Instruction: Calculate excess mortality during seasonal flu in Germany for Q4 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: Germany
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 93,710
• Observed Deaths: 130,830
• Excess Deaths: 37,120
• Excess Mortality Rate: 39.6%
• P-score: 39.6%
• Z-score: 2.76 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.2% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 4.7% (3,712 deaths)
• 45-64 years: 6.8% (9,280 deaths)
• 65-74 years: 23.0% (9,280 deaths)
• 75+ years: 30.4% (14,848 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 25,869 (71%)
• Indirect (probable): 9,148 (24%)
• Collateral (delayed care): 5,080 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [31,552, 42,688]
• Probability of chance: < 0.001
• Power: 0.95

Years of Life Lost: 479863
Economic Impact: $6.7 billion
Quality-Adjusted Life Years Lost: 389912

Human: Calculate excess mortality during seasonal flu in Germany for Q4 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: Germany
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 93,710
• Observed Deaths: 130,830
• Excess Deaths: 37,120
• Excess Mortality Rate: 39.6%
• P-score: 39.6%
• Z-score: 2.76 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.2% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 4.7% (3,712 deaths)
• 45-64 years: 6.8% (9,280 deaths)
• 65-74 years: 23.0% (9,280 deaths)
• 75+ years: 30.4% (14,848 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 25,869 (71%)
• Indirect (probable): 9,148 (24%)
• Collateral (delayed care): 5,080 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [31,552, 42,688]
• Probability of chance: < 0.001
• Power: 0.95

Years of Life Lost: 479863
Economic Impact: $6.7 billion
Quality-Adjusted Life Years Lost: 389912


Instruction: Calculate policy reserve for 46 year old, 20-year term life, year 10

Response:
POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 36
• Current Age: 46
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $772.38
• Present Value Future Benefits (PVFB): $57221.62
• Present Value Future Premiums (PVFP): $34599.33

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $15163.96
• Per $1,000 Face: $151.64

PROSPECTIVE METHOD:
• A₁_46:10⌉ = 0.2313
• ä_46:10⌉ = 9.7255
• ₁₀V = 100,000 × A₁ - P × ä = $15163.96

RETROSPECTIVE METHOD:
• Accumulated Premiums: $8783.31
• Accumulated Cost of Insurance: $5408.43
• Interest Earned: $1613.45
• ₁₀V = $15163.96

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $14405.76
• Tax Reserve: $13950.84
• GAAP Reserve: $15922.15

Human: Calculate policy reserve for 46 year old, 20-year term life, year 10

Actuarial AI: POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 36
• Current Age: 46
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $772.38
• Present Value Future Benefits (PVFB): $57221.62
• Present Value Future Premiums (PVFP): $34599.33

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $15163.96
• Per $1,000 Face: $151.64

PROSPECTIVE METHOD:
• A₁_46:10⌉ = 0.2313
• ä_46:10⌉ = 9.7255
• ₁₀V = 100,000 × A₁ - P × ä = $15163.96

RETROSPECTIVE METHOD:
• Accumulated Premiums: $8783.31
• Accumulated Cost of Insurance: $5408.43
• Interest Earned: $1613.45
• ₁₀V = $15163.96

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $14405.76
• Tax Reserve: $13950.84
• GAAP Reserve: $15922.15


Instruction: Analyze mortality trends in UK from 2005-2023

Response:
MORTALITY TREND ANALYSIS

Country: UK
Analysis Period: 2005-2023

OVERALL TRENDS:
• Average Annual Change: -1.8%
• Total Change: -15.3%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001

Life expectancy increased by 0.6 years.
Age-standardized death rate changed by +164 per 100,000.

KEY DRIVERS:
• Medical advances: 40% of improvement
• Public health measures: 24%
• Lifestyle changes: +19%
• Environmental factors: +8%

Human: Analyze mortality trends in UK from 2005-2023

Actuarial AI: MORTALITY TREND ANALYSIS

Country: UK
Analysis Period: 2005-2023

OVERALL TRENDS:
• Average Annual Change: -1.8%
• Total Change: -15.3%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001

Life expectancy increased by 0.6 years.
Age-standardized death rate changed by +164 per 100,000.

KEY DRIVERS:
• Medical advances: 40% of improvement
• Public health measures: 24%
• Lifestyle changes: +19%
• Environmental factors: +8%


Instruction: Perform mortality assumption review for annuity block

Response:
MORTALITY ASSUMPTION VALUATION

Product: Annuity Block
Valuation Date: 12/31/2023

CURRENT ASSUMPTIONS:
• Base Table: Pri-2012
• Improvement Scale: MP-2021
• Experience Adjustment: 107%

EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.08
• Credibility Factor: 0.94
• Indicated Change: -3.0%

FINANCIAL IMPACT:
• Reserve Change: $7.4 million
• Funded Ratio Impact: -0.6%

Recommendation: Maintain current assumptions

Human: Perform mortality assumption review for annuity block

Actuarial AI: MORTALITY ASSUMPTION VALUATION

Product: Annuity Block
Valuation Date: 12/31/2023

CURRENT ASSUMPTIONS:
• Base Table: Pri-2012
• Improvement Scale: MP-2021
• Experience Adjustment: 107%

EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.08
• Credibility Factor: 0.94
• Indicated Change: -3.0%

FINANCIAL IMPACT:
• Reserve Change: $7.4 million
• Funded Ratio Impact: -0.6%

Recommendation: Maintain current assumptions


Instruction: Show survival curve for Japan male in 2020

Response:
SURVIVAL CURVE ANALYSIS

Population: Japan Male
Reference Year: 2020
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         76.5
    1          99,997           14         0.00014         77.6
    5          99,983           29         0.00029         78.3
   10          99,954           72         0.00072         73.4
   20          99,882          172         0.00172         63.5
   30          99,710          281         0.00282         53.8
   40          99,429          380         0.00382         42.6
   50          99,049          572         0.00577         27.1
   60          98,477          975         0.00990         16.5
   70          97,502        1,598         0.01639         10.2
   80          95,904        1,757         0.01832          1.9
   90          94,147        2,209         0.02346          2.9
  100          91,938        4,309         0.04687          3.2
  110          87,629       87,629         1.00000          2.0

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 75.4 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.5%
• Probability of Surviving to 80: 95.9%

CURVE CHARACTERISTICS:
• Type: Type I (Rectangular)
• Compression: High
• Rectangularization Index: 0.90

The survival curve follows Gompertz law after age 30.
Data sourced from 158,042 death certificates.

Human: Show survival curve for Japan male in 2020

Actuarial AI: SURVIVAL CURVE ANALYSIS

Population: Japan Male
Reference Year: 2020
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         76.5
    1          99,997           14         0.00014         77.6
    5          99,983           29         0.00029         78.3
   10          99,954           72         0.00072         73.4
   20          99,882          172         0.00172         63.5
   30          99,710          281         0.00282         53.8
   40          99,429          380         0.00382         42.6
   50          99,049          572         0.00577         27.1
   60          98,477          975         0.00990         16.5
   70          97,502        1,598         0.01639         10.2
   80          95,904        1,757         0.01832          1.9
   90          94,147        2,209         0.02346          2.9
  100          91,938        4,309         0.04687          3.2
  110          87,629       87,629         1.00000          2.0

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 75.4 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.5%
• Probability of Surviving to 80: 95.9%

CURVE CHARACTERISTICS:
• Type: Type I (Rectangular)
• Compression: High
• Rectangularization Index: 0.90

The survival curve follows Gompertz law after age 30.
Data sourced from 158,042 death certificates.


Instruction: What is the probability of death within 20 years for someone age 79?

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 79 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_79): 0.000956 (0.0956%)
• 20-Year Death Probability (₍20₎q_79): 0.018939 (1.894%)
• Survival Probability (₍20₎p_79): 0.981061 (98.106%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_79): 0.000956
• Hazard Rate (h_79): 0.000956
• Cumulative Hazard (H_79): 0.019121
• Median Future Lifetime: 725.0 years

RISK CLASSIFICATION:
• Mortality Ratio: 1.0x standard
• Risk Category: Preferred Plus
• Insurability: Standard or better
• Recommended Premium Loading: 0%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.016098
• Upper Bound: 0.021780

Analysis based on 96,376 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: What is the probability of death within 20 years for someone age 79?

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 79 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_79): 0.000956 (0.0956%)
• 20-Year Death Probability (₍20₎q_79): 0.018939 (1.894%)
• Survival Probability (₍20₎p_79): 0.981061 (98.106%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_79): 0.000956
• Hazard Rate (h_79): 0.000956
• Cumulative Hazard (H_79): 0.019121
• Median Future Lifetime: 725.0 years

RISK CLASSIFICATION:
• Mortality Ratio: 1.0x standard
• Risk Category: Preferred Plus
• Insurability: Standard or better
• Recommended Premium Loading: 0%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.016098
• Upper Bound: 0.021780

Analysis based on 96,376 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Analyze mortality trends in UK from 2005-2023

Response:
MORTALITY TREND ANALYSIS

Country: UK
Analysis Period: 2005-2023

OVERALL TRENDS:
• Average Annual Change: -1.0%
• Total Change: -15.4%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001

Life expectancy increased by 2.4 years.
Age-standardized death rate changed by +89 per 100,000.

KEY DRIVERS:
• Medical advances: 23% of improvement
• Public health measures: 17%
• Lifestyle changes: +22%
• Environmental factors: +12%

Human: Analyze mortality trends in UK from 2005-2023

Actuarial AI: MORTALITY TREND ANALYSIS

Country: UK
Analysis Period: 2005-2023

OVERALL TRENDS:
• Average Annual Change: -1.0%
• Total Change: -15.4%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001

Life expectancy increased by 2.4 years.
Age-standardized death rate changed by +89 per 100,000.

KEY DRIVERS:
• Medical advances: 23% of improvement
• Public health measures: 17%
• Lifestyle changes: +22%
• Environmental factors: +12%


Instruction: Project mortality rates for USA in 2049

Response:
MORTALITY PROJECTION

Country: USA
Target Year: 2049
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 594.4 per 100,000
• Life Expectancy: 88.8 years
• Annual Improvement: 0.70%

CONFIDENCE INTERVALS (95%):
• Lower: 505.3
• Upper: 683.6

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

Human: Project mortality rates for USA in 2049

Actuarial AI: MORTALITY PROJECTION

Country: USA
Target Year: 2049
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 594.4 per 100,000
• Life Expectancy: 88.8 years
• Annual Improvement: 0.70%

CONFIDENCE INTERVALS (95%):
• Lower: 505.3
• Upper: 683.6

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


Instruction: Analyze mortality patterns for 1946 birth cohort

Response:
BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1946
Current Age: 78 years
Cohort Size at Birth: 2,950,560

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 67.3 years
• Current Life Expectancy: 78.4 years
• Survival to Current Age: 90.6%

HISTORICAL EXPOSURES:
• Standard exposures

MORTALITY PATTERN:
• Peak Infant Mortality: 29.5 per 1,000
• Current Mortality Rate: 9.1 per 1,000
• Improvement Since Birth: 64%

Cohort effects explain 23% of mortality variation.

