Quantica Risk Modelling is an AI-native, explainable risk platform combining quantitative analysis, machine learning, structured expert judgement and regulator-grade governance. The design principle is simple: every number that reaches a board pack or a supervisory filing is traceable, reviewable and defensible. Underlying methodology and implementation are proprietary and discussed only under NDA.
Credit risk under Basel III, IFRS 9 expected credit loss, PD term structure modelling, LGD and collateral valuation, IRRBB and ALM, ICAAP capital planning, ILAAP liquidity stress testing, concentration risk, and integrated climate credit risk overlays for mortgage, corporate and SME portfolios.
Solvency II pillar 1 and pillar 2 modelling, ORSA scenario design, reserving under IFRS 17, underwriting risk, catastrophe modelling, reinsurance structure evaluation, asset-liability integration, and climate physical and transition overlays for property, motor, health, life and specialty lines.
Physical perils (flood, wind, heat, wildfire, drought, coastal) and transition pathways are assessed for their financial consequences — credit quality, underwriting results, asset values, reserves and capital — under NGFS and bespoke scenarios. The emphasis is on decision-useful, defensible output for boards and supervisors rather than on the mechanics behind it.
Fixed income, equity, real estate, infrastructure and structured credit are re-priced under coherent macro-financial shocks. Scenarios respect no-arbitrage constraints, hedge relationships and liquidity segmentation so results are usable for capital planning, not just headline numbers.
Independent validation is built into the workflow: model inventory, documentation, backtesting, benchmarking, sensitivity analysis, expert challenge, limitations, findings, remediation and approval. Change control and re-validation triggers are explicit, not implicit.
Inputs are governed rather than improvised: defined ownership, documented lineage, quality standards, access control and periodic review. Assumptions are evidenced and challenged, and uncertainty is reported alongside results. Methodology, data processing and calibration detail are proprietary and shared only under NDA.
Designed with Solvency II, Basel III, IFRS 9, IFRS 17, ICAAP, ILAAP and ORSA in mind. Supervisory climate stress tests, EBA guidelines and NGFS scenario applications are treated as first-class outputs, not afterthoughts bolted on to a pricing tool.
The platform is built to institutional software standards: version control, automated testing, reproducible runs, audit logging, access control and documented release management. Machine-learning components sit behind explainability, monitoring and human review. Internal design and implementation detail are not disclosed publicly.
Quantica is a working concept, iterated with practitioners in banking, insurance, reinsurance and asset management. If you're scoping an AI-native risk modelling, climate risk or model validation programme, I'm open to conversations under NDA.