instruction stringlengths 3 177 | response stringlengths 53 582k | type stringclasses 25 values | text stringlengths 144 582k | version stringclasses 3 values | exam stringclasses 2 values | source stringclasses 4 values |
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Compare cancer mortality between South Korea, Russia and Spain | INTERNATIONAL MORTALITY COMPARISON
Metric: Cancer Mortality
Countries: South Korea, Russia, Spain
Reference Year: 2023
COMPARATIVE STATISTICS:
• South Korea: 174.2 per 100,000 population
• Russia: 178.9 per 100,000 population
• Spain: 173.2 per 100,000 population
RANKINGS:
1. Spain: 173.2
2. South Korea: 174.2
3. Russia: 178.9
STATISTICAL ANALYSIS:
• Range: 5.7
• Mean: 175.4
• Median: 174.2
• Standard Deviation: 2.5
• Coefficient of Variation: 1.4%
RELATIVE COMPARISONS:
• Best vs Worst: 1.03x difference
• Above Average: 1/3
• Global Ranking: South Korea: #124, Russia: #23, Spain: #105
CONTRIBUTING FACTORS:
• Healthcare System: 29% of variation
• Economic Development: 18% of variation
• Public Health Policy: 19% of variation
• Demographics: 13% of variation
• Environmental Factors: 10% of variation
Convergence/Divergence: Converging at 1.1% annually | comparison | Human: Compare cancer mortality between South Korea, Russia and Spain
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Cancer Mortality
Countries: South Korea, Russia, Spain
Reference Year: 2023
COMPARATIVE STATISTICS:
• South Korea: 174.2 per 100,000 population
• Russia: 178.9 per 100,000 population
• Spain: 173.2 per 100,000 population
RANKINGS:
1. Spain: 173.2
2. South Korea: 174.2
3. Russia: 178.9
STATISTICAL ANALYSIS:
• Range: 5.7
• Mean: 175.4
• Median: 174.2
• Standard Deviation: 2.5
• Coefficient of Variation: 1.4%
RELATIVE COMPARISONS:
• Best vs Worst: 1.03x difference
• Above Average: 1/3
• Global Ranking: South Korea: #124, Russia: #23, Spain: #105
CONTRIBUTING FACTORS:
• Healthcare System: 29% of variation
• Economic Development: 18% of variation
• Public Health Policy: 19% of variation
• Demographics: 13% of variation
• Environmental Factors: 10% of variation
Convergence/Divergence: Converging at 1.1% annually | 0.0.5 | null | null |
Calculate the 30-year death probability for a 59 year old with obesity | MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 59 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: obesity
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_59): 0.000888 (0.0888%)
• 30-Year Death Probability (₍30₎q_59): 0.026313 (2.631%)
• Survival Probability (₍30₎p_59): 0.973687 (97.369%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_59): 0.000889
• Hazard Rate (h_59): 0.000889
• Cumulative Hazard (H_59): 0.026665
• Median Future Lifetime: 779.8 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.9x standard
• Risk Category: Preferred Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.022366
• Upper Bound: 0.030260
Analysis based on 66,566 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE. | death_probability | Human: Calculate the 30-year death probability for a 59 year old with obesity
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 59 years
• Assessment Period: 30 years
• Smoking Status: Non-smoker
• Health Conditions: obesity
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_59): 0.000888 (0.0888%)
• 30-Year Death Probability (₍30₎q_59): 0.026313 (2.631%)
• Survival Probability (₍30₎p_59): 0.973687 (97.369%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_59): 0.000889
• Hazard Rate (h_59): 0.000889
• Cumulative Hazard (H_59): 0.026665
• Median Future Lifetime: 779.8 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.9x standard
• Risk Category: Preferred Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.022366
• Upper Bound: 0.030260
Analysis based on 66,566 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE. | 0.0.5 | null | null |
Calculate excess mortality during seasonal flu in Germany for 2021 | EXCESS MORTALITY ANALYSIS
Event: seasonal flu
Location: Germany
Period: 2021
MORTALITY METRICS:
• Expected Deaths (Baseline): 74,466
• Observed Deaths: 88,008
• Excess Deaths: 13,542
• Excess Mortality Rate: 18.2%
• P-score: 18.2%
• Z-score: 3.02 (p < 0.001)
BASELINE CALCULATION:
• Method: Farrington surveillance
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.8% annual
AGE-SPECIFIC EXCESS:
• 0-44 years: -3.7% (1,354 deaths)
• 45-64 years: 19.1% (3,385 deaths)
• 65-74 years: 26.9% (3,385 deaths)
• 75+ years: 39.0% (5,416 deaths)
CAUSE ATTRIBUTION:
• Direct (confirmed): 8,459 (51%)
• Indirect (probable): 2,301 (26%)
• Collateral (delayed care): 2,542 (18%)
STATISTICAL SIGNIFICANCE:
• 95% CI: [11,510, 15,573]
• Probability of chance: < 0.001
• Power: 0.98
Years of Life Lost: 200891
Economic Impact: $10.0 billion
Quality-Adjusted Life Years Lost: 150031 | excess_mortality | Human: Calculate excess mortality during seasonal flu in Germany for 2021
Actuarial AI: EXCESS MORTALITY ANALYSIS
Event: seasonal flu
Location: Germany
Period: 2021
MORTALITY METRICS:
• Expected Deaths (Baseline): 74,466
• Observed Deaths: 88,008
• Excess Deaths: 13,542
• Excess Mortality Rate: 18.2%
• P-score: 18.2%
• Z-score: 3.02 (p < 0.001)
BASELINE CALCULATION:
• Method: Farrington surveillance
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.8% annual
AGE-SPECIFIC EXCESS:
• 0-44 years: -3.7% (1,354 deaths)
• 45-64 years: 19.1% (3,385 deaths)
• 65-74 years: 26.9% (3,385 deaths)
• 75+ years: 39.0% (5,416 deaths)
CAUSE ATTRIBUTION:
• Direct (confirmed): 8,459 (51%)
• Indirect (probable): 2,301 (26%)
• Collateral (delayed care): 2,542 (18%)
STATISTICAL SIGNIFICANCE:
• 95% CI: [11,510, 15,573]
• Probability of chance: < 0.001
• Power: 0.98
Years of Life Lost: 200891
Economic Impact: $10.0 billion
Quality-Adjusted Life Years Lost: 150031 | 0.0.5 | null | null |
What is the mortality rate for Stroke in USA in 2024? | CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Stroke
Location: USA
Year: 2024
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 42.1 per 100,000 population
• Age-Adjusted Rate: 37.7 per 100,000
• Total Deaths: 530,365
• Percentage of All Deaths: 10.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 50.5 per 100,000
• Female Death Rate: 35.8 per 100,000
• Sex Ratio (M:F): 1.41:1
TREND ANALYSIS:
• 5-Year Change: -6.5%
• 10-Year Change: +5.1%
• Annual Percentage Change: +1.3%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #11
• Years of Potential Life Lost (YPLL): 9433414
• Economic Burden: $47.3 billion annually
• Preventable Deaths: 34%
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: Near-Complete (86% coverage) | cause_specific | Human: What is the mortality rate for Stroke in USA in 2024?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Stroke
Location: USA
Year: 2024
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 42.1 per 100,000 population
• Age-Adjusted Rate: 37.7 per 100,000
• Total Deaths: 530,365