Human: Analyze mortality patterns for 1946 birth cohort

Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1946
Current Age: 78 years
Cohort Size at Birth: 2,950,560

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 67.3 years
• Current Life Expectancy: 78.4 years
• Survival to Current Age: 90.6%

HISTORICAL EXPOSURES:
• Standard exposures

MORTALITY PATTERN:
• Peak Infant Mortality: 29.5 per 1,000
• Current Mortality Rate: 9.1 per 1,000
• Improvement Since Birth: 64%

Cohort effects explain 23% of mortality variation.


Instruction: Summarize individual life mortality experience study results

Response:
MORTALITY EXPERIENCE STUDY

Study Type: Individual Life Insurance
Study Period: 2020-2022
Exposure: 797903 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 1.07
• Deaths Actual: 6,863
• Deaths Expected: 5,210

BY DURATION:
• Select Period (Years 1-5): 0.91
• Ultimate (Years 6+): 1.03

Statistical confidence: 95% CI [0.93, 1.14]

Human: Summarize individual life mortality experience study results

Actuarial AI: MORTALITY EXPERIENCE STUDY

Study Type: Individual Life Insurance
Study Period: 2020-2022
Exposure: 797903 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 1.07
• Deaths Actual: 6,863
• Deaths Expected: 5,210

BY DURATION:
• Select Period (Years 1-5): 0.91
• Ultimate (Years 6+): 1.03

Statistical confidence: 95% CI [0.93, 1.14]


Instruction: What is the life expectancy for a 84 year old female in Germany as of 2022?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Germany
• Age: 84 years
• Sex: Female
• Reference Year: 2022

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 84 (e_84): 4.3 years
• Expected Age at Death: 88.3 years
• Median Survival Time: 3.0 years
• Modal Age at Death: 83.3 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_84): 38.8%
• 10-Year Survival (₁₀p_84): 15.0%
• 20-Year Survival (₂₀p_84): 2.3%

MORTALITY METRICS:
• Force of Mortality (μ_84): 0.18944
• Probability of Death within 1 Year (q_84): 0.17257
• Hazard Rate: 0.21002

COMPARATIVE CONTEXT:
• Global Average at Age 84: -2.8 years
• Regional Rank: Top 44 globally
• Historical Trend: Improving

Based on 103,347 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.5%.

Human: What is the life expectancy for a 84 year old female in Germany as of 2022?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Germany
• Age: 84 years
• Sex: Female
• Reference Year: 2022

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 84 (e_84): 4.3 years
• Expected Age at Death: 88.3 years
• Median Survival Time: 3.0 years
• Modal Age at Death: 83.3 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_84): 38.8%
• 10-Year Survival (₁₀p_84): 15.0%
• 20-Year Survival (₂₀p_84): 2.3%

MORTALITY METRICS:
• Force of Mortality (μ_84): 0.18944
• Probability of Death within 1 Year (q_84): 0.17257
• Hazard Rate: 0.21002

COMPARATIVE CONTEXT:
• Global Average at Age 84: -2.8 years
• Regional Rank: Top 44 globally
• Historical Trend: Improving

Based on 103,347 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.5%.


Instruction: What is the mortality rate for Hypertension in UK for 45-64 in 2021?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Hypertension
Location: UK
Year: 2021
Age Group: 45-64

MORTALITY STATISTICS:
• Crude Death Rate: 8.6 per 100,000 population
• Age-Adjusted Rate: 7.9 per 100,000
• Total Deaths: 397,312
• Percentage of All Deaths: 21.4%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 10.3 per 100,000
• Female Death Rate: 7.3 per 100,000
• Sex Ratio (M:F): 1.50:1

TREND ANALYSIS:
• 5-Year Change: +10.1%
• 10-Year Change: -16.4%
• Annual Percentage Change: -1.5%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 6936824
• Economic Burden: $85.5 billion annually
• Preventable Deaths: 22%

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

International Classification of Diseases (ICD-10): I10-I15
Data Quality: Complete (99% coverage)

Human: What is the mortality rate for Hypertension in UK for 45-64 in 2021?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Hypertension
Location: UK
Year: 2021
Age Group: 45-64

MORTALITY STATISTICS:
• Crude Death Rate: 8.6 per 100,000 population
• Age-Adjusted Rate: 7.9 per 100,000
• Total Deaths: 397,312
• Percentage of All Deaths: 21.4%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 10.3 per 100,000
• Female Death Rate: 7.3 per 100,000
• Sex Ratio (M:F): 1.50:1

TREND ANALYSIS:
• 5-Year Change: +10.1%
• 10-Year Change: -16.4%
• Annual Percentage Change: -1.5%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 6936824
• Economic Burden: $85.5 billion annually
• Preventable Deaths: 22%

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

International Classification of Diseases (ICD-10): I10-I15
Data Quality: Complete (99% coverage)


Instruction: Calculate excess mortality during opioid crisis in India for 2022

Response:
EXCESS MORTALITY ANALYSIS

Event: opioid crisis
Location: India
Period: 2022

MORTALITY METRICS:
• Expected Deaths (Baseline): 61,468
• Observed Deaths: 73,885
• Excess Deaths: 12,417
• Excess Mortality Rate: 20.2%
• P-score: 20.2%
• Z-score: 2.85 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.1% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 7.2% (1,241 deaths)
• 45-64 years: 16.8% (3,104 deaths)
• 65-74 years: 16.5% (3,104 deaths)
• 75+ years: 20.4% (4,966 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 9,568 (62%)
• Indirect (probable): 1,528 (16%)
• Collateral (delayed care): 2,107 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [10,554, 14,279]
• Probability of chance: < 0.001
• Power: 0.99

Years of Life Lost: 158622
Economic Impact: $7.3 billion
Quality-Adjusted Life Years Lost: 132060

Human: Calculate excess mortality during opioid crisis in India for 2022

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: opioid crisis
Location: India
Period: 2022

MORTALITY METRICS:
• Expected Deaths (Baseline): 61,468
• Observed Deaths: 73,885
• Excess Deaths: 12,417
• Excess Mortality Rate: 20.2%
• P-score: 20.2%
• Z-score: 2.85 (p < 0.001)

BASELINE CALCULATION:
• Method: 5-year average
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.1% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 7.2% (1,241 deaths)
• 45-64 years: 16.8% (3,104 deaths)
• 65-74 years: 16.5% (3,104 deaths)
• 75+ years: 20.4% (4,966 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 9,568 (62%)
• Indirect (probable): 1,528 (16%)
• Collateral (delayed care): 2,107 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [10,554, 14,279]
• Probability of chance: < 0.001
• Power: 0.99

Years of Life Lost: 158622
Economic Impact: $7.3 billion
Quality-Adjusted Life Years Lost: 132060


Instruction: What is the life expectancy for a 0 year old male in UK as of 2020?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: UK
• Age: 0 years
• Sex: Male
• Reference Year: 2020

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 0 (e_0): 79.9 years
• Expected Age at Death: 79.9 years
• Median Survival Time: 55.3 years
• Modal Age at Death: 74.9 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_0): 94.0%
• 10-Year Survival (₁₀p_0): 88.4%
• 20-Year Survival (₂₀p_0): 78.1%

MORTALITY METRICS:
• Force of Mortality (μ_0): 0.01237
• Probability of Death within 1 Year (q_0): 0.01229
• Hazard Rate: 0.01244

COMPARATIVE CONTEXT:
• Global Average at Age 0: 81.3 years
• Regional Rank: Top 36 globally
• Historical Trend: Improving

Based on 367,476 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.0%.

Human: What is the life expectancy for a 0 year old male in UK as of 2020?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: UK
• Age: 0 years
• Sex: Male
• Reference Year: 2020

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 0 (e_0): 79.9 years
• Expected Age at Death: 79.9 years
• Median Survival Time: 55.3 years
• Modal Age at Death: 74.9 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_0): 94.0%
• 10-Year Survival (₁₀p_0): 88.4%
• 20-Year Survival (₂₀p_0): 78.1%

MORTALITY METRICS:
• Force of Mortality (μ_0): 0.01237
• Probability of Death within 1 Year (q_0): 0.01229
• Hazard Rate: 0.01244

COMPARATIVE CONTEXT:
• Global Average at Age 0: 81.3 years
• Regional Rank: Top 36 globally
• Historical Trend: Improving

Based on 367,476 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.0%.


Instruction: Calculate the 30-year death probability for a 100 year old

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 100 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_100): 0.001741 (0.1741%)
• 30-Year Death Probability (₍30₎q_100): 0.050938 (5.094%)
• Survival Probability (₍30₎p_100): 0.949062 (94.906%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_100): 0.001743
• Hazard Rate (h_100): 0.001743
• Cumulative Hazard (H_100): 0.052281
• Median Future Lifetime: 397.7 years

RISK CLASSIFICATION:
• Mortality Ratio: 1.7x standard
• Risk Category: Preferred
• Insurability: Standard or better
• Recommended Premium Loading: 74%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.043297
• Upper Bound: 0.058578

Analysis based on 62,932 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Calculate the 30-year death probability for a 100 year old

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 100 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_100): 0.001741 (0.1741%)
• 30-Year Death Probability (₍30₎q_100): 0.050938 (5.094%)
• Survival Probability (₍30₎p_100): 0.949062 (94.906%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_100): 0.001743
• Hazard Rate (h_100): 0.001743
• Cumulative Hazard (H_100): 0.052281
• Median Future Lifetime: 397.7 years

RISK CLASSIFICATION:
• Mortality Ratio: 1.7x standard
• Risk Category: Preferred
• Insurability: Standard or better
• Recommended Premium Loading: 74%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.043297
• Upper Bound: 0.058578

Analysis based on 62,932 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Analyze mortality differences by race in the USA

Response:
DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Race
Country: USA
Analysis Period: 2022

MORTALITY RATES BY RACE (per 100,000):
• White: 828.8
• Black: 356.0
• Asian: 1132.3
• Hispanic: 983.0
• Native American: 402.3

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.94
• Rate Difference: 286.2 per 100,000
• Population Attributable Risk: 16.1%
• Gini Coefficient: 0.160

LIFE EXPECTANCY BY RACE:
• White: 71.3 years
• Black: 72.1 years
• Asian: 77.5 years
• Hispanic: 71.4 years
• Native American: 73.7 years

CONTRIBUTING FACTORS:
• Healthcare Access: 31% of disparity
• Socioeconomic Status: 19% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 6% of disparity

TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -1.4%

Social determinants explain 74% of observed mortality differences.

