원클릭으로 Manus에서 모든 스킬 실행

actuarial-modeling

스타58

포크19

업데이트2026년 5월 18일 09:06

Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards. USE THIS SKILL WHEN: - You need to review or audit actuarial models (reserving, pricing, capital) - Someone asks about loss triangle analysis or reserve adequacy - You are evaluating IBNR calculations, chain ladder methods, or Bornhuetter-Ferguson - A project involves insurance pricing, GLM rating models, or ratemaking - You need to assess Solvency II SCR calculations or RBC compliance - Someone mentions actuarial opinions, ASOP compliance, or SOA standards - You are reviewing stochastic models, ESG configurations, or DFA frameworks - A codebase uses actuarial libraries (chainladder, lifetables, ChainLadder R package) TRIGGER PHRASES: "actuarial", "loss reserving", "IBNR", "chain ladder", "premium pricing", "mortality table", "Solvency II", "capital adequacy", "ratemaking", "GLM pricing", "risk-based capital", "re

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

Manus에서 실행

출처

FDU-INS

FDU-INS/Insurance-Skills

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

============================================================ PHASE 1: ACTUARIAL SYSTEM DISCOVERY

Step 1.1 -- Technology Stack Detection

Identify actuarial platforms by scanning for these markers:

*.sas / SAS configs -> SAS-based actuarial models (reserving, pricing)
requirements.txt with chainladder, lifetables -> Python actuarial libraries
*.r / *.R with ChainLadder, actuar -> R actuarial packages
*.xlsx / VBA modules -> Excel-based actuarial workbooks
pom.xml with actuarial references -> Java-based platforms (Willis Towers Watson, Moody's)
Vendor platforms: ResQ, Arius, ICRFS, Igloo, Prophet, MoSes, AXIS
Database schemas with triangle/development tables -> Loss reserving data
Configuration for ESG (Economic Scenario Generator) -> Stochastic modeling

Step 1.2 -- Model Inventory

Catalog every actuarial model found. For each model, record:

Model type (loss reserving, pricing, life valuation, capital, catastrophe, reinsurance)
Risk classification (materiality: high/medium/low, complexity, frequency of use)
Owner and last review date (from comments, git history, or documentation)
Input data sources and output consumers

Step 1.3 -- Data Infrastructure

Map actuarial data sources:

Loss development triangles (paid, incurred, reported, closed)
Exposure and premium data (earned, written, in-force)
Mortality/morbidity tables (SOA tables, company-specific experience)
Economic assumptions (interest rates, inflation, yield curves)
Industry benchmarks (ISO, NCCI, AM Best aggregates)
Experience studies (lapse, mortality, morbidity, disability)

============================================================ PHASE 2: LOSS RESERVING ANALYSIS

Step 2.1 -- Reserving Methodology

For each reserving model, determine the method and assess appropriateness:

Chain Ladder (paid and incurred development) -- check for stability of development factors
Bornhuetter-Ferguson (expected loss ratio method) -- check ELR source and reasonableness
Cape Cod (Stanard-Buhlmann) -- verify weighting methodology
Generalized linear models for development patterns -- check model fit
Individual claim-level reserving (case reserves + IBNR) -- verify completeness
Frequency-severity methods -- check independence assumption
Berquist-Sherman adjustments -- verify adjustment rationale

Decision criteria: Flag any model using a single method without cross-validation against alternatives.

Step 2.2 -- Triangle Analysis

Assess loss development data quality:

Triangle construction: verify accident year/quarter, development period, evaluation date alignment
Data segmentation: confirm line of business, coverage, claim type, state splits are appropriate
Development factor selection: compare volume-weighted, simple average, medial, optimal selections
Tail factor selection: verify methodology is documented and reasonable
Diagonal effects: check for calendar year trends that distort development
Outlier identification: confirm treatment is documented and consistent

Step 2.3 -- Reserve Adequacy

Evaluate reserve quality against these benchmarks:

Actual vs. expected analysis (reserve runoff testing) -- flag if AVE ratio deviates > 5% for 2+ years
Reserve range estimation -- verify point estimate, low, high, and percentile ranges exist
Discount rate application -- confirm methodology matches regulatory requirements
Salvage and subrogation offsets -- verify they are not double-counted
ULAE/ALAE reserve calculations -- check allocation methodology
Actuarial opinion documentation -- verify NAIC Statement of Actuarial Opinion compliance
ASOP compliance -- check ASOP 36, 43 (P&C) and ASOP 25 (health)

============================================================ PHASE 3: PREMIUM PRICING METHODOLOGY

Step 3.1 -- Ratemaking Process

Evaluate the pricing pipeline end to end:

Pure premium vs. loss ratio approach -- confirm appropriate for the data volume
Loss trend analysis -- verify frequency, severity, and mix shift trends are separated
Loss development to ultimate -- confirm consistency with reserving ultimates
Expense loading -- verify fixed, variable, profit, and contingency loads
Credibility weighting -- check method (classical, Buhlmann, Buhlmann-Straub) and minimum thresholds
Rate level history -- verify on-level adjustments are complete and accurate
Indicated rate change -- confirm calculation ties to exhibits

Step 3.2 -- GLM Rating Models

If GLMs are used for pricing, assess each model for:

Distribution selection appropriateness (Tweedie, Poisson-Gamma, Logistic)
Link function selection with justification
Variable selection -- check for multicollinearity and interaction terms
Model fit statistics (deviance, AIC, BIC, residual analysis) -- flag poor fits
Relativities stability -- compare across model iterations
Cross-validation -- confirm out-of-sample testing is performed
Comparison to one-way and two-way factor analysis for reasonableness