• Percentage of All Deaths: 10.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 50.5 per 100,000
• Female Death Rate: 35.8 per 100,000
• Sex Ratio (M:F): 1.41:1
TREND ANALYSIS:
• 5-Year Change: -6.5%
• 10-Year Change: +5.1%
• Annual Percentage Change: +1.3%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #11
• Years of Potential Life Lost (YPLL): 9433414
• Economic Burden: $47.3 billion annually
• Preventable Deaths: 34%
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: Near-Complete (86% coverage) | 0.0.5 | null | null |
Calculate Term life insurance premium for 41 year old male, $100,000 coverage, 10 year term, Substandard rating | LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Term Life Insurance
• Face Amount: $100,000
• Term Length: 10 years
• Issue Age: 41
• Sex: Male
• Underwriting Class: Substandard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_41): 0.003474
• Underwriting Multiplier: 1.5x
• Product Load Factor: 1.0x
• Expense Loading: 15% of gross premium
• Commission Load: 64% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $208.42
• Expense Charge: $52.11
• Reserve Accumulation: $69.47
• Profit Margin: $17.37
• Gross Annual Premium: $347.37
PAYMENT OPTIONS:
• Annual: $347.37
• Semi-Annual: $180.63 (x2 = $361.27/year)
• Quarterly: $92.05 (x4 = $368.21/year)
• Monthly: $31.26 (x12 = $375.16/year)
RESERVE CALCULATIONS:
• Net Level Premium: $260.53
• First Year Reserve: $69.47
• Terminal Reserve (Year 10): $52698.85
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 10.1%
Profit Margin: 14.3%
Lapse Assumption: 5.8% annual
Illustration assumes guaranteed rates. Actual results may vary. | insurance_premium | Human: Calculate Term life insurance premium for 41 year old male, $100,000 coverage, 10 year term, Substandard rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Term Life Insurance
• Face Amount: $100,000
• Term Length: 10 years
• Issue Age: 41
• Sex: Male
• Underwriting Class: Substandard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_41): 0.003474
• Underwriting Multiplier: 1.5x
• Product Load Factor: 1.0x
• Expense Loading: 15% of gross premium
• Commission Load: 64% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $208.42
• Expense Charge: $52.11
• Reserve Accumulation: $69.47
• Profit Margin: $17.37
• Gross Annual Premium: $347.37
PAYMENT OPTIONS:
• Annual: $347.37
• Semi-Annual: $180.63 (x2 = $361.27/year)
• Quarterly: $92.05 (x4 = $368.21/year)
• Monthly: $31.26 (x12 = $375.16/year)
RESERVE CALCULATIONS:
• Net Level Premium: $260.53
• First Year Reserve: $69.47
• Terminal Reserve (Year 10): $52698.85
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 10.1%
Profit Margin: 14.3%
Lapse Assumption: 5.8% annual
Illustration assumes guaranteed rates. Actual results may vary. | 0.0.5 | null | null |
What is the occupational mortality rate for Transportation workers? | OCCUPATIONAL MORTALITY ANALYSIS
Industry: Transportation
Fatal Injury Rate: 122.7 per 100,000 full-time workers
Annual Deaths: 3,293
LEADING CAUSES:
• Falls: 33%
• Struck by object: 15%
• Electrocution: 5%
• Caught-in/between: 18%
Workers' compensation death benefit: $291,600 | occupational_mortality | Human: What is the occupational mortality rate for Transportation workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Transportation
Fatal Injury Rate: 122.7 per 100,000 full-time workers
Annual Deaths: 3,293
LEADING CAUSES:
• Falls: 33%
• Struck by object: 15%
• Electrocution: 5%
• Caught-in/between: 18%
Workers' compensation death benefit: $291,600 | 0.0.5 | null | null |
Analyze mortality impact of MERS | PANDEMIC MORTALITY ANALYSIS
Pandemic: MERS
Global Deaths: 959
Case Fatality Rate: 6.4%
Infection Fatality Rate: 1.74%
Age-specific mortality shows exponential increase with age.
Economic impact: $5.9 trillion globally. | pandemic_analysis | Human: Analyze mortality impact of MERS
Actuarial AI: PANDEMIC MORTALITY ANALYSIS
Pandemic: MERS
Global Deaths: 959
Case Fatality Rate: 6.4%
Infection Fatality Rate: 1.74%
Age-specific mortality shows exponential increase with age.
Economic impact: $5.9 trillion globally. | 0.0.5 | null | null |
Analyze mortality differences by education in the USA | DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Education
Country: USA
Analysis Period: 2023
MORTALITY RATES BY EDUCATION (per 100,000):
• Less than High School: 506.6
• High School: 1129.2
• Some College: 735.9
• Bachelor's: 658.5
• Graduate Degree: 919.9
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.80
• Rate Difference: 418.8 per 100,000
• Population Attributable Risk: 21.0%
• Gini Coefficient: 0.370
LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 74.8 years
• High School: 81.5 years
• Some College: 84.0 years
• Bachelor's: 75.4 years
• Graduate Degree: 82.5 years
CONTRIBUTING FACTORS:
• Healthcare Access: 38% of disparity
• Socioeconomic Status: 21% of disparity
• Environmental Factors: 11% of disparity
• Behavioral Factors: 17% of disparity
• Biological Factors: 10% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -1.4%
Social determinants explain 61% of observed mortality differences. | demographic_analysis | 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: 506.6
• High School: 1129.2
• Some College: 735.9
• Bachelor's: 658.5
• Graduate Degree: 919.9
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.80
• Rate Difference: 418.8 per 100,000
• Population Attributable Risk: 21.0%
• Gini Coefficient: 0.370
LIFE EXPECTANCY BY EDUCATION:
• Less than High School: 74.8 years
• High School: 81.5 years
• Some College: 84.0 years
• Bachelor's: 75.4 years
• Graduate Degree: 82.5 years
CONTRIBUTING FACTORS:
• Healthcare Access: 38% of disparity
• Socioeconomic Status: 21% of disparity
• Environmental Factors: 11% of disparity
• Behavioral Factors: 17% of disparity
• Biological Factors: 10% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -1.4%
Social determinants explain 61% of observed mortality differences. | 0.0.5 | null | null |
38. An insurance policy pays for a random loss X subject to a deductible of C, where | This is a multiple choice question. Let me analyze each option:
(A) 0.1
(B) 0.3
(C) 0.4
(D) 0.6
(E) 0.8
To solve this problem, we need to apply probability concepts and calculate the correct answer. | exam_p_pdf | Human: 38. An insurance policy pays for a random loss X subject to a deductible of C, where
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 0.1
(B) 0.3
(C) 0.4
(D) 0.6
(E) 0.8
To solve this problem, we need to apply probability concepts and calculate the correct answer. | 0.0.6 | P | edu-exam-p-sample-quest.pdf |
Perform mortality assumption review for pension plan | MORTALITY ASSUMPTION VALUATION
Product: Pension Plan
Valuation Date: 12/31/2023
CURRENT ASSUMPTIONS:
• Base Table: RP-2014
• Improvement Scale: MP-2021
• Experience Adjustment: 97%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.04
• Credibility Factor: 0.73
• Indicated Change: -7.5%
FINANCIAL IMPACT:
• Reserve Change: $-1.5 million
• Funded Ratio Impact: +1.2%
Recommendation: Maintain current assumptions | valuation | 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: RP-2014
• Improvement Scale: MP-2021
• Experience Adjustment: 97%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.04
• Credibility Factor: 0.73
• Indicated Change: -7.5%
FINANCIAL IMPACT:
• Reserve Change: $-1.5 million
• Funded Ratio Impact: +1.2%
Recommendation: Maintain current assumptions | 0.0.5 | null | null |
What is the life expectancy for a 12 year old male in France as of 2016? | ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: France
• Age: 12 years
• Sex: Male
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 12 (e_12): 67.8 years
• Expected Age at Death: 79.8 years
• Median Survival Time: 47.0 years
• Modal Age at Death: 74.8 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_12): 93.0%
• 10-Year Survival (₁₀p_12): 86.5%
• 20-Year Survival (₂₀p_12): 74.8%
MORTALITY METRICS:
• Force of Mortality (μ_12): 0.01454
• Probability of Death within 1 Year (q_12): 0.01444
• Hazard Rate: 0.01465
COMPARATIVE CONTEXT:
• Global Average at Age 12: 70.5 years
• Regional Rank: Top 50 globally
• Historical Trend: Stable
Based on 378,241 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.7%. | life_expectancy | Human: What is the life expectancy for a 12 year old male in France as of 2016?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: France
• Age: 12 years
• Sex: Male
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 12 (e_12): 67.8 years
• Expected Age at Death: 79.8 years
• Median Survival Time: 47.0 years
• Modal Age at Death: 74.8 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_12): 93.0%
• 10-Year Survival (₁₀p_12): 86.5%
• 20-Year Survival (₂₀p_12): 74.8%
MORTALITY METRICS:
• Force of Mortality (μ_12): 0.01454
• Probability of Death within 1 Year (q_12): 0.01444
• Hazard Rate: 0.01465
COMPARATIVE CONTEXT:
• Global Average at Age 12: 70.5 years
• Regional Rank: Top 50 globally
• Historical Trend: Stable
Based on 378,241 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.7%. | 0.0.5 | null | null |
What is the mortality rate for Parkinson's in Germany for 45-64 in 2020? | CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Parkinson's
Location: Germany
Year: 2020
Age Group: 45-64
MORTALITY STATISTICS:
• Crude Death Rate: 9.9 per 100,000 population
• Age-Adjusted Rate: 9.3 per 100,000
• Total Deaths: 70,646
• Percentage of All Deaths: 9.1%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 11.8 per 100,000
• Female Death Rate: 8.4 per 100,000
• Sex Ratio (M:F): 1.50:1
TREND ANALYSIS:
• 5-Year Change: -4.0%
• 10-Year Change: -5.6%
• Annual Percentage Change: +2.2%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #2
• Years of Potential Life Lost (YPLL): 2056839
• Economic Burden: $38.6 billion annually
• Preventable Deaths: 47%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): G20
Data Quality: Partial (94% coverage) | cause_specific | Human: What is the mortality rate for Parkinson's in Germany for 45-64 in 2020?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Parkinson's
Location: Germany
Year: 2020
Age Group: 45-64
MORTALITY STATISTICS:
• Crude Death Rate: 9.9 per 100,000 population
• Age-Adjusted Rate: 9.3 per 100,000
• Total Deaths: 70,646
• Percentage of All Deaths: 9.1%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 11.8 per 100,000
• Female Death Rate: 8.4 per 100,000
• Sex Ratio (M:F): 1.50:1
TREND ANALYSIS:
• 5-Year Change: -4.0%
• 10-Year Change: -5.6%
• Annual Percentage Change: +2.2%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #2
• Years of Potential Life Lost (YPLL): 2056839
• Economic Burden: $38.6 billion annually
• Preventable Deaths: 47%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): G20
Data Quality: Partial (94% coverage) | 0.0.5 | null | null |
Calculate mortality improvement factors for age 76 | MORTALITY IMPROVEMENT ANALYSIS
Age: 76
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.05%
• Current (2024): 2.18%
• Ultimate (2044+): 0.53%
PROJECTION FACTORS:
• 10-Year Factor: 0.8022
• 20-Year Factor: 0.6435
• 30-Year Factor: 0.5162
Cohort effect adjustment: Not applied
Gender-specific: No | mortality_improvement | Human: Calculate mortality improvement factors for age 76
Actuarial AI: MORTALITY IMPROVEMENT ANALYSIS
Age: 76
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.05%
• Current (2024): 2.18%
• Ultimate (2044+): 0.53%
PROJECTION FACTORS:
• 10-Year Factor: 0.8022
• 20-Year Factor: 0.6435
• 30-Year Factor: 0.5162
Cohort effect adjustment: Not applied
Gender-specific: No | 0.0.5 | null | null |
251. Two independent estimates are to be made on a building damaged by fire. Each estimate | This is a multiple choice question. Let me analyze each option:
(A) 0.023
(B) 0.100
(C) 0.115
(D) 0.221
(E) 0.444
To solve this problem, we need to apply probability concepts and calculate the correct answer. | exam_p_pdf | Human: 251. Two independent estimates are to be made on a building damaged by fire. Each estimate
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 0.023
(B) 0.100
(C) 0.115
(D) 0.221
(E) 0.444
To solve this problem, we need to apply probability concepts and calculate the correct answer. | 0.0.6 | P | edu-exam-p-sample-quest.pdf |
Calculate policy reserve for 30 year old, 20-year term life, year 10 | POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 20
• Current Age: 30
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1122.86
• Present Value Future Benefits (PVFB): $44509.29
• Present Value Future Premiums (PVFP): $34313.77
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $17829.59
• Per $1,000 Face: $178.30
PROSPECTIVE METHOD:
• A₁_30:10⌉ = 0.1863
• ä_30:10⌉ = 9.4282
• ₁₀V = 100,000 × A₁ - P × ä = $17829.59
RETROSPECTIVE METHOD:
• Accumulated Premiums: $11794.51
• Accumulated Cost of Insurance: $4570.67
• Interest Earned: $1015.51
• ₁₀V = $17829.59
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $16938.11
• Tax Reserve: $16403.22
• GAAP Reserve: $18721.07 | actuarial_calculation | Human: Calculate policy reserve for 30 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: 20
• Current Age: 30
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1122.86
• Present Value Future Benefits (PVFB): $44509.29
• Present Value Future Premiums (PVFP): $34313.77
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $17829.59
• Per $1,000 Face: $178.30
PROSPECTIVE METHOD:
• A₁_30:10⌉ = 0.1863
• ä_30:10⌉ = 9.4282
• ₁₀V = 100,000 × A₁ - P × ä = $17829.59
RETROSPECTIVE METHOD:
• Accumulated Premiums: $11794.51
• Accumulated Cost of Insurance: $4570.67
• Interest Earned: $1015.51
• ₁₀V = $17829.59
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $16938.11
• Tax Reserve: $16403.22
• GAAP Reserve: $18721.07 | 0.0.5 | null | null |
Calculate Universal Life life insurance premium for 70 year old female, $5,000,000 coverage, Preferred Plus rating | LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $5,000,000