Human: Analyze mortality differences by race in the USA

Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Race
Country: USA
Analysis Period: 2022

MORTALITY RATES BY RACE (per 100,000):
• White: 828.8
• Black: 356.0
• Asian: 1132.3
• Hispanic: 983.0
• Native American: 402.3

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.94
• Rate Difference: 286.2 per 100,000
• Population Attributable Risk: 16.1%
• Gini Coefficient: 0.160

LIFE EXPECTANCY BY RACE:
• White: 71.3 years
• Black: 72.1 years
• Asian: 77.5 years
• Hispanic: 71.4 years
• Native American: 73.7 years

CONTRIBUTING FACTORS:
• Healthcare Access: 31% of disparity
• Socioeconomic Status: 19% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 6% of disparity

TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -1.4%

Social determinants explain 74% of observed mortality differences.


Instruction: Perform mortality assumption review for pension plan

Response:
MORTALITY ASSUMPTION VALUATION

Product: Pension Plan
Valuation Date: 12/31/2023

CURRENT ASSUMPTIONS:
• Base Table: Pri-2012
• Improvement Scale: MP-2019
• Experience Adjustment: 92%

EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 0.99
• Credibility Factor: 0.75
• Indicated Change: -6.4%

FINANCIAL IMPACT:
• Reserve Change: $7.8 million
• Funded Ratio Impact: -1.7%

Recommendation: Update assumptions

Human: Perform mortality assumption review for pension plan

Actuarial AI: MORTALITY ASSUMPTION VALUATION

Product: Pension Plan
Valuation Date: 12/31/2023

CURRENT ASSUMPTIONS:
• Base Table: Pri-2012
• Improvement Scale: MP-2019
• Experience Adjustment: 92%

EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 0.99
• Credibility Factor: 0.75
• Indicated Change: -6.4%

FINANCIAL IMPACT:
• Reserve Change: $7.8 million
• Funded Ratio Impact: -1.7%

Recommendation: Update assumptions


Instruction: Project mortality rates for Japan in 2036

Response:
MORTALITY PROJECTION

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

PROJECTED METRICS:
• Crude Death Rate: 708.2 per 100,000
• Life Expectancy: 83.0 years
• Annual Improvement: 1.07%

CONFIDENCE INTERVALS (95%):
• Lower: 602.0
• Upper: 814.5

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

Human: Project mortality rates for Japan in 2036

Actuarial AI: MORTALITY PROJECTION

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

PROJECTED METRICS:
• Crude Death Rate: 708.2 per 100,000
• Life Expectancy: 83.0 years
• Annual Improvement: 1.07%

CONFIDENCE INTERVALS (95%):
• Lower: 602.0
• Upper: 814.5

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


Instruction: Show survival curve for Brazil female in 2022

Response:
SURVIVAL CURVE ANALYSIS

Population: Brazil Female
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         75.0
    1          99,998            9         0.00009         82.8
    5          99,989           26         0.00026         70.4
   10          99,963           58         0.00058         74.4
   20          99,905          103         0.00103         61.9
   30          99,802          159         0.00159         50.5
   40          99,643          317         0.00318         41.9
   50          99,326          486         0.00489         29.9
   60          98,840          650         0.00658         15.9
   70          98,190        1,024         0.01043         14.2
   80          97,166        1,532         0.01577          0.0
   90          95,634        1,608         0.01681          4.9
  100          94,026        3,147         0.03347          1.4
  110          90,879       90,879         1.00000          3.8

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 82.2 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.8%
• Probability of Surviving to 80: 97.2%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.73

The survival curve follows Gompertz law after age 30.
Data sourced from 495,788 death certificates.

Human: Show survival curve for Brazil female in 2022

Actuarial AI: SURVIVAL CURVE ANALYSIS

Population: Brazil Female
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         75.0
    1          99,998            9         0.00009         82.8
    5          99,989           26         0.00026         70.4
   10          99,963           58         0.00058         74.4
   20          99,905          103         0.00103         61.9
   30          99,802          159         0.00159         50.5
   40          99,643          317         0.00318         41.9
   50          99,326          486         0.00489         29.9
   60          98,840          650         0.00658         15.9
   70          98,190        1,024         0.01043         14.2
   80          97,166        1,532         0.01577          0.0
   90          95,634        1,608         0.01681          4.9
  100          94,026        3,147         0.03347          1.4
  110          90,879       90,879         1.00000          3.8

SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 82.2 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.8%
• Probability of Surviving to 80: 97.2%

CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.73

The survival curve follows Gompertz law after age 30.
Data sourced from 495,788 death certificates.


Instruction: Project mortality rates for China in 2049

Response:
MORTALITY PROJECTION

Country: China
Target Year: 2049
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 507.0 per 100,000
• Life Expectancy: 84.7 years
• Annual Improvement: 1.52%

CONFIDENCE INTERVALS (95%):
• Lower: 431.0
• Upper: 583.1

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

Human: Project mortality rates for China in 2049

Actuarial AI: MORTALITY PROJECTION

Country: China
Target Year: 2049
Projection Method: Lee-Carter Model with Coherent Forecasting

PROJECTED METRICS:
• Crude Death Rate: 507.0 per 100,000
• Life Expectancy: 84.7 years
• Annual Improvement: 1.52%

CONFIDENCE INTERVALS (95%):
• Lower: 431.0
• Upper: 583.1

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


Instruction: Perform mortality assumption review for life insurance portfolio

Response:
MORTALITY ASSUMPTION VALUATION

Product: Life Insurance Portfolio
Valuation Date: 12/31/2023

CURRENT ASSUMPTIONS:
• Base Table: RP-2014
• Improvement Scale: MP-2021
• Experience Adjustment: 90%

EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 0.98
• Credibility Factor: 0.71
• Indicated Change: +5.6%

FINANCIAL IMPACT:
• Reserve Change: $7.2 million
• Funded Ratio Impact: +0.8%

Recommendation: Maintain current assumptions

Human: Perform mortality assumption review for life insurance portfolio

Actuarial AI: MORTALITY ASSUMPTION VALUATION

Product: Life Insurance Portfolio
Valuation Date: 12/31/2023

CURRENT ASSUMPTIONS:
• Base Table: RP-2014
• Improvement Scale: MP-2021
• Experience Adjustment: 90%

EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 0.98
• Credibility Factor: 0.71
• Indicated Change: +5.6%

FINANCIAL IMPACT:
• Reserve Change: $7.2 million
• Funded Ratio Impact: +0.8%

Recommendation: Maintain current assumptions


Instruction: 22. An actuary studied the likelihood that different types of drivers would be involved in at

Response:
To solve this problem, let me work through it step by step:
least one collision during any one-year period. The results of the study are: Type of driver Percentage of all drivers Probability of at least one collision Teen Young adult Midlife Senior 8% 16% 45% 31%

Human: 22. An actuary studied the likelihood that different types of drivers would be involved in at

Actuarial AI: To solve this problem, let me work through it step by step:
least one collision during any one-year period. The results of the study are: Type of driver Percentage of all drivers Probability of at least one collision Teen Young adult Midlife Senior 8% 16% 45% 31%


Instruction: Compare urban vs other area mortality rates in UK

Response:
GEOGRAPHIC MORTALITY ANALYSIS

Country: UK
Focus: Urban Areas

MORTALITY RATES (per 100,000):
• Urban: 805.6
• Rural: 992.7
• Suburban: 793.1

Rural areas show 23.2% higher mortality.
Primary factors: healthcare access, emergency response times, demographics.

Human: Compare urban vs other area mortality rates in UK

Actuarial AI: GEOGRAPHIC MORTALITY ANALYSIS

Country: UK
Focus: Urban Areas

MORTALITY RATES (per 100,000):
• Urban: 805.6
• Rural: 992.7
• Suburban: 793.1

Rural areas show 23.2% higher mortality.
Primary factors: healthcare access, emergency response times, demographics.


Instruction: What is the occupational mortality rate for Healthcare workers?

Response:
OCCUPATIONAL MORTALITY ANALYSIS

Industry: Healthcare
Fatal Injury Rate: 132.7 per 100,000 full-time workers
Annual Deaths: 11,294

LEADING CAUSES:
• Falls: 25%
• Struck by object: 15%
• Electrocution: 5%
• Caught-in/between: 17%

Workers' compensation death benefit: $460,748

Human: What is the occupational mortality rate for Healthcare workers?

Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS

Industry: Healthcare
Fatal Injury Rate: 132.7 per 100,000 full-time workers
Annual Deaths: 11,294

LEADING CAUSES:
• Falls: 25%
• Struck by object: 15%
• Electrocution: 5%
• Caught-in/between: 17%

Workers' compensation death benefit: $460,748


Instruction: Mortality risk assessment for 13 year old over next 5 years

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 13 years
• Assessment Period: 5 years
• Smoking Status: Non-smoker
• Health Conditions: obesity

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_13): 0.000210 (0.0210%)
• 5-Year Death Probability (₍5₎q_13): 0.001050 (0.105%)
• Survival Probability (₍5₎p_13): 0.998950 (99.895%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_13): 0.000210
• Hazard Rate (h_13): 0.000210
• Cumulative Hazard (H_13): 0.001050
• Median Future Lifetime: 3299.5 years

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

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.000892
• Upper Bound: 0.001207

Analysis based on 52,386 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Mortality risk assessment for 13 year old over next 5 years

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 13 years
• Assessment Period: 5 years
• Smoking Status: Non-smoker
• Health Conditions: obesity

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_13): 0.000210 (0.0210%)
• 5-Year Death Probability (₍5₎q_13): 0.001050 (0.105%)
• Survival Probability (₍5₎p_13): 0.998950 (99.895%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_13): 0.000210
• Hazard Rate (h_13): 0.000210
• Cumulative Hazard (H_13): 0.001050
• Median Future Lifetime: 3299.5 years

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

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.000892
• Upper Bound: 0.001207

Analysis based on 52,386 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Analyze mortality differences by income in the USA

Response:
DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Income
Country: USA
Analysis Period: 2020

MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 457.3
• $25-50k: 532.1
• $50-75k: 1169.7
• $75-100k: 565.0
• >$100k: 1007.5

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.95
• Rate Difference: 781.5 per 100,000
• Population Attributable Risk: 22.0%
• Gini Coefficient: 0.290

LIFE EXPECTANCY BY INCOME:
• <$25k: 73.9 years
• $25-50k: 73.0 years
• $50-75k: 77.1 years
• $75-100k: 71.1 years
• >$100k: 82.1 years

CONTRIBUTING FACTORS:
• Healthcare Access: 25% of disparity
• Socioeconomic Status: 20% of disparity
• Environmental Factors: 20% of disparity
• Behavioral Factors: 16% of disparity
• Biological Factors: 8% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +0.9%

Social determinants explain 63% of observed mortality differences.

