Quantitative use cases
Model the decision, not just the data.
Explore representative risk scenarios, model diagnostics, actions, and retained evidence.
Modeled loss distribution
BaselineAdverseReverse stress
4model capabilities
Quantitative scenarios
See how the model changes the decision.
Banking
Surface portfolio deterioration before a payment event.
Combine borrower, account, collateral, sector, and behavior signals into an explainable early-warning view.
0.82Illustrative validation AUC
14Days of modeled lead time
7.4Illustrative stability index
Illustrative sample data for product demonstration. Customer outcomes depend on data, scope, controls, and acceptance criteria.
Inspect the model before it changes the decision.
Move the stress level and compare the forecast, leading drivers, decision threshold, and retained evidence.
Decision under analysis
Portfolio early warning
PD migration and loss forecast
Composite risk72Review
Accepted baselineAdverse scenario
NowModeled horizon
Driver contribution
Illustrative sample data for product demonstration. Model design, performance, thresholds, and actions are validated against each customer's data and control requirements.
Explore the quantitative risk library.
Search representative engagement patterns by risk domain and model capability.
8 representative scenarios
Portfolio early warning
Forecast migration and loss while preserving the borrower, feature, model, and policy trail.
Credit decision consistency
Calibrate scores, thresholds, overrides, and review policy against accepted portfolio behavior.
Claims network anomalies
Prioritize unusual provider, claimant, timing, location, and relationship combinations.
Loss development stress
Test severity, inflation, event, concentration, and reserve assumptions in one evidence trail.
Intraday behavior breaks
Detect changes in price, volume, liquidity, spread, and conduct sequences against live baselines.
Counterparty correlation stress
Connect collateral, exposure, market, entity, and concentration shocks before limit decisions.
Supplier dependency scoring
Reveal financial, delivery, geographic, ownership, logistics, and single-source concentration.
Demand and disruption forecast
Model demand distributions and route disruption so inventory decisions include uncertainty.
Turn one scenario into a validation and pricing plan.
Choose the model capabilities, data sources, deployment boundary, and validation support needed for the first accepted decision.