Risk Modelling Portfolio

Twelve modelling modules across climate, banking, insurance, ALM, IRRBB, valuation, capital and validation — each summarised by objective, scope, governance, outputs, users and regulatory relevance. Methodology and implementation detail are proprietary and discussed under NDA.

Climate Physical Risk

Objective: Quantify hazard-driven financial impact from flood, wind, heat, wildfire, drought and coastal perils.
Scope: Property, mortgage, corporate and specialty portfolios; single-event and annual exposure; concentration and accumulation questions.
Governance: Documented assumptions and limitations, sensitivity analysis, benchmarking against recognised catastrophe views, independent validation.
Outputs: Event and annual losses, tail metrics, portfolio heatmaps.
Users: Underwriters, credit officers, CRO, risk committees.
Regulatory: Solvency II NatCat, PRA climate expectations, ORSA.

Physical risk articles

Climate Transition Risk

Objective: Translate transition pathways into sector-level financial impact on credit, valuation and reserves.
Scope: Sector and counterparty exposure to policy, carbon pricing, technology substitution and demand change under NGFS and bespoke scenarios.
Governance: Scenario rationale and horizon documented, judgement made explicit, results presented with uncertainty ranges.
Outputs: Portfolio PD/LGD shifts, valuation impacts, sector heatmaps.
Users: Credit risk, portfolio management, investment risk.
Regulatory: IFRS 9 macro overlays, ICAAP, ORSA transition scenarios.

Transition risk articles

IRRBB and ALM

Objective: Measure interest-rate and liquidity risk in the banking book across curves, tenors and behavioural assumptions.
Scope: Economic value and earnings sensitivity, behavioural assumptions for non-maturity deposits and prepayment, hedge strategy.
Governance: Behavioural assumptions owned, evidenced and reviewed; sensitivity ranges disclosed where data is thin.
Outputs: EVE, NII, hedge effectiveness, liquidity stress metrics.
Users: Treasury, ALCO, risk committees.
Regulatory: EBA IRRBB, ILAAP, LCR, NSFR.

Credit Risk and IFRS 9

Objective: Expected credit loss with forward-looking macroeconomic overlays including climate.
Scope: Staging, lifetime loss, scenario weighting and overlay governance across retail, SME and corporate portfolios.
Governance: Challenger comparison, out-of-sample review, overlay justification, audit and validation evidence.
Outputs: Stage 1/2/3 provisions, sensitivity, scenario probability weighting.
Users: Finance, credit risk, audit.
Regulatory: IFRS 9, ICAAP stress testing, EBA guidelines.

Insurance Pricing

Objective: Technical pricing across property, motor, health, specialty and life lines.
Scope: Risk segmentation, portfolio mix, profitability monitoring and fairness considerations.
Governance: Performance monitoring, review cadence, documented limitations, human oversight of automated components.
Outputs: Technical rates, risk selection, portfolio mix.
Users: Actuaries, underwriters, pricing committees.
Regulatory: Consumer duty, IDD, local pricing rules.

Reserving

Objective: Best estimate and risk margin under IFRS 17 and Solvency II.
Scope: Reserve adequacy, development uncertainty, claims-environment change and reserve risk.
Governance: Actual-versus-expected review, documented judgement, independent actuarial challenge and audit trail.
Outputs: Best estimate, risk margin, sensitivity, CSM.
Users: Actuarial reserving, finance, audit.
Regulatory: IFRS 17, Solvency II TP, local statutory frameworks.

Solvency II Economic Capital

Objective: SCR and internal-model style economic capital.
Scope: Risk module coverage, dependency and diversification judgement, tail adequacy, standard formula appropriateness.
Governance: Use test, documented dependency rationale, validation cycle, board understanding of limitations.
Outputs: SCR, own funds, coverage ratio, sensitivities.
Users: Risk function, capital committee.
Regulatory: Solvency II Pillar 1/2, ORSA.

Basel III Capital Modelling

Objective: RWA and capital across credit, market and operational risk.
Scope: Approach selection, portfolio segmentation, stress capital and capital planning.
Governance: Regulatory floors and add-ons applied, documented limitations, supervisory review readiness.
Outputs: RWA, capital ratios, stress capital.
Users: Regulatory reporting, treasury, CRO.
Regulatory: Basel III/IV, EBA, PRA.

Liquidity Risk

Objective: Institution-level liquidity risk under normal and stressed conditions.
Scope: Funding concentration, behavioural outflow assumptions, survival horizon and contingency planning.
Governance: Stress severity rationale, assumption ownership, escalation triggers and contingency funding plan testing.
Outputs: Coverage ratios, liquidity horizon, contingency needs.
Users: Treasury, ALCO.
Regulatory: ILAAP, LCR, NSFR.

Cross-Asset Valuation

Objective: Coherent scenario re-pricing of fixed income, equity, real estate and infrastructure.
Scope: Scenario consistency across asset classes, liquidity segmentation and hedge relationships.
Governance: Market-consistency checks, challenger comparison, documented judgement on illiquid assets.
Outputs: Scenario NAVs, MTM stresses, hedge effectiveness.
Users: Investment risk, ALM, treasury.
Regulatory: Solvency II asset stress, ICAAP market shocks.

Model Validation

Objective: Independent second-line validation across risk models.
Scope: Conceptual soundness, data quality, implementation review, performance testing, benchmarking and effective challenge.
Governance: Findings with severity ratings, remediation tracking, re-validation triggers and formal sign-off.
Outputs: Findings, severity ratings, remediation plans, sign-off.
Users: Model risk function, audit, regulators.
Regulatory: SR 11-7, EBA model management, PRA SS 1/23.

Model validation notes

AI Model Governance

Objective: Governance of machine learning and generative components across the modelling estate.
Scope: Model inventory and tiering, explainability, drift and performance monitoring, human oversight, third-party and vendor risk.
Governance: AI risk appetite, approved-use registers, incident handling, red-team review and periodic re-approval.
Outputs: Approved use, monitoring dashboards, incident reports.
Users: Model risk, compliance, technology, business owners.
Regulatory: EU AI Act, PRA SS 1/23, SR 11-7.

AI for climate risk

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