• Duration: Lifetime Coverage
• Issue Age: 70
• Sex: Female
• Underwriting Class: Preferred Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_70): 0.002700
• Underwriting Multiplier: 0.6x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 69% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $22681.60
• Expense Charge: $5670.40
• Reserve Accumulation: $7560.53
• Profit Margin: $1890.13
• Gross Annual Premium: $37802.66
PAYMENT OPTIONS:
• Annual: $37802.66
• Semi-Annual: $19657.38 (x2 = $39314.77/year)
• Quarterly: $10017.70 (x4 = $40070.82/year)
• Monthly: $3402.24 (x12 = $40826.87/year)
RESERVE CALCULATIONS:
• Net Level Premium: $28351.99
• First Year Reserve: $7560.53
• Terminal Reserve (Year -5): $2949923.09
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 11.9%
Profit Margin: 10.7%
Lapse Assumption: 5.8% annual
Illustration assumes guaranteed rates. Actual results may vary. | insurance_premium | Human: Calculate Universal Life life insurance premium for 70 year old female, $5,000,000 coverage, Preferred Plus rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $5,000,000
• Duration: Lifetime Coverage
• Issue Age: 70
• Sex: Female
• Underwriting Class: Preferred Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_70): 0.002700
• Underwriting Multiplier: 0.6x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 69% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $22681.60
• Expense Charge: $5670.40
• Reserve Accumulation: $7560.53
• Profit Margin: $1890.13
• Gross Annual Premium: $37802.66
PAYMENT OPTIONS:
• Annual: $37802.66
• Semi-Annual: $19657.38 (x2 = $39314.77/year)
• Quarterly: $10017.70 (x4 = $40070.82/year)
• Monthly: $3402.24 (x12 = $40826.87/year)
RESERVE CALCULATIONS:
• Net Level Premium: $28351.99
• First Year Reserve: $7560.53
• Terminal Reserve (Year -5): $2949923.09
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 11.9%
Profit Margin: 10.7%
Lapse Assumption: 5.8% annual
Illustration assumes guaranteed rates. Actual results may vary. | 0.0.5 | null | null |
Show survival curve for China female in 2019 | SURVIVAL CURVE ANALYSIS
Population: China Female
Reference Year: 2019
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 2 0.00002 83.6
1 99,998 10 0.00010 79.3
5 99,988 26 0.00026 71.3
10 99,962 53 0.00053 73.5
20 99,909 88 0.00088 57.1
30 99,821 157 0.00157 52.9
40 99,664 270 0.00271 38.4
50 99,394 459 0.00462 27.5
60 98,935 574 0.00580 22.1
70 98,361 804 0.00817 11.3
80 97,557 1,212 0.01242 0.1
90 96,345 2,230 0.02315 3.5
100 94,115 3,071 0.03263 4.0
110 91,044 91,044 1.00000 1.2
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 83.3 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.9%
• Probability of Surviving to 80: 97.6%
CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.82
The survival curve follows Gompertz law after age 30.
Data sourced from 110,403 death certificates. | survival_curve | Human: Show survival curve for China female in 2019
Actuarial AI: SURVIVAL CURVE ANALYSIS
Population: China Female
Reference Year: 2019
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 2 0.00002 83.6
1 99,998 10 0.00010 79.3
5 99,988 26 0.00026 71.3
10 99,962 53 0.00053 73.5
20 99,909 88 0.00088 57.1
30 99,821 157 0.00157 52.9
40 99,664 270 0.00271 38.4
50 99,394 459 0.00462 27.5
60 98,935 574 0.00580 22.1
70 98,361 804 0.00817 11.3
80 97,557 1,212 0.01242 0.1
90 96,345 2,230 0.02315 3.5
100 94,115 3,071 0.03263 4.0
110 91,044 91,044 1.00000 1.2
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 83.3 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.9%
• Probability of Surviving to 80: 97.6%
CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.82
The survival curve follows Gompertz law after age 30.
Data sourced from 110,403 death certificates. | 0.0.5 | null | null |
What is the life expectancy for a 100 year old both in Germany as of 2016? | ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 100 years
• Sex: Both
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 100 (e_100): 0.0 years
• Expected Age at Death: 100.0 years
• Median Survival Time: 0.0 years
• Modal Age at Death: 95.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_100): 0.7%
• 10-Year Survival (₁₀p_100): 0.0%
• 20-Year Survival (₂₀p_100): 0.0%
MORTALITY METRICS:
• Force of Mortality (μ_100): 1.00000
• Probability of Death within 1 Year (q_100): 0.63212
• Hazard Rate: 4.60517
COMPARATIVE CONTEXT:
• Global Average at Age 100: -18.8 years
• Regional Rank: Top 16 globally
• Historical Trend: Stable
Based on 447,730 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.1%. | life_expectancy | Human: What is the life expectancy for a 100 year old both in Germany as of 2016?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 100 years
• Sex: Both
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 100 (e_100): 0.0 years
• Expected Age at Death: 100.0 years
• Median Survival Time: 0.0 years
• Modal Age at Death: 95.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_100): 0.7%
• 10-Year Survival (₁₀p_100): 0.0%
• 20-Year Survival (₂₀p_100): 0.0%
MORTALITY METRICS:
• Force of Mortality (μ_100): 1.00000
• Probability of Death within 1 Year (q_100): 0.63212
• Hazard Rate: 4.60517
COMPARATIVE CONTEXT:
• Global Average at Age 100: -18.8 years
• Regional Rank: Top 16 globally
• Historical Trend: Stable
Based on 447,730 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.1%. | 0.0.5 | null | null |
Calculate Universal Life life insurance premium for 44 year old female, $500,000 coverage, Preferred Plus rating | LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 44
• Sex: Female
• Underwriting Class: Preferred Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_44): 0.001135
• Underwriting Multiplier: 0.6x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 65% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $953.42
• Expense Charge: $238.36
• Reserve Accumulation: $317.81
• Profit Margin: $79.45
• Gross Annual Premium: $1589.04
PAYMENT OPTIONS:
• Annual: $1589.04
• Semi-Annual: $826.30 (x2 = $1652.60/year)
• Quarterly: $421.09 (x4 = $1684.38/year)
• Monthly: $143.01 (x12 = $1716.16/year)
RESERVE CALCULATIONS:
• Net Level Premium: $1191.78
• First Year Reserve: $317.81
• Terminal Reserve (Year 21): $243488.05
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 11.1%
Profit Margin: 10.8%
Lapse Assumption: 4.3% annual
Illustration assumes guaranteed rates. Actual results may vary. | insurance_premium | Human: Calculate Universal Life life insurance premium for 44 year old female, $500,000 coverage, Preferred Plus rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 44
• Sex: Female
• Underwriting Class: Preferred Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_44): 0.001135
• Underwriting Multiplier: 0.6x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 65% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $953.42
