magnus919_agent-skills/actuarial-risk-modeling/references/source-index.md

Source Index

These sources supplement the skill and should be checked for current scope and applicable professional requirements. They are orientation and evidence, not permission to skip jurisdictional or organizational review.

Source	Use
Actuarial Standards Board: Data Quality	Data relevance, quality, limitations, and documentation
Actuarial Standards Board: Modeling	Model risk, controls, intended use, and communication
Actuarial Standards Board: Risk Classification	Risk-classification purpose, data, assumptions, and communication
Actuarial Standards Board: Actuarial Communications	Clear disclosure of methods, assumptions, uncertainty, and limitations
Actuarial Standards Board: Property/Casualty Unpaid Claim Estimates	Reserving scope, assumptions, and communication boundaries
Actuarial Standards Board: Estimating Future Costs	Prospective cost estimates and documentation boundaries
CAS Monograph Series: Generalized Linear Models	Insurance frequency, severity, pure-premium, and GLM practice context
CAS: Predictive Models — A Practical Guide	Predictive-model development, evaluation, review, and implementation
CAS: Estimating Unpaid Claims Using Basic Techniques	Claims development, reserve methods, assumptions, and uncertainty
CAS: Extreme Value Theory as a Risk Management Tool	Tail modeling, threshold exceedances, extreme quantiles, and limitations
Open Actuarial Texts: Loss Data Analytics — Credibility	Experience rating, partial credibility, pooling, and pure-premium context
Open Actuarial Texts: Loss Data Analytics — Loss Reserving	Claims reserves, development data, stochastic reserving, and GLM approaches
Forecasting: Principles and Practice	Forecasting methods, evaluation, uncertainty, and time-series cross-validation
Forecasting: Time-series cross-validation	Rolling-origin evaluation and temporal information boundaries
scikit-learn: Probability calibration	Reliability, calibration, and calibration procedure caveats
scikit-learn: Model evaluation	Proper scoring rules and metric selection
scikit-learn: TimeSeriesSplit	Chronological split mechanics and future-data leakage avoidance
statsmodels: GLM	Reference implementation concepts for exponential-family GLMs
statsmodels: User guide	Official references for time series, GEE, mixed, and duration methods
R survival package vignette	Censoring, survival curves, proportional hazards, and recurrent events
NIST: Extreme Value Distributions	Extreme-value concepts, domains of attraction, and tail interpretation
Federal Reserve: Supervisory Guidance on Model Risk Management	Model development, validation, monitoring, governance, and controls
American Statistical Association: Ethical Guidelines	Professional competence, integrity, transparency, and responsible communication
Basel Framework: Market Risk	Market-risk measurement, backtesting, and prudential context

Check the current source before relying on a standard, software API, or jurisdiction-specific interpretation. Link claims to the source section that actually supports them.