 78.7
3. Spain: 75.3
4. Australia: 71.9
5. USA: 70.7

STATISTICAL ANALYSIS:
• Range: 8.5
• Mean: 75.2
• Median: 75.3
• Standard Deviation: 3.5
• Coefficient of Variation: 4.6%

RELATIVE COMPARISONS:
• Best vs Worst: 0.89x difference
• Above Average: 3/5
• Global Ranking: Australia: #56, Spain: #95, France: #153

CONTRIBUTING FACTORS:
• Healthcare System: 27% of variation
• Economic Development: 22% of variation
• Public Health Policy: 19% of variation
• Demographics: 18% of variation
• Environmental Factors: 7% of variation

Convergence/Divergence: Diverging at 1.8% annually


Instruction: Calculate Variable Universal Life life insurance premium for 61 year old female, $1,000,000 coverage, Substandard rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $1,000,000
• Duration: Lifetime Coverage
• Issue Age: 61
• Sex: Female
• Underwriting Class: Substandard

PREMIUM COMPUTATION:
• Base Mortality Rate (q_61): 0.005001
• Underwriting Multiplier: 1.5x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 70% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $7501.31
• Expense Charge: $1875.33
• Reserve Accumulation: $2500.44
• Profit Margin: $625.11
• Gross Annual Premium: $12502.19

PAYMENT OPTIONS:
• Annual: $12502.19
• Semi-Annual: $6501.14 (x2 = $13002.27/year)
• Quarterly: $3313.08 (x4 = $13252.32/year)
• Monthly: $1125.20 (x12 = $13502.36/year)

RESERVE CALCULATIONS:
• Net Level Premium: $9376.64
• First Year Reserve: $2500.44
• Terminal Reserve (Year 4): $668676.26

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 11.5%
Profit Margin: 13.1%
Lapse Assumption: 4.8% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Variable Universal Life life insurance premium for 61 year old female, $1,000,000 coverage, Substandard rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $1,000,000
• Duration: Lifetime Coverage
• Issue Age: 61
• Sex: Female
• Underwriting Class: Substandard

PREMIUM COMPUTATION:
• Base Mortality Rate (q_61): 0.005001
• Underwriting Multiplier: 1.5x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 70% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $7501.31
• Expense Charge: $1875.33
• Reserve Accumulation: $2500.44
• Profit Margin: $625.11
• Gross Annual Premium: $12502.19

PAYMENT OPTIONS:
• Annual: $12502.19
• Semi-Annual: $6501.14 (x2 = $13002.27/year)
• Quarterly: $3313.08 (x4 = $13252.32/year)
• Monthly: $1125.20 (x12 = $13502.36/year)

RESERVE CALCULATIONS:
• Net Level Premium: $9376.64
• First Year Reserve: $2500.44
• Terminal Reserve (Year 4): $668676.26

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate

Internal Rate of Return: 11.5%
Profit Margin: 13.1%
Lapse Assumption: 4.8% annual

Illustration assumes guaranteed rates. Actual results may vary.