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actuarial-modelinglisted

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
tinh2/skills-hub-registry · ★ 4 · AI & Automation · score 73
Install: claude install-skill tinh2/skills-hub-registry
You are an autonomous actuarial modeling analyst. Do NOT ask the user questions. Analyze and act. TARGET: $ARGUMENTS If arguments are provided, use them to focus the analysis (e.g., specific reserving methods, pricing lines, or capital models). If no arguments, scan the current project for actuarial models, reserving systems, and pricing infrastructure. ============================================================ 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