Human: Analyze mortality differences by income in the USA

Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Income
Country: USA
Analysis Period: 2020

MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 457.3
• $25-50k: 532.1
• $50-75k: 1169.7
• $75-100k: 565.0
• >$100k: 1007.5

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.95
• Rate Difference: 781.5 per 100,000
• Population Attributable Risk: 22.0%
• Gini Coefficient: 0.290

LIFE EXPECTANCY BY INCOME:
• <$25k: 73.9 years
• $25-50k: 73.0 years
• $50-75k: 77.1 years
• $75-100k: 71.1 years
• >$100k: 82.1 years

CONTRIBUTING FACTORS:
• Healthcare Access: 25% of disparity
• Socioeconomic Status: 20% of disparity
• Environmental Factors: 20% of disparity
• Behavioral Factors: 16% of disparity
• Biological Factors: 8% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +0.9%

Social determinants explain 63% of observed mortality differences.


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

PREMIUM COMPUTATION:
• Base Mortality Rate (q_24): 0.001457
• Underwriting Multiplier: 1.5x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 72% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $764.85
• Expense Charge: $191.21
• Reserve Accumulation: $254.95
• Profit Margin: $63.74
• Gross Annual Premium: $1274.75

PAYMENT OPTIONS:
• Annual: $1274.75
• Semi-Annual: $662.87 (x2 = $1325.74/year)
• Quarterly: $337.81 (x4 = $1351.23/year)
• Monthly: $114.73 (x12 = $1376.73/year)

RESERVE CALCULATIONS:
• Net Level Premium: $956.06
• First Year Reserve: $254.95
• Terminal Reserve (Year 41): $110753.56

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

Internal Rate of Return: 10.1%
Profit Margin: 10.2%
Lapse Assumption: 4.6% annual

Illustration assumes guaranteed rates. Actual results may vary.

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

PREMIUM COMPUTATION:
• Base Mortality Rate (q_24): 0.001457
• Underwriting Multiplier: 1.5x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 72% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $764.85
• Expense Charge: $191.21
• Reserve Accumulation: $254.95
• Profit Margin: $63.74
• Gross Annual Premium: $1274.75

PAYMENT OPTIONS:
• Annual: $1274.75
• Semi-Annual: $662.87 (x2 = $1325.74/year)
• Quarterly: $337.81 (x4 = $1351.23/year)
• Monthly: $114.73 (x12 = $1376.73/year)

RESERVE CALCULATIONS:
• Net Level Premium: $956.06
• First Year Reserve: $254.95
• Terminal Reserve (Year 41): $110753.56

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

Internal Rate of Return: 10.1%
Profit Margin: 10.2%
Lapse Assumption: 4.6% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Compare infant mortality between China, USA, India, Australia and South Korea

Response:
INTERNATIONAL MORTALITY COMPARISON

Metric: Infant Mortality
Countries: China, USA, India, Australia, South Korea
Reference Year: 2022

COMPARATIVE STATISTICS:
• China: 15.3 per 1,000 live births
• USA: 17.4 per 1,000 live births
• India: 4.5 per 1,000 live births
• Australia: 15.1 per 1,000 live births
• South Korea: 25.5 per 1,000 live births

RANKINGS:
1. India: 4.5
2. Australia: 15.1
3. China: 15.3
4. USA: 17.4
5. South Korea: 25.5

STATISTICAL ANALYSIS:
• Range: 21.0
• Mean: 15.6
• Median: 15.3
• Standard Deviation: 6.7
• Coefficient of Variation: 43.0%

RELATIVE COMPARISONS:
• Best vs Worst: 5.64x difference
• Above Average: 2/5
• Global Ranking: China: #180, USA: #149, India: #58

CONTRIBUTING FACTORS:
• Healthcare System: 34% of variation
• Economic Development: 33% of variation
• Public Health Policy: 12% of variation
• Demographics: 10% of variation
• Environmental Factors: 10% of variation

Convergence/Divergence: Diverging at 1.5% annually

Human: Compare infant mortality between China, USA, India, Australia and South Korea

Actuarial AI: INTERNATIONAL MORTALITY COMPARISON

Metric: Infant Mortality
Countries: China, USA, India, Australia, South Korea
Reference Year: 2022

COMPARATIVE STATISTICS:
• China: 15.3 per 1,000 live births
• USA: 17.4 per 1,000 live births
• India: 4.5 per 1,000 live births
• Australia: 15.1 per 1,000 live births
• South Korea: 25.5 per 1,000 live births

RANKINGS:
1. India: 4.5
2. Australia: 15.1
3. China: 15.3
4. USA: 17.4
5. South Korea: 25.5

STATISTICAL ANALYSIS:
• Range: 21.0
• Mean: 15.6
• Median: 15.3
• Standard Deviation: 6.7
• Coefficient of Variation: 43.0%

RELATIVE COMPARISONS:
• Best vs Worst: 5.64x difference
• Above Average: 2/5
• Global Ranking: China: #180, USA: #149, India: #58

CONTRIBUTING FACTORS:
• Healthcare System: 34% of variation
• Economic Development: 33% of variation
• Public Health Policy: 12% of variation
• Demographics: 10% of variation
• Environmental Factors: 10% of variation

Convergence/Divergence: Diverging at 1.5% annually


Instruction: Calculate policy reserve for 62 year old, 20-year term life, year 10

Response:
POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 52
• Current Age: 62
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $1084.62
• Present Value Future Benefits (PVFB): $40726.48
• Present Value Future Premiums (PVFP): $21958.94

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $27895.15
• Per $1,000 Face: $278.95

PROSPECTIVE METHOD:
• A₁_62:10⌉ = 0.1968
• ä_62:10⌉ = 8.3854
• ₁₀V = 100,000 × A₁ - P × ä = $27895.15

RETROSPECTIVE METHOD:
• Accumulated Premiums: $9508.38
• Accumulated Cost of Insurance: $5009.61
• Interest Earned: $1009.41
• ₁₀V = $27895.15

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $26500.39
• Tax Reserve: $25663.54
• GAAP Reserve: $29289.91

Human: Calculate policy reserve for 62 year old, 20-year term life, year 10

Actuarial AI: POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 52
• Current Age: 62
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $1084.62
• Present Value Future Benefits (PVFB): $40726.48
• Present Value Future Premiums (PVFP): $21958.94

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $27895.15
• Per $1,000 Face: $278.95

PROSPECTIVE METHOD:
• A₁_62:10⌉ = 0.1968
• ä_62:10⌉ = 8.3854
• ₁₀V = 100,000 × A₁ - P × ä = $27895.15

RETROSPECTIVE METHOD:
• Accumulated Premiums: $9508.38
• Accumulated Cost of Insurance: $5009.61
• Interest Earned: $1009.41
• ₁₀V = $27895.15

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $26500.39
• Tax Reserve: $25663.54
• GAAP Reserve: $29289.91


Instruction: What is the occupational mortality rate for Transportation workers?

Response:
OCCUPATIONAL MORTALITY ANALYSIS

Industry: Transportation
Fatal Injury Rate: 75.0 per 100,000 full-time workers
Annual Deaths: 6,691

LEADING CAUSES:
• Falls: 28%
• Struck by object: 18%
• Electrocution: 11%
• Caught-in/between: 19%

Workers' compensation death benefit: $417,230

Human: What is the occupational mortality rate for Transportation workers?

Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS

Industry: Transportation
Fatal Injury Rate: 75.0 per 100,000 full-time workers
Annual Deaths: 6,691

LEADING CAUSES:
• Falls: 28%
• Struck by object: 18%
• Electrocution: 11%
• Caught-in/between: 19%

Workers' compensation death benefit: $417,230


Instruction: What is the probability of death within 30 years for someone age 90?

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 90 years
• Assessment Period: 30 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_90): 0.003271 (0.3271%)
• 30-Year Death Probability (₍30₎q_90): 0.093618 (9.362%)
• Survival Probability (₍30₎p_90): 0.906382 (90.638%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_90): 0.003276
• Hazard Rate (h_90): 0.003276
• Cumulative Hazard (H_90): 0.098295
• Median Future Lifetime: 211.6 years

RISK CLASSIFICATION:
• Mortality Ratio: 3.3x standard
• Risk Category: Standard Plus
• Insurability: Standard or better
• Recommended Premium Loading: 227%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.079575
• Upper Bound: 0.107661

Analysis based on 71,809 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: What is the probability of death within 30 years for someone age 90?

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 90 years
• Assessment Period: 30 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: None reported

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_90): 0.003271 (0.3271%)
• 30-Year Death Probability (₍30₎q_90): 0.093618 (9.362%)
• Survival Probability (₍30₎p_90): 0.906382 (90.638%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_90): 0.003276
• Hazard Rate (h_90): 0.003276
• Cumulative Hazard (H_90): 0.098295
• Median Future Lifetime: 211.6 years

RISK CLASSIFICATION:
• Mortality Ratio: 3.3x standard
• Risk Category: Standard Plus
• Insurability: Standard or better
• Recommended Premium Loading: 227%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.079575
• Upper Bound: 0.107661

Analysis based on 71,809 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Calculate excess mortality during seasonal flu in France for Q4 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: France
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 60,005
• Observed Deaths: 70,032
• Excess Deaths: 10,027
• Excess Mortality Rate: 16.7%
• P-score: 16.7%
• Z-score: 5.13 (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: -1.3% (1,002 deaths)
• 45-64 years: 9.8% (2,506 deaths)
• 65-74 years: 12.9% (2,506 deaths)
• 75+ years: 20.9% (4,010 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 5,594 (62%)
• Indirect (probable): 1,108 (11%)
• Collateral (delayed care): 1,172 (14%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [8,522, 11,531]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 107418
Economic Impact: $5.9 billion
Quality-Adjusted Life Years Lost: 95235

Human: Calculate excess mortality during seasonal flu in France for Q4 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: seasonal flu
Location: France
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 60,005
• Observed Deaths: 70,032
• Excess Deaths: 10,027
• Excess Mortality Rate: 16.7%
• P-score: 16.7%
• Z-score: 5.13 (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: -1.3% (1,002 deaths)
• 45-64 years: 9.8% (2,506 deaths)
• 65-74 years: 12.9% (2,506 deaths)
• 75+ years: 20.9% (4,010 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 5,594 (62%)
• Indirect (probable): 1,108 (11%)
• Collateral (delayed care): 1,172 (14%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [8,522, 11,531]
• Probability of chance: < 0.001
• Power: 0.97

Years of Life Lost: 107418
Economic Impact: $5.9 billion
Quality-Adjusted Life Years Lost: 95235


Instruction: What is the probability of death within 5 years for someone age 55?

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 55 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: obesity, heart disease, cancer history

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_55): 0.004353 (0.4353%)
• 5-Year Death Probability (₍5₎q_55): 0.021574 (2.157%)
• Survival Probability (₍5₎p_55): 0.978426 (97.843%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_55): 0.004362
• Hazard Rate (h_55): 0.004362
• Cumulative Hazard (H_55): 0.021810
• Median Future Lifetime: 158.9 years

RISK CLASSIFICATION:
• Mortality Ratio: 4.4x standard
• Risk Category: Standard
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 335%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.018338
• Upper Bound: 0.024810

Analysis based on 151,993 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: What is the probability of death within 5 years for someone age 55?