• Expense Charge: $238.36
• Reserve Accumulation: $317.81
• Profit Margin: $79.45
• Gross Annual Premium: $1589.04
PAYMENT OPTIONS:
• Annual: $1589.04
• Semi-Annual: $826.30 (x2 = $1652.60/year)
• Quarterly: $421.09 (x4 = $1684.38/year)
• Monthly: $143.01 (x12 = $1716.16/year)
RESERVE CALCULATIONS:
• Net Level Premium: $1191.78
• First Year Reserve: $317.81
• Terminal Reserve (Year 21): $243488.05
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 11.1%
Profit Margin: 10.8%
Lapse Assumption: 4.3% annual
Illustration assumes guaranteed rates. Actual results may vary. | 0.0.5 | null | null |
Analyze mortality patterns for 1936 birth cohort | BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1936
Current Age: 88 years
Cohort Size at Birth: 3,763,988
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 65.9 years
• Current Life Expectancy: 80.2 years
• Survival to Current Age: 71.8%
HISTORICAL EXPOSURES:
• Standard exposures
MORTALITY PATTERN:
• Peak Infant Mortality: 29.3 per 1,000
• Current Mortality Rate: 24.6 per 1,000
• Improvement Since Birth: 36%
Cohort effects explain 22% of mortality variation. | cohort_analysis | Human: Analyze mortality patterns for 1936 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1936
Current Age: 88 years
Cohort Size at Birth: 3,763,988
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 65.9 years
• Current Life Expectancy: 80.2 years
• Survival to Current Age: 71.8%
HISTORICAL EXPOSURES:
• Standard exposures
MORTALITY PATTERN:
• Peak Infant Mortality: 29.3 per 1,000
• Current Mortality Rate: 24.6 per 1,000
• Improvement Since Birth: 36%
Cohort effects explain 22% of mortality variation. | 0.0.5 | null | null |
What is the mortality rate for Liver Disease in Australia for 75+ in 2024? | CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: Australia
Year: 2024
Age Group: 75+
MORTALITY STATISTICS:
• Crude Death Rate: 11.0 per 100,000 population
• Age-Adjusted Rate: 10.1 per 100,000
• Total Deaths: 371,130
• Percentage of All Deaths: 3.4%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 13.3 per 100,000
• Female Death Rate: 9.4 per 100,000
• Sex Ratio (M:F): 1.43:1
TREND ANALYSIS:
• 5-Year Change: +5.8%
• 10-Year Change: -22.7%
• Annual Percentage Change: +0.5%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #10
• Years of Potential Life Lost (YPLL): 5875267
• Economic Burden: $50.6 billion annually
• Preventable Deaths: 46%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Near-Complete (93% coverage) | cause_specific | Human: What is the mortality rate for Liver Disease in Australia for 75+ in 2024?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: Australia
Year: 2024
Age Group: 75+
MORTALITY STATISTICS:
• Crude Death Rate: 11.0 per 100,000 population
• Age-Adjusted Rate: 10.1 per 100,000
• Total Deaths: 371,130
• Percentage of All Deaths: 3.4%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 13.3 per 100,000
• Female Death Rate: 9.4 per 100,000
• Sex Ratio (M:F): 1.43:1
TREND ANALYSIS:
• 5-Year Change: +5.8%
• 10-Year Change: -22.7%
• Annual Percentage Change: +0.5%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #10
• Years of Potential Life Lost (YPLL): 5875267
• Economic Burden: $50.6 billion annually
• Preventable Deaths: 46%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Near-Complete (93% coverage) | 0.0.5 | null | null |
What is the life expectancy for a 78 year old both in Germany as of 2016? | ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 78 years
• Sex: Both
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 78 (e_78): 2.0 years
• Expected Age at Death: 80.0 years
• Median Survival Time: 1.4 years
• Modal Age at Death: 75.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_78): 19.3%
• 10-Year Survival (₁₀p_78): 3.7%
• 20-Year Survival (₂₀p_78): 0.1%
MORTALITY METRICS:
• Force of Mortality (μ_78): 0.32911
• Probability of Death within 1 Year (q_78): 0.28044
• Hazard Rate: 0.39916
COMPARATIVE CONTEXT:
• Global Average at Age 78: 3.2 years
• Regional Rank: Top 49 globally
• Historical Trend: Improving
Based on 412,084 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.6%. | life_expectancy | Human: What is the life expectancy for a 78 year old both in Germany as of 2016?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 78 years
• Sex: Both
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 78 (e_78): 2.0 years
• Expected Age at Death: 80.0 years
• Median Survival Time: 1.4 years
• Modal Age at Death: 75.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_78): 19.3%
• 10-Year Survival (₁₀p_78): 3.7%
• 20-Year Survival (₂₀p_78): 0.1%
MORTALITY METRICS:
• Force of Mortality (μ_78): 0.32911
• Probability of Death within 1 Year (q_78): 0.28044
• Hazard Rate: 0.39916
COMPARATIVE CONTEXT:
• Global Average at Age 78: 3.2 years
• Regional Rank: Top 49 globally
• Historical Trend: Improving
Based on 412,084 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.6%. | 0.0.5 | null | null |
What is the mortality rate for Suicide in France for 25-44 in 2019? | CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Suicide
Location: France
Year: 2019
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 14.6 per 100,000 population
• Age-Adjusted Rate: 13.2 per 100,000
• Total Deaths: 379,613
• Percentage of All Deaths: 6.5%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 17.5 per 100,000
• Female Death Rate: 12.4 per 100,000
• Sex Ratio (M:F): 1.40:1
TREND ANALYSIS:
• 5-Year Change: -3.5%
• 10-Year Change: +10.0%
• Annual Percentage Change: -2.2%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 5963791
• Economic Burden: $52.9 billion annually
• Preventable Deaths: 21%
RISK FACTORS:
• Mental illness: 90% of cases
• Substance abuse: 30%
• Previous attempt: 40x risk
• Access to means: Critical
• Social isolation: 25%
International Classification of Diseases (ICD-10): X60-X84
Data Quality: Near-Complete (86% coverage) | cause_specific | Human: What is the mortality rate for Suicide in France for 25-44 in 2019?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Suicide
Location: France
Year: 2019
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 14.6 per 100,000 population
• Age-Adjusted Rate: 13.2 per 100,000
• Total Deaths: 379,613
• Percentage of All Deaths: 6.5%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 17.5 per 100,000
• Female Death Rate: 12.4 per 100,000
• Sex Ratio (M:F): 1.40:1
TREND ANALYSIS:
• 5-Year Change: -3.5%
• 10-Year Change: +10.0%
• Annual Percentage Change: -2.2%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 5963791
• Economic Burden: $52.9 billion annually
• Preventable Deaths: 21%
RISK FACTORS:
• Mental illness: 90% of cases
• Substance abuse: 30%
• Previous attempt: 40x risk
• Access to means: Critical
• Social isolation: 25%
International Classification of Diseases (ICD-10): X60-X84
Data Quality: Near-Complete (86% coverage) | 0.0.5 | null | null |
