SentinelAI™ - Portfolio Early Warning System

Continuously monitors every loan in your portfolio, detecting subtle deterioration patterns that predict default months in advance.

The Challenge

By the time borrowers miss a payment, it's often too late. Banks need 3-6 months advance warning to prevent defaults through early intervention.

What It Does

Continuously monitors every loan in your portfolio, detecting subtle deterioration patterns that predict default months before traditional delinquency metrics.

Model Metadata

Model Architecture: LSTM (Long Short-Term Memory) neural networks with attention mechanisms
Training Data Size: 50M+ monthly account observations, 8+ years
Features: Time-series of 150+ account, credit bureau, and behavioral metrics
Update Frequency: Real-time scoring, weekly model refresh
Lookback Period: 24 months of historical patterns
Prediction Horizon: 3, 6, and 12-month default probabilities

Business Outcomes

5-month average advance warning of defaults
35% reduction in charge-offs through early intervention
$8M+ annual savings in loss mitigation (typical $500M portfolio)
4x improvement in collection efficiency
Prioritized outreach to highest-risk accounts

Training Approach

Sequence ModelingLSTM networks trained on monthly time-series data to learn temporal patterns in account deterioration. Attention mechanisms identify which historical periods most strongly predict future default.

Multi-Horizon TrainingSimultaneous prediction of 3, 6, and 12-month default probabilities using shared representation learning.

Imbalanced LearningSMOTE (Synthetic Minority Oversampling) and focal loss to handle severe class imbalance in default events.

Data Sources

Account-Level Data

Payment history (amounts, timing, partial payments)
Balance trends and utilization patterns
Customer service interactions and disputes
Automated payment enrollment/cancellation

External Credit Data

Monthly credit bureau updates (soft pulls)
Credit utilization trends across all accounts
New credit inquiries and account openings
Public records (liens, judgments, bankruptcies)

Behavioral Signals

Digital banking engagement (login frequency, feature usage)
Mobile app activity patterns
Statement viewing and paperless enrollment
Communication preferences and response rates

Economic Indicators

Local unemployment trends
Housing price indices (zip code level)
Industry-specific economic indicators
Seasonal patterns

Third-Party Data

Experian Clarity (real-time credit attribute updates)
CoreLogic (property value trends for secured loans)
Equifax Early Detection (financial stress indicators)

Implementation

Real-time dashboard with risk stratification, automated alerts for accounts crossing risk thresholds, integration with collection and servicing systems.