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 55 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: obesity, heart disease, cancer history

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_55): 0.004353 (0.4353%)
• 5-Year Death Probability (₍5₎q_55): 0.021574 (2.157%)
• Survival Probability (₍5₎p_55): 0.978426 (97.843%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_55): 0.004362
• Hazard Rate (h_55): 0.004362
• Cumulative Hazard (H_55): 0.021810
• Median Future Lifetime: 158.9 years

RISK CLASSIFICATION:
• Mortality Ratio: 4.4x standard
• Risk Category: Standard
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 335%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.018338
• Upper Bound: 0.024810

Analysis based on 151,993 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: What is the mortality rate for Parkinson's in Germany for Under 25 in 2023?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Parkinson's
Location: Germany
Year: 2023
Age Group: Under 25

MORTALITY STATISTICS:
• Crude Death Rate: 8.9 per 100,000 population
• Age-Adjusted Rate: 7.8 per 100,000
• Total Deaths: 63,257
• Percentage of All Deaths: 9.7%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 10.6 per 100,000
• Female Death Rate: 7.5 per 100,000
• Sex Ratio (M:F): 1.39:1

TREND ANALYSIS:
• 5-Year Change: -5.2%
• 10-Year Change: -22.7%
• Annual Percentage Change: -1.0%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #8
• Years of Potential Life Lost (YPLL): 638758
• Economic Burden: $23.4 billion annually
• Preventable Deaths: 46%

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

International Classification of Diseases (ICD-10): G20
Data Quality: Partial (86% coverage)

Human: What is the mortality rate for Parkinson's in Germany for Under 25 in 2023?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Parkinson's
Location: Germany
Year: 2023
Age Group: Under 25

MORTALITY STATISTICS:
• Crude Death Rate: 8.9 per 100,000 population
• Age-Adjusted Rate: 7.8 per 100,000
• Total Deaths: 63,257
• Percentage of All Deaths: 9.7%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 10.6 per 100,000
• Female Death Rate: 7.5 per 100,000
• Sex Ratio (M:F): 1.39:1

TREND ANALYSIS:
• 5-Year Change: -5.2%
• 10-Year Change: -22.7%
• Annual Percentage Change: -1.0%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #8
• Years of Potential Life Lost (YPLL): 638758
• Economic Burden: $23.4 billion annually
• Preventable Deaths: 46%

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

International Classification of Diseases (ICD-10): G20
Data Quality: Partial (86% coverage)


Instruction: What is the life expectancy for a 85 year old female in Japan as of 2017?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Japan
• Age: 85 years
• Sex: Female
• Reference Year: 2017

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 85 (e_85): 3.1 years
• Expected Age at Death: 88.1 years
• Median Survival Time: 2.2 years
• Modal Age at Death: 83.1 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_85): 29.8%
• 10-Year Survival (₁₀p_85): 8.9%
• 20-Year Survival (₂₀p_85): 0.8%

MORTALITY METRICS:
• Force of Mortality (μ_85): 0.24227
• Probability of Death within 1 Year (q_85): 0.21515
• Hazard Rate: 0.27743

COMPARATIVE CONTEXT:
• Global Average at Age 85: -0.4 years
• Regional Rank: Top 27 globally
• Historical Trend: Stable

Based on 330,682 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.5%.

Human: What is the life expectancy for a 85 year old female in Japan as of 2017?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: Japan
• Age: 85 years
• Sex: Female
• Reference Year: 2017

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 85 (e_85): 3.1 years
• Expected Age at Death: 88.1 years
• Median Survival Time: 2.2 years
• Modal Age at Death: 83.1 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_85): 29.8%
• 10-Year Survival (₁₀p_85): 8.9%
• 20-Year Survival (₂₀p_85): 0.8%

MORTALITY METRICS:
• Force of Mortality (μ_85): 0.24227
• Probability of Death within 1 Year (q_85): 0.21515
• Hazard Rate: 0.27743

COMPARATIVE CONTEXT:
• Global Average at Age 85: -0.4 years
• Regional Rank: Top 27 globally
• Historical Trend: Stable

Based on 330,682 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.5%.


Instruction: What is the life expectancy for a 69 year old male in China as of 2024?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: China
• Age: 69 years
• Sex: Male
• Reference Year: 2024

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 69 (e_69): 8.2 years
• Expected Age at Death: 77.2 years
• Median Survival Time: 5.7 years
• Modal Age at Death: 72.2 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_69): 58.2%
• 10-Year Survival (₁₀p_69): 33.9%
• 20-Year Survival (₂₀p_69): 11.5%

MORTALITY METRICS:
• Force of Mortality (μ_69): 0.10813
• Probability of Death within 1 Year (q_69): 0.10249
• Hazard Rate: 0.11444

COMPARATIVE CONTEXT:
• Global Average at Age 69: 7.9 years
• Regional Rank: Top 5 globally
• Historical Trend: Improving

Based on 493,285 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.

Human: What is the life expectancy for a 69 year old male in China as of 2024?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: China
• Age: 69 years
• Sex: Male
• Reference Year: 2024

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 69 (e_69): 8.2 years
• Expected Age at Death: 77.2 years
• Median Survival Time: 5.7 years
• Modal Age at Death: 72.2 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_69): 58.2%
• 10-Year Survival (₁₀p_69): 33.9%
• 20-Year Survival (₂₀p_69): 11.5%

MORTALITY METRICS:
• Force of Mortality (μ_69): 0.10813
• Probability of Death within 1 Year (q_69): 0.10249
• Hazard Rate: 0.11444

COMPARATIVE CONTEXT:
• Global Average at Age 69: 7.9 years
• Regional Rank: Top 5 globally
• Historical Trend: Improving

Based on 493,285 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.


Instruction: Calculate the present value of a life annuity for a 53 year old at 5.1% interest

Response:
LIFE ANNUITY VALUATION

Parameters:
• Age (x): 53
• Interest Rate (i): 5.11%
• Discount Factor (v): 0.951372
• Mortality Table: 2017 CSO

ANNUITY VALUES:
• Whole Life Annuity-Due (ä_53): 19.0584
• Whole Life Annuity-Immediate (a_53): 18.0584
• Temporary Annuity-Due (ä_53:20⌉): 14.8886
• Deferred Annuity (₁₀|ä_53): 8.2511

COMMUTATION FUNCTIONS:
• D_53 = v^53 × l_53: 2546.83
• N_53 = Σ D_k (k≥53): 10248.24
• S_53 = Σ N_k (k≥53): 365339.24

CALCULATION:
ä_53 = N_53 / D_53 = 19.0584

MONTHLY CONVERSION:
• Annual Annuity: $10000.00
• Monthly Payment: $837.17
• Conversion Factor (12): 11.719

Present Value of $1,000/month for life: $18611910.59

Human: Calculate the present value of a life annuity for a 53 year old at 5.1% interest

Actuarial AI: LIFE ANNUITY VALUATION

Parameters:
• Age (x): 53
• Interest Rate (i): 5.11%
• Discount Factor (v): 0.951372
• Mortality Table: 2017 CSO

ANNUITY VALUES:
• Whole Life Annuity-Due (ä_53): 19.0584
• Whole Life Annuity-Immediate (a_53): 18.0584
• Temporary Annuity-Due (ä_53:20⌉): 14.8886
• Deferred Annuity (₁₀|ä_53): 8.2511

COMMUTATION FUNCTIONS:
• D_53 = v^53 × l_53: 2546.83
• N_53 = Σ D_k (k≥53): 10248.24
• S_53 = Σ N_k (k≥53): 365339.24

CALCULATION:
ä_53 = N_53 / D_53 = 19.0584

MONTHLY CONVERSION:
• Annual Annuity: $10000.00
• Monthly Payment: $837.17
• Conversion Factor (12): 11.719

Present Value of $1,000/month for life: $18611910.59


Instruction: Analyze mortality impact of H1N1

Response:
PANDEMIC MORTALITY ANALYSIS

Pandemic: H1N1
Global Deaths: 379,926
Case Fatality Rate: 9.5%
Infection Fatality Rate: 0.83%

Age-specific mortality shows exponential increase with age.
Economic impact: $7.6 trillion globally.

Human: Analyze mortality impact of H1N1

Actuarial AI: PANDEMIC MORTALITY ANALYSIS

Pandemic: H1N1
Global Deaths: 379,926
Case Fatality Rate: 9.5%
Infection Fatality Rate: 0.83%

Age-specific mortality shows exponential increase with age.
Economic impact: $7.6 trillion globally.


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: 455.8
• High School: 577.9
• Some College: 444.8
• Bachelor's: 652.0
• Graduate Degree: 955.6

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.45
• Rate Difference: 483.9 per 100,000
• Population Attributable Risk: 27.4%
• Gini Coefficient: 0.153

LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 83.7 years
• High School: 75.1 years
• Some College: 72.5 years
• Bachelor's: 72.3 years
• Graduate Degree: 76.3 years

CONTRIBUTING FACTORS:
• Healthcare Access: 28% of disparity
• Socioeconomic Status: 17% of disparity
• Environmental Factors: 24% of disparity
• Behavioral Factors: 13% of disparity
• Biological Factors: 7% of disparity

TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -0.8%

Social determinants explain 72% 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: 455.8
• High School: 577.9
• Some College: 444.8
• Bachelor's: 652.0
• Graduate Degree: 955.6

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.45
• Rate Difference: 483.9 per 100,000
• Population Attributable Risk: 27.4%
• Gini Coefficient: 0.153

LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 83.7 years
• High School: 75.1 years
• Some College: 72.5 years
• Bachelor's: 72.3 years
• Graduate Degree: 76.3 years

CONTRIBUTING FACTORS:
• Healthcare Access: 28% of disparity
• Socioeconomic Status: 17% of disparity
• Environmental Factors: 24% of disparity
• Behavioral Factors: 13% of disparity
• Biological Factors: 7% of disparity

TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -0.8%

Social determinants explain 72% of observed mortality differences.


Instruction: Analyze mortality differences by marital status in the USA

Response:
DEMOGRAPHIC MORTALITY ANALYSIS

Demographic Variable: Marital Status
Country: USA
Analysis Period: 2021

MORTALITY RATES BY MARITAL STATUS (per 100,000):
• Married: 759.0
• Single: 835.5
• Divorced: 1163.5
• Widowed: 856.8

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.68
• Rate Difference: 515.8 per 100,000
• Population Attributable Risk: 24.4%
• Gini Coefficient: 0.335

LIFE EXPECTANCY BY MARITAL STATUS:
• Married: 76.3 years
• Single: 75.2 years
• Divorced: 83.5 years
• Widowed: 74.1 years

CONTRIBUTING FACTORS:
• Healthcare Access: 26% of disparity
• Socioeconomic Status: 35% of disparity
• Environmental Factors: 11% of disparity
• Behavioral Factors: 24% of disparity
• Biological Factors: 15% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +1.3%

Social determinants explain 76% 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: 2021

MORTALITY RATES BY MARITAL STATUS (per 100,000):
• Married: 759.0
• Single: 835.5
• Divorced: 1163.5
• Widowed: 856.8

DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.68
• Rate Difference: 515.8 per 100,000
• Population Attributable Risk: 24.4%
• Gini Coefficient: 0.335

LIFE EXPECTANCY BY MARITAL STATUS:
• Married: 76.3 years
• Single: 75.2 years
• Divorced: 83.5 years
• Widowed: 74.1 years

CONTRIBUTING FACTORS:
• Healthcare Access: 26% of disparity
• Socioeconomic Status: 35% of disparity
• Environmental Factors: 11% of disparity
• Behavioral Factors: 24% of disparity
• Biological Factors: 15% of disparity

TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +1.3%

Social determinants explain 76% of observed mortality differences.