Step 3.3 -- Rate Filing Support

Evaluate regulatory compliance readiness:

Rate indication documentation per state requirements
Support for "not excessive, inadequate, or unfairly discriminatory" standard
Filing exhibit preparation (loss data, trend, development, expense)
Competitive analysis and market impact assessment
Implementation planning (rate capping, grandfathering, transition rules)

============================================================ PHASE 4: LIFE AND HEALTH ACTUARIAL MODELS

Skip this phase if no life/health models are found. Otherwise:

Step 4.1 -- Mortality and Morbidity Tables

Evaluate table usage:

Table sources: verify SOA tables (2017 CSO, VBT, ILEC) or company experience are current
Experience study methodology: check exposure calculation, graduation, credibility
Mortality improvement assumptions: verify Scale MP or custom improvement is applied
Morbidity assumptions: check by condition and duration
Lapse and persistency: verify assumptions match recent experience
Selection vs. ultimate: confirm appropriate period is used

Step 4.2 -- Valuation Models

Assess reserve methodology against applicable standards:

GAAP (ASC 944), Statutory (VM-20, AG43), IFRS 17 -- confirm correct standard is applied
Cash flow projections -- verify both deterministic and stochastic runs exist
Net premium reserve calculations -- check for accuracy
DAC modeling -- verify amortization methodology
PBR implementation -- confirm exclusion test and stochastic reserve calculations
Asset adequacy analysis -- verify cash flow testing scenarios

Step 4.3 -- Product Pricing

Evaluate product pricing models:

Profit testing methodology (profit margin, IRR, embedded value)
Assumption sensitivity analysis -- confirm key assumptions are stress-tested
Product design optimization (benefit structure, rider pricing)
Reinsurance pricing and treaty optimization
Competitive positioning analysis

============================================================ PHASE 5: STOCHASTIC MODELING AND CAPITAL ADEQUACY

Step 5.1 -- Stochastic Framework

Evaluate stochastic modeling infrastructure:

ESG: identify interest rate model (CIR, Hull-White, Black-Karasinski) and calibration
Monte Carlo engine: check scenario count (minimum 1,000 for screening, 10,000+ for production)
Convergence testing: verify results stabilize with increasing scenario count
Correlation structure: confirm risk factor correlations are justified
Random number generation: check seed management and quasi-random sequence usage
Runtime performance: assess parallelization and bottlenecks

Step 5.2 -- Capital Modeling

Assess capital adequacy models:

Risk categories covered: insurance risk, market risk, credit risk, operational risk
Capital metric: VaR, TVaR/CTE, economic capital, regulatory capital -- confirm appropriate metric
Confidence level and time horizon: verify alignment with regulatory requirements
Diversification benefit: check correlation assumptions and methodology
Stress testing: confirm both prescribed and reverse stress tests exist
DFA framework: verify Dynamic Financial Analysis integration if present

Step 5.3 -- Regulatory Capital Compliance

Evaluate compliance with applicable capital standards:

Solvency II: SCR calculation, internal model approval status, ORSA documentation
NAIC RBC: verify formula components and action level calculations
IFRS 17: risk adjustment methodology and confidence level
OSFI (Canadian): capital requirements if applicable
ORSA: verify Own Risk and Solvency Assessment is current and comprehensive
Capital allocation: confirm allocation methodology by business unit or product line

============================================================ PHASE 6: MODEL GOVERNANCE AND CONTROLS

Step 6.1 -- Model Risk Management

Assess governance against regulatory expectations (SR 11-7 / SS3/18):

Model inventory with risk classification -- flag any models not in the inventory
Development standards and documentation -- check for completeness
Independent peer review or validation -- verify independence and qualifications
Change control and version management -- check for audit trail
Assumption setting governance and sign-off -- verify approval chain
Model limitation documentation -- confirm limitations are disclosed to users

Step 6.2 -- Actuarial Controls

Evaluate the control framework:

Data reconciliation: source-to-model tie-out procedures
Reasonableness checks: automated bounds checking on outputs
Back-testing: historical validation results and trending
Audit trail: assumption change logging with justification
SOX controls: financial reporting model controls documented and tested
Certification process: actuarial opinion sign-off workflow and timeline

============================================================ PHASE 7: WRITE REPORT

Write analysis to docs/actuarial-modeling-analysis.md (create docs/ if needed).

Structure the report as:

Executive Summary -- 3-5 bullet points of critical findings
Model Inventory -- table of all models with risk classification
Loss Reserving Assessment -- methodology evaluation and adequacy findings
Pricing Methodology Review -- ratemaking and GLM assessment
Life/Health Model Evaluation (if applicable)
Stochastic Modeling Capabilities -- ESG and Monte Carlo assessment
Capital Adequacy Assessment -- regulatory compliance status
Model Governance Review -- control gaps and recommendations
Prioritized Recommendations -- with actuarial standards references (ASOP, SOA, Solvency II)

============================================================ SELF-HEALING VALIDATION (max 2 iterations)

After producing output, validate data quality and completeness:

Verify all output sections have substantive content (not just headers).
Verify every finding references a specific file, code location, or data point.
Verify recommendations are actionable and evidence-based.
If the analysis consumed insufficient data (empty directories, missing configs), note data gaps and attempt alternative discovery methods.

IF VALIDATION FAILS:

Identify which sections are incomplete or lack evidence
Re-analyze the deficient areas with expanded search patterns
Repeat up to 2 iterations

IF STILL INCOMPLETE after 2 iterations:

Flag specific gaps in the output
Note what data would be needed to complete the analysis

============================================================ OUTPUT