Interactive Simulations for Predictive Banking Analytics
About These Simulations
Welcome to the Coredian Banking Models interactive simulation suite. Each model is a standalone, fully-functional microsimulation that demonstrates how modern banks use machine learning to predict customer behavior and optimize business outcomes.
Each simulation includes three comprehensive tabs:
- Case Study: Hyper-realistic real-world examples from US banking institutions, featuring actual customer profiles, behavioral signals, and intervention outcomes
- Simulation: Detailed explanation of how the model works, including feature engineering, monotone constraints, calibration techniques, and SHAP explainability
- Run: Live interactive simulation where you can adjust parameters and watch customer states evolve in real-time
All simulations are completely standalone - no API calls, no external dependencies, no backend required. Just open in your browser and explore!
Model Portfolio Overview
Attrition Risk Model
Predicts which customers are likely to close their accounts in the next 30-90 days based on behavioral signals.
- ✓ ADB trends & balance breaches
- ✓ Fee events & payroll disruptions
- ✓ Digital engagement metrics
- ✓ 68% retention rate with interventions
Auto Loan Cross-Sell
Identifies customers likely to purchase vehicles in the next 60-90 days using shopping signals.
- ✓ Lease expiration tracking
- ✓ Dealer visit detection
- ✓ Vehicle age & mileage signals
- ✓ 24% conversion rate
Card Usage Decline
Prevents card attrition by detecting wallet share migration to competitors or digital wallets.
- ✓ Spend trend analysis
- ✓ Digital wallet shift detection
- ✓ Merchant diversity tracking
- ✓ 61% wallet share recovery
Card Upgrade Propensity
Identifies customers ready to upgrade from basic to premium card products.
- ✓ Credit score improvements
- ✓ Spend pattern evolution
- ✓ Limit constraint detection
- ✓ 42% upgrade conversion
Credit Card Cross-Sell
Acquires new credit card customers from existing deposit base using propensity modeling.
- ✓ Debit spend analysis
- ✓ Credit readiness scoring
- ✓ Competitive signal detection
- ✓ 18% acquisition conversion
Credit Line Increase
Proactively offers credit line increases to qualified customers before they request.
- ✓ Utilization pattern analysis
- ✓ Credit score monitoring
- ✓ Income growth detection
- ✓ 76% acceptance rate
Digital Engagement
Converts branch-dependent customers to digital channels, reducing servicing costs.
- ✓ Device ownership detection
- ✓ Branch visit tracking
- ✓ Age-appropriate onboarding
- ✓ $4.87M annual cost savings
Mass Affluent Segmentation
Identifies emerging high-net-worth customers for wealth management referrals.
- ✓ AUM potential estimation
- ✓ Investment outflow detection
- ✓ Life stage analysis
- ✓ $248M AUM captured
Mortgage Cross-Sell
Identifies home purchase intent before customers shop elsewhere. Highest-value model.
- ✓ Realtor activity detection
- ✓ Savings velocity tracking
- ✓ Moving signals monitoring
- ✓ $186M loan origination
Personal Loan Cross-Sell
Identifies debt consolidation and major purchase financing needs proactively.
- ✓ High-interest debt detection
- ✓ DTI ratio monitoring
- ✓ Competitor research signals
- ✓ $87.7M loan volume
Wealth Referral
Identifies customers ready for financial advisor relationships based on complexity.
- ✓ AUM threshold tracking
- ✓ Rollover event detection
- ✓ Tax complexity signals
- ✓ $892M AUM captured
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All simulations are standalone HTML files - No server, No API, No dependencies