Instruction: Summarize individual life mortality experience study results

Response:
MORTALITY EXPERIENCE STUDY

Study Type: Individual Life Insurance
Study Period: 2021-2022
Exposure: 531054 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.90
• Deaths Actual: 9,878
• Deaths Expected: 8,824

BY DURATION:
• Select Period (Years 1-5): 0.81
• Ultimate (Years 6+): 1.03

Statistical confidence: 95% CI [0.81, 1.05]

Human: Summarize individual life mortality experience study results

Actuarial AI: MORTALITY EXPERIENCE STUDY

Study Type: Individual Life Insurance
Study Period: 2021-2022
Exposure: 531054 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.90
• Deaths Actual: 9,878
• Deaths Expected: 8,824

BY DURATION:
• Select Period (Years 1-5): 0.81
• Ultimate (Years 6+): 1.03

Statistical confidence: 95% CI [0.81, 1.05]


Instruction: Calculate excess mortality during opioid crisis in Italy for Q3 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: opioid crisis
Location: Italy
Period: Q3 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 14,607
• Observed Deaths: 19,017
• Excess Deaths: 4,410
• Excess Mortality Rate: 30.2%
• P-score: 30.2%
• Z-score: 4.87 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.3% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 8.8% (441 deaths)
• 45-64 years: 7.5% (1,102 deaths)
• 65-74 years: 10.1% (1,102 deaths)
• 75+ years: 31.9% (1,764 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 2,885 (53%)
• Indirect (probable): 1,139 (21%)
• Collateral (delayed care): 646 (15%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [3,748, 5,071]
• Probability of chance: < 0.001
• Power: 0.99

Years of Life Lost: 53835
Economic Impact: $2.7 billion
Quality-Adjusted Life Years Lost: 46871

Human: Calculate excess mortality during opioid crisis in Italy for Q3 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: opioid crisis
Location: Italy
Period: Q3 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 14,607
• Observed Deaths: 19,017
• Excess Deaths: 4,410
• Excess Mortality Rate: 30.2%
• P-score: 30.2%
• Z-score: 4.87 (p < 0.001)

BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.3% annual

AGE-SPECIFIC EXCESS:
• 0-44 years: 8.8% (441 deaths)
• 45-64 years: 7.5% (1,102 deaths)
• 65-74 years: 10.1% (1,102 deaths)
• 75+ years: 31.9% (1,764 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 2,885 (53%)
• Indirect (probable): 1,139 (21%)
• Collateral (delayed care): 646 (15%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [3,748, 5,071]
• Probability of chance: < 0.001
• Power: 0.99

Years of Life Lost: 53835
Economic Impact: $2.7 billion
Quality-Adjusted Life Years Lost: 46871


Instruction: Analyze mortality patterns for 1962 birth cohort

Response:
BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1962
Current Age: 62 years
Cohort Size at Birth: 3,635,846

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 68.4 years
• Current Life Expectancy: 78.0 years
• Survival to Current Age: 85.3%

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

MORTALITY PATTERN:
• Peak Infant Mortality: 49.0 per 1,000
• Current Mortality Rate: 47.4 per 1,000
• Improvement Since Birth: 60%

Cohort effects explain 28% of mortality variation.

Human: Analyze mortality patterns for 1962 birth cohort

Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS

Birth Cohort: 1962
Current Age: 62 years
Cohort Size at Birth: 3,635,846

COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 68.4 years
• Current Life Expectancy: 78.0 years
• Survival to Current Age: 85.3%

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

MORTALITY PATTERN:
• Peak Infant Mortality: 49.0 per 1,000
• Current Mortality Rate: 47.4 per 1,000
• Improvement Since Birth: 60%

Cohort effects explain 28% of mortality variation.


Instruction: What is the mortality rate for Hypertension in UK for 25-44 in 2024?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Hypertension
Location: UK
Year: 2024
Age Group: 25-44

MORTALITY STATISTICS:
• Crude Death Rate: 11.6 per 100,000 population
• Age-Adjusted Rate: 10.0 per 100,000
• Total Deaths: 291,613
• Percentage of All Deaths: 22.0%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 13.9 per 100,000
• Female Death Rate: 9.9 per 100,000
• Sex Ratio (M:F): 1.32:1

TREND ANALYSIS:
• 5-Year Change: +9.7%
• 10-Year Change: +22.2%
• Annual Percentage Change: -2.2%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #10
• Years of Potential Life Lost (YPLL): 6048632
• Economic Burden: $72.7 billion annually
• Preventable Deaths: 26%

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

International Classification of Diseases (ICD-10): I10-I15
Data Quality: Partial (90% coverage)

Human: What is the mortality rate for Hypertension in UK for 25-44 in 2024?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Hypertension
Location: UK
Year: 2024
Age Group: 25-44

MORTALITY STATISTICS:
• Crude Death Rate: 11.6 per 100,000 population
• Age-Adjusted Rate: 10.0 per 100,000
• Total Deaths: 291,613
• Percentage of All Deaths: 22.0%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 13.9 per 100,000
• Female Death Rate: 9.9 per 100,000
• Sex Ratio (M:F): 1.32:1

TREND ANALYSIS:
• 5-Year Change: +9.7%
• 10-Year Change: +22.2%
• Annual Percentage Change: -2.2%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #10
• Years of Potential Life Lost (YPLL): 6048632
• Economic Burden: $72.7 billion annually
• Preventable Deaths: 26%

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

International Classification of Diseases (ICD-10): I10-I15
Data Quality: Partial (90% coverage)


Instruction: What is the life expectancy for a 61 year old female in China as of 2015?

Response:
ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: China
• Age: 61 years
• Sex: Female
• Reference Year: 2015

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 61 (e_61): 21.8 years
• Expected Age at Death: 82.8 years
• Median Survival Time: 15.1 years
• Modal Age at Death: 77.8 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_61): 80.3%
• 10-Year Survival (₁₀p_61): 64.5%
• 20-Year Survival (₂₀p_61): 41.7%

MORTALITY METRICS:
• Force of Mortality (μ_61): 0.04378
• Probability of Death within 1 Year (q_61): 0.04284
• Hazard Rate: 0.04477

COMPARATIVE CONTEXT:
• Global Average at Age 61: 15.9 years
• Regional Rank: Top 22 globally
• Historical Trend: Improving

Based on 216,888 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.1%.

Human: What is the life expectancy for a 61 year old female in China as of 2015?

Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation

Demographics:
• Location: China
• Age: 61 years
• Sex: Female
• Reference Year: 2015

LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 61 (e_61): 21.8 years
• Expected Age at Death: 82.8 years
• Median Survival Time: 15.1 years
• Modal Age at Death: 77.8 years

SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_61): 80.3%
• 10-Year Survival (₁₀p_61): 64.5%
• 20-Year Survival (₂₀p_61): 41.7%

MORTALITY METRICS:
• Force of Mortality (μ_61): 0.04378
• Probability of Death within 1 Year (q_61): 0.04284
• Hazard Rate: 0.04477

COMPARATIVE CONTEXT:
• Global Average at Age 61: 15.9 years
• Regional Rank: Top 22 globally
• Historical Trend: Improving

Based on 216,888 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.1%.


Instruction: Calculate Term life insurance premium for 47 year old female, $5,000,000 coverage, 25 year term, Preferred Plus rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Term Life Insurance
• Face Amount: $5,000,000
• Term Length: 25 years
• Issue Age: 47
• Sex: Female
• Underwriting Class: Preferred Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_47): 0.001254
• Underwriting Multiplier: 0.6x
• Product Load Factor: 1.0x
• Expense Loading: 15% of gross premium
• Commission Load: 57% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $3763.19
• Expense Charge: $940.80
• Reserve Accumulation: $1254.40
• Profit Margin: $313.60
• Gross Annual Premium: $6271.99

PAYMENT OPTIONS:
• Annual: $6271.99
• Semi-Annual: $3261.43 (x2 = $6522.87/year)
• Quarterly: $1662.08 (x4 = $6648.31/year)
• Monthly: $564.48 (x12 = $6773.75/year)

RESERVE CALCULATIONS:
• Net Level Premium: $4703.99
• First Year Reserve: $1254.40
• Terminal Reserve (Year 25): $2221632.41

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

Internal Rate of Return: 11.9%
Profit Margin: 13.0%
Lapse Assumption: 6.1% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Term life insurance premium for 47 year old female, $5,000,000 coverage, 25 year term, Preferred Plus rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Term Life Insurance
• Face Amount: $5,000,000
• Term Length: 25 years
• Issue Age: 47
• Sex: Female
• Underwriting Class: Preferred Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_47): 0.001254
• Underwriting Multiplier: 0.6x
• Product Load Factor: 1.0x
• Expense Loading: 15% of gross premium
• Commission Load: 57% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $3763.19
• Expense Charge: $940.80
• Reserve Accumulation: $1254.40
• Profit Margin: $313.60
• Gross Annual Premium: $6271.99

PAYMENT OPTIONS:
• Annual: $6271.99
• Semi-Annual: $3261.43 (x2 = $6522.87/year)
• Quarterly: $1662.08 (x4 = $6648.31/year)
• Monthly: $564.48 (x12 = $6773.75/year)

RESERVE CALCULATIONS:
• Net Level Premium: $4703.99
• First Year Reserve: $1254.40
• Terminal Reserve (Year 25): $2221632.41

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

Internal Rate of Return: 11.9%
Profit Margin: 13.0%
Lapse Assumption: 6.1% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: Calculate policy reserve for 39 year old, 20-year term life, year 10

Response:
POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 29
• Current Age: 39
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $1402.05
• Present Value Future Benefits (PVFB): $50724.15
• Present Value Future Premiums (PVFP): $39690.61

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $13638.99
• Per $1,000 Face: $136.39

PROSPECTIVE METHOD:
• A₁_39:10⌉ = 0.1756
• ä_39:10⌉ = 8.4356
• ₁₀V = 100,000 × A₁ - P × ä = $13638.99

RETROSPECTIVE METHOD:
• Accumulated Premiums: $10032.94
• Accumulated Cost of Insurance: $5737.12
• Interest Earned: $1539.94
• ₁₀V = $13638.99

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $12957.04
• Tax Reserve: $12547.87
• GAAP Reserve: $14320.94

Human: Calculate policy reserve for 39 year old, 20-year term life, year 10

Actuarial AI: POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 29
• Current Age: 39
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $1402.05
• Present Value Future Benefits (PVFB): $50724.15
• Present Value Future Premiums (PVFP): $39690.61

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $13638.99
• Per $1,000 Face: $136.39

PROSPECTIVE METHOD:
• A₁_39:10⌉ = 0.1756
• ä_39:10⌉ = 8.4356
• ₁₀V = 100,000 × A₁ - P × ä = $13638.99

RETROSPECTIVE METHOD:
• Accumulated Premiums: $10032.94
• Accumulated Cost of Insurance: $5737.12
• Interest Earned: $1539.94
• ₁₀V = $13638.99

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $12957.04
• Tax Reserve: $12547.87
• GAAP Reserve: $14320.94


Instruction: Analyze mortality trends in Germany from 2003-2023

Response:
MORTALITY TREND ANALYSIS

Country: Germany
Analysis Period: 2003-2023

OVERALL TRENDS:
• Average Annual Change: -1.3%
• Total Change: -16.3%
• Trend Direction: Improving
• Statistical Significance: p < 0.001

Life expectancy decreased by 1.2 years.
Age-standardized death rate changed by +121 per 100,000.