Calculate policy reserve for 55 year old, 20-year term life, year 10 | POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 45
• Current Age: 55
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $721.36
• Present Value Future Benefits (PVFB): $50693.61
• Present Value Future Premiums (PVFP): $27357.78
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $21296.73
• Per $1,000 Face: $212.97
PROSPECTIVE METHOD:
• A₁_55:10⌉ = 0.1622
• ä_55:10⌉ = 9.8442
• ₁₀V = 100,000 × A₁ - P × ä = $21296.73
RETROSPECTIVE METHOD:
• Accumulated Premiums: $10508.46
• Accumulated Cost of Insurance: $5167.96
• Interest Earned: $1120.97
• ₁₀V = $21296.73
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $20231.90
• Tax Reserve: $19593.00
• GAAP Reserve: $22361.57 | actuarial_calculation | Human: Calculate policy reserve for 55 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: 45
• Current Age: 55
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $721.36
• Present Value Future Benefits (PVFB): $50693.61
• Present Value Future Premiums (PVFP): $27357.78
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $21296.73
• Per $1,000 Face: $212.97
PROSPECTIVE METHOD:
• A₁_55:10⌉ = 0.1622
• ä_55:10⌉ = 9.8442
• ₁₀V = 100,000 × A₁ - P × ä = $21296.73
RETROSPECTIVE METHOD:
• Accumulated Premiums: $10508.46
• Accumulated Cost of Insurance: $5167.96
• Interest Earned: $1120.97
• ₁₀V = $21296.73
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $20231.90
• Tax Reserve: $19593.00
• GAAP Reserve: $22361.57 | 0.0.5 | null | null |
What is the mortality rate for Liver Disease in Germany for 75+ in 2023? | CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: Germany
Year: 2023
Age Group: 75+
MORTALITY STATISTICS:
• Crude Death Rate: 9.9 per 100,000 population
• Age-Adjusted Rate: 8.5 per 100,000
• Total Deaths: 453,206
• Percentage of All Deaths: 14.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 11.8 per 100,000
• Female Death Rate: 8.4 per 100,000
• Sex Ratio (M:F): 1.39:1
TREND ANALYSIS:
• 5-Year Change: +14.2%
• 10-Year Change: -5.5%
• Annual Percentage Change: -1.9%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #14
• Years of Potential Life Lost (YPLL): 12576854
• Economic Burden: $17.2 billion annually
• Preventable Deaths: 48%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Near-Complete (86% coverage) | cause_specific | Human: What is the mortality rate for Liver Disease in Germany for 75+ in 2023?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: Germany
Year: 2023
Age Group: 75+
MORTALITY STATISTICS:
• Crude Death Rate: 9.9 per 100,000 population
• Age-Adjusted Rate: 8.5 per 100,000
• Total Deaths: 453,206
• Percentage of All Deaths: 14.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 11.8 per 100,000
• Female Death Rate: 8.4 per 100,000
• Sex Ratio (M:F): 1.39:1
TREND ANALYSIS:
• 5-Year Change: +14.2%
• 10-Year Change: -5.5%
• Annual Percentage Change: -1.9%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #14
• Years of Potential Life Lost (YPLL): 12576854
• Economic Burden: $17.2 billion annually
• Preventable Deaths: 48%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Near-Complete (86% coverage) | 0.0.5 | null | null |
Compare infant mortality between UK, Mexico and Brazil | INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: UK, Mexico, Brazil
Reference Year: 2021
COMPARATIVE STATISTICS:
• UK: 3.8 per 1,000 live births
• Mexico: 28.7 per 1,000 live births
• Brazil: 14.9 per 1,000 live births
RANKINGS:
1. UK: 3.8
2. Brazil: 14.9
3. Mexico: 28.7
STATISTICAL ANALYSIS:
• Range: 25.0
• Mean: 15.8
• Median: 14.9
• Standard Deviation: 10.2
• Coefficient of Variation: 64.6%
RELATIVE COMPARISONS:
• Best vs Worst: 7.61x difference
• Above Average: 1/3
• Global Ranking: UK: #103, Mexico: #147, Brazil: #17
CONTRIBUTING FACTORS:
• Healthcare System: 37% of variation
• Economic Development: 23% of variation
• Public Health Policy: 11% of variation
• Demographics: 18% of variation
• Environmental Factors: 12% of variation
Convergence/Divergence: Diverging at 1.4% annually | comparison | Human: Compare infant mortality between UK, Mexico and Brazil
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: UK, Mexico, Brazil
Reference Year: 2021
COMPARATIVE STATISTICS:
• UK: 3.8 per 1,000 live births
• Mexico: 28.7 per 1,000 live births
• Brazil: 14.9 per 1,000 live births
RANKINGS:
1. UK: 3.8
2. Brazil: 14.9
3. Mexico: 28.7
STATISTICAL ANALYSIS:
• Range: 25.0
• Mean: 15.8
• Median: 14.9
• Standard Deviation: 10.2
• Coefficient of Variation: 64.6%
RELATIVE COMPARISONS:
• Best vs Worst: 7.61x difference
• Above Average: 1/3
• Global Ranking: UK: #103, Mexico: #147, Brazil: #17
CONTRIBUTING FACTORS:
• Healthcare System: 37% of variation
• Economic Development: 23% of variation
• Public Health Policy: 11% of variation
• Demographics: 18% of variation
• Environmental Factors: 12% of variation
Convergence/Divergence: Diverging at 1.4% annually | 0.0.5 | null | null |
Perform mortality assumption review for life insurance portfolio | MORTALITY ASSUMPTION VALUATION
Product: Life Insurance Portfolio
Valuation Date: 12/31/2024
CURRENT ASSUMPTIONS:
• Base Table: Pub-2010
• Improvement Scale: MP-2019
• Experience Adjustment: 86%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.08
• Credibility Factor: 0.84
• Indicated Change: +3.4%
FINANCIAL IMPACT:
• Reserve Change: $-1.8 million
• Funded Ratio Impact: +1.4%
Recommendation: Maintain current assumptions | valuation | Human: Perform mortality assumption review for life insurance portfolio
Actuarial AI: MORTALITY ASSUMPTION VALUATION
Product: Life Insurance Portfolio
Valuation Date: 12/31/2024
CURRENT ASSUMPTIONS:
• Base Table: Pub-2010
• Improvement Scale: MP-2019
• Experience Adjustment: 86%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.08
• Credibility Factor: 0.84
• Indicated Change: +3.4%
FINANCIAL IMPACT:
• Reserve Change: $-1.8 million
• Funded Ratio Impact: +1.4%
Recommendation: Maintain current assumptions | 0.0.5 | null | null |
What is the occupational mortality rate for Construction workers? | OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 88.9 per 100,000 full-time workers
Annual Deaths: 4,361
LEADING CAUSES:
• Falls: 38%
• Struck by object: 21%
• Electrocution: 10%
• Caught-in/between: 16%
Workers' compensation death benefit: $278,174 | occupational_mortality | Human: What is the occupational mortality rate for Construction workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 88.9 per 100,000 full-time workers
Annual Deaths: 4,361
LEADING CAUSES:
• Falls: 38%
• Struck by object: 21%
• Electrocution: 10%
• Caught-in/between: 16%
Workers' compensation death benefit: $278,174 | 0.0.5 | null | null |
Analyze mortality trends in Canada from 2005-2022 | MORTALITY TREND ANALYSIS
Country: Canada
Analysis Period: 2005-2022
OVERALL TRENDS:
• Average Annual Change: +0.6%
• Total Change: -16.9%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001
Life expectancy increased by 1.8 years.
Age-standardized death rate changed by +72 per 100,000.
KEY DRIVERS:
• Medical advances: 33% of improvement
• Public health measures: 24%
• Lifestyle changes: +15%
• Environmental factors: +12% | trend_analysis | Human: Analyze mortality trends in Canada from 2005-2022
Actuarial AI: MORTALITY TREND ANALYSIS
Country: Canada
Analysis Period: 2005-2022
OVERALL TRENDS:
• Average Annual Change: +0.6%
• Total Change: -16.9%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001
Life expectancy increased by 1.8 years.
Age-standardized death rate changed by +72 per 100,000.
KEY DRIVERS:
• Medical advances: 33% of improvement
• Public health measures: 24%
• Lifestyle changes: +15%
• Environmental factors: +12% | 0.0.5 | null | null |
Analyze mortality trends in Germany from 2004-2024 | MORTALITY TREND ANALYSIS
Country: Germany
Analysis Period: 2004-2024
OVERALL TRENDS:
• Average Annual Change: +0.7%
• Total Change: +14.0%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001
Life expectancy increased by 0.6 years.
Age-standardized death rate changed by +160 per 100,000.
KEY DRIVERS:
• Medical advances: 25% of improvement
• Public health measures: 15%
• Lifestyle changes: -24%
• Environmental factors: +8% | trend_analysis | Human: Analyze mortality trends in Germany from 2004-2024
Actuarial AI: MORTALITY TREND ANALYSIS
Country: Germany
Analysis Period: 2004-2024
OVERALL TRENDS:
• Average Annual Change: +0.7%
• Total Change: +14.0%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001
Life expectancy increased by 0.6 years.
Age-standardized death rate changed by +160 per 100,000.
KEY DRIVERS:
• Medical advances: 25% of improvement
• Public health measures: 15%
• Lifestyle changes: -24%
• Environmental factors: +8% | 0.0.5 | null | null |
Compare cancer mortality between China, Russia and Canada | INTERNATIONAL MORTALITY COMPARISON
Metric: Cancer Mortality
Countries: China, Russia, Canada
Reference Year: 2023
COMPARATIVE STATISTICS:
• China: 139.1 per 100,000 population
• Russia: 115.7 per 100,000 population
• Canada: 114.9 per 100,000 population
RANKINGS:
1. Canada: 114.9
2. Russia: 115.7
3. China: 139.1
STATISTICAL ANALYSIS:
• Range: 24.2
• Mean: 123.2
• Median: 115.7
• Standard Deviation: 11.2
• Coefficient of Variation: 9.1%
RELATIVE COMPARISONS:
• Best vs Worst: 1.21x difference
• Above Average: 1/3
• Global Ranking: China: #120, Russia: #92, Canada: #88
CONTRIBUTING FACTORS:
• Healthcare System: 39% of variation
• Economic Development: 20% of variation
• Public Health Policy: 23% of variation
• Demographics: 16% of variation
• Environmental Factors: 8% of variation
Convergence/Divergence: Diverging at 0.7% annually | comparison | Human: Compare cancer mortality between China, Russia and Canada
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Cancer Mortality
Countries: China, Russia, Canada
Reference Year: 2023
COMPARATIVE STATISTICS:
• China: 139.1 per 100,000 population
• Russia: 115.7 per 100,000 population
• Canada: 114.9 per 100,000 population
RANKINGS:
1. Canada: 114.9
2. Russia: 115.7
3. China: 139.1
STATISTICAL ANALYSIS:
• Range: 24.2
• Mean: 123.2
• Median: 115.7
• Standard Deviation: 11.2
• Coefficient of Variation: 9.1%
RELATIVE COMPARISONS:
• Best vs Worst: 1.21x difference
• Above Average: 1/3
• Global Ranking: China: #120, Russia: #92, Canada: #88
CONTRIBUTING FACTORS:
• Healthcare System: 39% of variation
• Economic Development: 20% of variation
• Public Health Policy: 23% of variation
• Demographics: 16% of variation
• Environmental Factors: 8% of variation
Convergence/Divergence: Diverging at 0.7% annually | 0.0.5 | null | null |
Analyze mortality patterns for 1928 birth cohort | BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1928
Current Age: 96 years
Cohort Size at Birth: 2,752,867
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 71.5 years
• Current Life Expectancy: 83.5 years
• Survival to Current Age: 63.7%
HISTORICAL EXPOSURES:
• Great Depression impact
MORTALITY PATTERN:
• Peak Infant Mortality: 32.5 per 1,000
• Current Mortality Rate: 33.1 per 1,000
• Improvement Since Birth: 38%
Cohort effects explain 28% of mortality variation. | cohort_analysis | Human: Analyze mortality patterns for 1928 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1928
Current Age: 96 years
Cohort Size at Birth: 2,752,867
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 71.5 years
• Current Life Expectancy: 83.5 years
• Survival to Current Age: 63.7%
HISTORICAL EXPOSURES:
• Great Depression impact
MORTALITY PATTERN:
• Peak Infant Mortality: 32.5 per 1,000
• Current Mortality Rate: 33.1 per 1,000
• Improvement Since Birth: 38%
Cohort effects explain 28% of mortality variation. | 0.0.5 | null | null |
Calculate Term life insurance premium for 57 year old female, $250,000 coverage, 20 year term, Preferred Plus rating | LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Term Life Insurance
• Face Amount: $250,000
• Term Length: 20 years
• Issue Age: 57
• Sex: Female
• Underwriting Class: Preferred Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_57): 0.001751
• Underwriting Multiplier: 0.6x
• Product Load Factor: 1.0x
• Expense Loading: 15% of gross premium
• Commission Load: 91% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $262.60
• Expense Charge: $65.65
• Reserve Accumulation: $87.53
• Profit Margin: $21.88
• Gross Annual Premium: $437.66
PAYMENT OPTIONS:
• Annual: $437.66
• Semi-Annual: $227.58 (x2 = $455.17/year)
• Quarterly: $115.98 (x4 = $463.92/year)
• Monthly: $39.39 (x12 = $472.68/year)
RESERVE CALCULATIONS:
• Net Level Premium: $328.25
• First Year Reserve: $87.53
• Terminal Reserve (Year 20): $122299.34
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 10.0%
Profit Margin: 10.6%
Lapse Assumption: 4.2% annual
Illustration assumes guaranteed rates. Actual results may vary. | insurance_premium | Human: Calculate Term life insurance premium for 57 year old female, $250,000 coverage, 20 year term, Preferred Plus rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Term Life Insurance