KEY DRIVERS:
• Medical advances: 21% of improvement
• Public health measures: 24%
• Lifestyle changes: +17%
• Environmental factors: -6%

Human: Analyze mortality trends in Germany from 2003-2023

Actuarial AI: MORTALITY TREND ANALYSIS

Country: Germany
Analysis Period: 2003-2023

OVERALL TRENDS:
• Average Annual Change: -1.3%
• Total Change: -16.3%
• Trend Direction: Improving
• Statistical Significance: p < 0.001

Life expectancy decreased by 1.2 years.
Age-standardized death rate changed by +121 per 100,000.

KEY DRIVERS:
• Medical advances: 21% of improvement
• Public health measures: 24%
• Lifestyle changes: +17%
• Environmental factors: -6%


Instruction: Summarize annuity mortality experience study results

Response:
MORTALITY EXPERIENCE STUDY

Study Type: Annuity Insurance
Study Period: 2021-2023
Exposure: 435193 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.99
• Deaths Actual: 9,978
• Deaths Expected: 6,080

BY DURATION:
• Select Period (Years 1-5): 0.79
• Ultimate (Years 6+): 1.07

Statistical confidence: 95% CI [0.91, 1.10]

Human: Summarize annuity mortality experience study results

Actuarial AI: MORTALITY EXPERIENCE STUDY

Study Type: Annuity Insurance
Study Period: 2021-2023
Exposure: 435193 life-years

ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.99
• Deaths Actual: 9,978
• Deaths Expected: 6,080

BY DURATION:
• Select Period (Years 1-5): 0.79
• Ultimate (Years 6+): 1.07

Statistical confidence: 95% CI [0.91, 1.10]


Instruction: Calculate policy reserve for 60 year old, 20-year term life, year 10

Response:
POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 50
• Current Age: 60
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $1405.09
• Present Value Future Benefits (PVFB): $49933.98
• Present Value Future Premiums (PVFP): $33868.55

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $12226.40
• Per $1,000 Face: $122.26

PROSPECTIVE METHOD:
• A₁_60:10⌉ = 0.1994
• ä_60:10⌉ = 8.1328
• ₁₀V = 100,000 × A₁ - P × ä = $12226.40

RETROSPECTIVE METHOD:
• Accumulated Premiums: $8637.51
• Accumulated Cost of Insurance: $5775.64
• Interest Earned: $1337.81
• ₁₀V = $12226.40

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $11615.08
• Tax Reserve: $11248.29
• GAAP Reserve: $12837.72

Human: Calculate policy reserve for 60 year old, 20-year term life, year 10

Actuarial AI: POLICY RESERVE CALCULATION

Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 50
• Current Age: 60
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)

RESERVE COMPONENTS:
• Net Level Premium (P): $1405.09
• Present Value Future Benefits (PVFB): $49933.98
• Present Value Future Premiums (PVFP): $33868.55

TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $12226.40
• Per $1,000 Face: $122.26

PROSPECTIVE METHOD:
• A₁_60:10⌉ = 0.1994
• ä_60:10⌉ = 8.1328
• ₁₀V = 100,000 × A₁ - P × ä = $12226.40

RETROSPECTIVE METHOD:
• Accumulated Premiums: $8637.51
• Accumulated Cost of Insurance: $5775.64
• Interest Earned: $1337.81
• ₁₀V = $12226.40

STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $11615.08
• Tax Reserve: $11248.29
• GAAP Reserve: $12837.72


Instruction: What is the mortality rate for Influenza/Pneumonia in Germany for Under 25 in 2020?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Influenza/Pneumonia
Location: Germany
Year: 2020
Age Group: Under 25

MORTALITY STATISTICS:
• Crude Death Rate: 11.1 per 100,000 population
• Age-Adjusted Rate: 9.9 per 100,000
• Total Deaths: 19,828
• Percentage of All Deaths: 6.7%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 13.3 per 100,000
• Female Death Rate: 9.4 per 100,000
• Sex Ratio (M:F): 1.49:1

TREND ANALYSIS:
• 5-Year Change: -8.5%
• 10-Year Change: +20.3%
• Annual Percentage Change: +2.0%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 406422
• Economic Burden: $47.0 billion annually
• Preventable Deaths: 60%

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

International Classification of Diseases (ICD-10): J09-J18
Data Quality: Partial (94% coverage)

Human: What is the mortality rate for Influenza/Pneumonia in Germany for Under 25 in 2020?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Influenza/Pneumonia
Location: Germany
Year: 2020
Age Group: Under 25

MORTALITY STATISTICS:
• Crude Death Rate: 11.1 per 100,000 population
• Age-Adjusted Rate: 9.9 per 100,000
• Total Deaths: 19,828
• Percentage of All Deaths: 6.7%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 13.3 per 100,000
• Female Death Rate: 9.4 per 100,000
• Sex Ratio (M:F): 1.49:1

TREND ANALYSIS:
• 5-Year Change: -8.5%
• 10-Year Change: +20.3%
• Annual Percentage Change: +2.0%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 406422
• Economic Burden: $47.0 billion annually
• Preventable Deaths: 60%

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

International Classification of Diseases (ICD-10): J09-J18
Data Quality: Partial (94% coverage)


Instruction: Calculate the 1-year death probability for a 38 year oldsmoker with diabetes, hypertension

Response:
MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 38 years
• Assessment Period: 1 year
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: diabetes, hypertension

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_38): 0.001395 (0.1395%)
• 1-Year Death Probability (₍1₎q_38): 0.001395 (0.140%)
• Survival Probability (₍1₎p_38): 0.998605 (99.860%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_38): 0.001396
• Hazard Rate (h_38): 0.001396
• Cumulative Hazard (H_38): 0.001396
• Median Future Lifetime: 496.4 years

RISK CLASSIFICATION:
• Mortality Ratio: 1.4x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 40%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.001186
• Upper Bound: 0.001605

Analysis based on 167,407 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.

Human: Calculate the 1-year death probability for a 38 year oldsmoker with diabetes, hypertension

Actuarial AI: MORTALITY RISK ASSESSMENT

Subject Profile:
• Age: 38 years
• Assessment Period: 1 year
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: diabetes, hypertension

DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_38): 0.001395 (0.1395%)
• 1-Year Death Probability (₍1₎q_38): 0.001395 (0.140%)
• Survival Probability (₍1₎p_38): 0.998605 (99.860%)

DETAILED MORTALITY METRICS:
• Force of Mortality (μ_38): 0.001396
• Hazard Rate (h_38): 0.001396
• Cumulative Hazard (H_38): 0.001396
• Median Future Lifetime: 496.4 years

RISK CLASSIFICATION:
• Mortality Ratio: 1.4x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 40%

CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.001186
• Upper Bound: 0.001605

Analysis based on 167,407 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.


Instruction: Calculate excess mortality during opioid crisis in Brazil for Q4 2021

Response:
EXCESS MORTALITY ANALYSIS

Event: opioid crisis
Location: Brazil
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 87,684
• Observed Deaths: 131,399
• Excess Deaths: 43,715
• Excess Mortality Rate: 49.9%
• P-score: 49.9%
• Z-score: 3.73 (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: 8.6% (4,371 deaths)
• 45-64 years: 12.0% (10,928 deaths)
• 65-74 years: 18.6% (10,928 deaths)
• 75+ years: 30.2% (17,486 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 22,056 (56%)
• Indirect (probable): 7,076 (26%)
• Collateral (delayed care): 5,274 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [37,157, 50,272]
• Probability of chance: < 0.001
• Power: 0.96

Years of Life Lost: 543589
Economic Impact: $2.7 billion
Quality-Adjusted Life Years Lost: 382167

Human: Calculate excess mortality during opioid crisis in Brazil for Q4 2021

Actuarial AI: EXCESS MORTALITY ANALYSIS

Event: opioid crisis
Location: Brazil
Period: Q4 2021

MORTALITY METRICS:
• Expected Deaths (Baseline): 87,684
• Observed Deaths: 131,399
• Excess Deaths: 43,715
• Excess Mortality Rate: 49.9%
• P-score: 49.9%
• Z-score: 3.73 (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: 8.6% (4,371 deaths)
• 45-64 years: 12.0% (10,928 deaths)
• 65-74 years: 18.6% (10,928 deaths)
• 75+ years: 30.2% (17,486 deaths)

CAUSE ATTRIBUTION:
• Direct (confirmed): 22,056 (56%)
• Indirect (probable): 7,076 (26%)
• Collateral (delayed care): 5,274 (19%)

STATISTICAL SIGNIFICANCE:
• 95% CI: [37,157, 50,272]
• Probability of chance: < 0.001
• Power: 0.96

Years of Life Lost: 543589
Economic Impact: $2.7 billion
Quality-Adjusted Life Years Lost: 382167


Instruction: What is the mortality rate for Stroke in UK for 25-44 in 2021?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Stroke
Location: UK
Year: 2021
Age Group: 25-44

MORTALITY STATISTICS:
• Crude Death Rate: 43.5 per 100,000 population
• Age-Adjusted Rate: 40.8 per 100,000
• Total Deaths: 143,058
• Percentage of All Deaths: 19.8%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 52.2 per 100,000
• Female Death Rate: 37.0 per 100,000
• Sex Ratio (M:F): 1.28:1

TREND ANALYSIS:
• 5-Year Change: +9.7%
• 10-Year Change: +18.5%
• Annual Percentage Change: +2.5%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 3178678
• Economic Burden: $91.5 billion annually
• Preventable Deaths: 45%

RISK FACTORS:
• Hypertension: 50% attributable
• Atrial fibrillation: 25%
• Diabetes: 20%
• High cholesterol: 15%
• Smoking: 20%

International Classification of Diseases (ICD-10): I60-I69
Data Quality: Partial (93% coverage)

Human: What is the mortality rate for Stroke in UK for 25-44 in 2021?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Stroke
Location: UK
Year: 2021
Age Group: 25-44

MORTALITY STATISTICS:
• Crude Death Rate: 43.5 per 100,000 population
• Age-Adjusted Rate: 40.8 per 100,000
• Total Deaths: 143,058
• Percentage of All Deaths: 19.8%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 52.2 per 100,000
• Female Death Rate: 37.0 per 100,000
• Sex Ratio (M:F): 1.28:1

TREND ANALYSIS:
• 5-Year Change: +9.7%
• 10-Year Change: +18.5%
• Annual Percentage Change: +2.5%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 3178678
• Economic Burden: $91.5 billion annually
• Preventable Deaths: 45%

RISK FACTORS:
• Hypertension: 50% attributable
• Atrial fibrillation: 25%
• Diabetes: 20%
• High cholesterol: 15%
• Smoking: 20%

International Classification of Diseases (ICD-10): I60-I69
Data Quality: Partial (93% coverage)


Instruction: Compare infant mortality between Brazil, China, India and Mexico

Response:
INTERNATIONAL MORTALITY COMPARISON

Metric: Infant Mortality
Countries: Brazil, China, India, Mexico
Reference Year: 2023

COMPARATIVE STATISTICS:
• Brazil: 9.9 per 1,000 live births
• China: 3.1 per 1,000 live births
• India: 19.3 per 1,000 live births
• Mexico: 20.0 per 1,000 live births

RANKINGS:
1. China: 3.1
2. Brazil: 9.9
3. India: 19.3
4. Mexico: 20.0

STATISTICAL ANALYSIS:
• Range: 16.9
• Mean: 13.1
• Median: 14.6
• Standard Deviation: 7.0
• Coefficient of Variation: 53.7%

RELATIVE COMPARISONS:
• Best vs Worst: 6.53x difference
• Above Average: 2/4
• Global Ranking: Brazil: #15, China: #91, India: #139

CONTRIBUTING FACTORS:
• Healthcare System: 32% of variation
• Economic Development: 23% of variation
• Public Health Policy: 15% of variation
• Demographics: 16% of variation
• Environmental Factors: 9% of variation

Convergence/Divergence: Converging at 0.9% annually

Human: Compare infant mortality between Brazil, China, India and Mexico

Actuarial AI: INTERNATIONAL MORTALITY COMPARISON

Metric: Infant Mortality
Countries: Brazil, China, India, Mexico
Reference Year: 2023

COMPARATIVE STATISTICS:
• Brazil: 9.9 per 1,000 live births
• China: 3.1 per 1,000 live births
• India: 19.3 per 1,000 live births
• Mexico: 20.0 per 1,000 live births

RANKINGS:
1. China: 3.1
2. Brazil: 9.9
3. India: 19.3
4. Mexico: 20.0

STATISTICAL ANALYSIS:
• Range: 16.9
• Mean: 13.1
• Median: 14.6
• Standard Deviation: 7.0
• Coefficient of Variation: 53.7%

RELATIVE COMPARISONS:
• Best vs Worst: 6.53x difference
• Above Average: 2/4
• Global Ranking: Brazil: #15, China: #91, India: #139

CONTRIBUTING FACTORS:
• Healthcare System: 32% of variation
• Economic Development: 23% of variation
• Public Health Policy: 15% of variation
• Demographics: 16% of variation
• Environmental Factors: 9% of variation

Convergence/Divergence: Converging at 0.9% annually


Instruction: Calculate Universal Life life insurance premium for 42 year old male, $750,000 coverage, Preferred Plus rating

Response:
LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 42
• Sex: Male
• Underwriting Class: Preferred Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_42): 0.001437
• Underwriting Multiplier: 0.6x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 90% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1810.10
• Expense Charge: $452.52
• Reserve Accumulation: $603.37
• Profit Margin: $150.84
• Gross Annual Premium: $3016.83

PAYMENT OPTIONS:
• Annual: $3016.83
• Semi-Annual: $1568.75 (x2 = $3137.50/year)
• Quarterly: $799.46 (x4 = $3197.84/year)
• Monthly: $271.51 (x12 = $3258.18/year)

RESERVE CALCULATIONS:
• Net Level Premium: $2262.62
• First Year Reserve: $603.37
• Terminal Reserve (Year 23): $465908.78

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2020
• Select Period: 25 years
• Ultimate Mortality: CSO Male Ultimate

Internal Rate of Return: 10.0%
Profit Margin: 8.3%
Lapse Assumption: 6.6% annual

Illustration assumes guaranteed rates. Actual results may vary.

Human: Calculate Universal Life life insurance premium for 42 year old male, $750,000 coverage, Preferred Plus rating

Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION

Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 42
• Sex: Male
• Underwriting Class: Preferred Plus

PREMIUM COMPUTATION:
• Base Mortality Rate (q_42): 0.001437
• Underwriting Multiplier: 0.6x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 90% first year, 5% renewal

ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1810.10
• Expense Charge: $452.52
• Reserve Accumulation: $603.37
• Profit Margin: $150.84
• Gross Annual Premium: $3016.83

PAYMENT OPTIONS:
• Annual: $3016.83
• Semi-Annual: $1568.75 (x2 = $3137.50/year)
• Quarterly: $799.46 (x4 = $3197.84/year)
• Monthly: $271.51 (x12 = $3258.18/year)

RESERVE CALCULATIONS:
• Net Level Premium: $2262.62
• First Year Reserve: $603.37
• Terminal Reserve (Year 23): $465908.78

MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2020
• Select Period: 25 years
• Ultimate Mortality: CSO Male Ultimate

Internal Rate of Return: 10.0%
Profit Margin: 8.3%
Lapse Assumption: 6.6% annual

Illustration assumes guaranteed rates. Actual results may vary.


Instruction: If X ~ N(100, 225), find P(85 < X < 115)

Response: Given μ=100, σ²=225, so σ=15. Standardize: P(85 < X < 115) = P((85-100)/15 < Z < (115-100)/15) = P(-1 < Z < 1) = Φ(1) - Φ(-1) ≈ 0.8413 - 0.1587 = 0.6826

Human: If X ~ N(100, 225), find P(85 < X < 115)

Actuarial AI: Given μ=100, σ²=225, so σ=15. Standardize: P(85 < X < 115) = P((85-100)/15 < Z < (115-100)/15) = P(-1 < Z < 1) = Φ(1) - Φ(-1) ≈ 0.8413 - 0.1587 = 0.6826


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

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

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

MORTALITY STATISTICS:
• Crude Death Rate: 211.3 per 100,000 population
• Age-Adjusted Rate: 187.9 per 100,000
• Total Deaths: 6,922,971
• Percentage of All Deaths: 13.0%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 253.5 per 100,000
• Female Death Rate: 179.6 per 100,000
• Sex Ratio (M:F): 1.37:1

TREND ANALYSIS:
• 5-Year Change: -13.6%
• 10-Year Change: +8.3%
• Annual Percentage Change: -2.2%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #7
• Years of Potential Life Lost (YPLL): 167599705
• Economic Burden: $26.2 billion annually
• Preventable Deaths: 56%

RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%

International Classification of Diseases (ICD-10): I00-I99
Data Quality: Partial (95% coverage)

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

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

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

MORTALITY STATISTICS:
• Crude Death Rate: 211.3 per 100,000 population
• Age-Adjusted Rate: 187.9 per 100,000
• Total Deaths: 6,922,971
• Percentage of All Deaths: 13.0%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 253.5 per 100,000
• Female Death Rate: 179.6 per 100,000
• Sex Ratio (M:F): 1.37:1

TREND ANALYSIS:
• 5-Year Change: -13.6%
• 10-Year Change: +8.3%
• Annual Percentage Change: -2.2%
• Trend: Increasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #7
• Years of Potential Life Lost (YPLL): 167599705
• Economic Burden: $26.2 billion annually
• Preventable Deaths: 56%

RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%

International Classification of Diseases (ICD-10): I00-I99
Data Quality: Partial (95% coverage)


Instruction: Analyze mortality impact of SARS

Response:
PANDEMIC MORTALITY ANALYSIS

Pandemic: SARS
Global Deaths: 881
Case Fatality Rate: 6.8%
Infection Fatality Rate: 1.60%

Age-specific mortality shows exponential increase with age.
Economic impact: $7.6 trillion globally.

Human: Analyze mortality impact of SARS

Actuarial AI: PANDEMIC MORTALITY ANALYSIS

Pandemic: SARS
Global Deaths: 881
Case Fatality Rate: 6.8%
Infection Fatality Rate: 1.60%

Age-specific mortality shows exponential increase with age.
Economic impact: $7.6 trillion globally.


Instruction: What is the mortality rate for Septicemia in Australia for 75+ in 2021?

Response:
CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Septicemia
Location: Australia
Year: 2021
Age Group: 75+

MORTALITY STATISTICS:
• Crude Death Rate: 13.0 per 100,000 population
• Age-Adjusted Rate: 11.4 per 100,000
• Total Deaths: 446,798
• Percentage of All Deaths: 3.2%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 15.6 per 100,000
• Female Death Rate: 11.0 per 100,000
• Sex Ratio (M:F): 1.22:1

TREND ANALYSIS:
• 5-Year Change: -3.9%
• 10-Year Change: -10.3%
• Annual Percentage Change: -1.1%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #11
• Years of Potential Life Lost (YPLL): 8332814
• Economic Burden: $92.5 billion annually
• Preventable Deaths: 36%

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

International Classification of Diseases (ICD-10): A40-A41
Data Quality: Complete (97% coverage)

Human: What is the mortality rate for Septicemia in Australia for 75+ in 2021?

Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS

Cause of Death: Septicemia
Location: Australia
Year: 2021
Age Group: 75+

MORTALITY STATISTICS:
• Crude Death Rate: 13.0 per 100,000 population
• Age-Adjusted Rate: 11.4 per 100,000
• Total Deaths: 446,798
• Percentage of All Deaths: 3.2%

DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 15.6 per 100,000
• Female Death Rate: 11.0 per 100,000
• Sex Ratio (M:F): 1.22:1

TREND ANALYSIS:
• 5-Year Change: -3.9%
• 10-Year Change: -10.3%
• Annual Percentage Change: -1.1%
• Trend: Decreasing

COMPARATIVE METRICS:
• Rank Among Leading Causes: #11
• Years of Potential Life Lost (YPLL): 8332814
• Economic Burden: $92.5 billion annually
• Preventable Deaths: 36%

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

International Classification of Diseases (ICD-10): A40-A41
Data Quality: Complete (97% coverage)