• Face Amount: $250,000
• Term Length: 20 years
• Issue Age: 57
• Sex: Female
• Underwriting Class: Preferred Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_57): 0.001751
• Underwriting Multiplier: 0.6x
• Product Load Factor: 1.0x
• Expense Loading: 15% of gross premium
• Commission Load: 91% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $262.60
• Expense Charge: $65.65
• Reserve Accumulation: $87.53
• Profit Margin: $21.88
• Gross Annual Premium: $437.66
PAYMENT OPTIONS:
• Annual: $437.66
• Semi-Annual: $227.58 (x2 = $455.17/year)
• Quarterly: $115.98 (x4 = $463.92/year)
• Monthly: $39.39 (x12 = $472.68/year)
RESERVE CALCULATIONS:
• Net Level Premium: $328.25
• First Year Reserve: $87.53
• Terminal Reserve (Year 20): $122299.34
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 10.0%
Profit Margin: 10.6%
Lapse Assumption: 4.2% annual
Illustration assumes guaranteed rates. Actual results may vary. | 0.0.5 | null | null |
Perform mortality assumption review for life insurance portfolio | MORTALITY ASSUMPTION VALUATION
Product: Life Insurance Portfolio
Valuation Date: 12/31/2023
CURRENT ASSUMPTIONS:
• Base Table: Pri-2012
• Improvement Scale: MP-2021
• Experience Adjustment: 114%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.01
• Credibility Factor: 0.94
• Indicated Change: -3.9%
FINANCIAL IMPACT:
• Reserve Change: $4.5 million
• Funded Ratio Impact: -1.2%
Recommendation: Maintain current assumptions | valuation | 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: Pri-2012
• Improvement Scale: MP-2021
• Experience Adjustment: 114%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 1.01
• Credibility Factor: 0.94
• Indicated Change: -3.9%
FINANCIAL IMPACT:
• Reserve Change: $4.5 million
• Funded Ratio Impact: -1.2%
Recommendation: Maintain current assumptions | 0.0.5 | null | null |
What is the life expectancy for a 14 year old female in Canada as of 2023? | ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Canada
• Age: 14 years
• Sex: Female
• Reference Year: 2023
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 14 (e_14): 73.3 years
• Expected Age at Death: 87.3 years
• Median Survival Time: 50.8 years
• Modal Age at Death: 82.3 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_14): 93.5%
• 10-Year Survival (₁₀p_14): 87.4%
• 20-Year Survival (₂₀p_14): 76.4%
MORTALITY METRICS:
• Force of Mortality (μ_14): 0.01346
• Probability of Death within 1 Year (q_14): 0.01337
• Hazard Rate: 0.01355
COMPARATIVE CONTEXT:
• Global Average at Age 14: 68.1 years
• Regional Rank: Top 40 globally
• Historical Trend: Stable
Based on 340,394 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.8%. | life_expectancy | Human: What is the life expectancy for a 14 year old female in Canada as of 2023?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Canada
• Age: 14 years
• Sex: Female
• Reference Year: 2023
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 14 (e_14): 73.3 years
• Expected Age at Death: 87.3 years
• Median Survival Time: 50.8 years
• Modal Age at Death: 82.3 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_14): 93.5%
• 10-Year Survival (₁₀p_14): 87.4%
• 20-Year Survival (₂₀p_14): 76.4%
MORTALITY METRICS:
• Force of Mortality (μ_14): 0.01346
• Probability of Death within 1 Year (q_14): 0.01337
• Hazard Rate: 0.01355
COMPARATIVE CONTEXT:
• Global Average at Age 14: 68.1 years
• Regional Rank: Top 40 globally
• Historical Trend: Stable
Based on 340,394 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.8%. | 0.0.5 | null | null |
344. Let X be a random variable with probability density function | This is a multiple choice question. Let me analyze each option:
(A) 0.019
(B) 0.030
(C) 0.056
(D) 0.500
(E) 0.714
To solve this problem, we need to apply probability concepts and calculate the correct answer. | exam_p_pdf | Human: 344. Let X be a random variable with probability density function
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 0.019
(B) 0.030
(C) 0.056
(D) 0.500
(E) 0.714
To solve this problem, we need to apply probability concepts and calculate the correct answer. | 0.0.6 | P | edu-exam-p-sample-quest.pdf |
What is the life expectancy for a 29 year old both in France as of 2016? | ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: France
• Age: 29 years
• Sex: Both
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 29 (e_29): 51.8 years
• Expected Age at Death: 80.8 years
• Median Survival Time: 35.9 years
• Modal Age at Death: 75.8 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_29): 91.0%
• 10-Year Survival (₁₀p_29): 82.8%
• 20-Year Survival (₂₀p_29): 68.5%
MORTALITY METRICS:
• Force of Mortality (μ_29): 0.01892
• Probability of Death within 1 Year (q_29): 0.01875
• Hazard Rate: 0.01911
COMPARATIVE CONTEXT:
• Global Average at Age 29: 53.5 years
• Regional Rank: Top 19 globally
• Historical Trend: Improving
Based on 177,466 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.7%. | life_expectancy | Human: What is the life expectancy for a 29 year old both in France as of 2016?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: France
• Age: 29 years
• Sex: Both
• Reference Year: 2016
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 29 (e_29): 51.8 years
• Expected Age at Death: 80.8 years
• Median Survival Time: 35.9 years
• Modal Age at Death: 75.8 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_29): 91.0%
• 10-Year Survival (₁₀p_29): 82.8%
• 20-Year Survival (₂₀p_29): 68.5%
MORTALITY METRICS:
• Force of Mortality (μ_29): 0.01892
• Probability of Death within 1 Year (q_29): 0.01875
• Hazard Rate: 0.01911
COMPARATIVE CONTEXT:
• Global Average at Age 29: 53.5 years
• Regional Rank: Top 19 globally
• Historical Trend: Improving
Based on 177,466 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.7%. | 0.0.5 | null | null |
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