Intelligent Decisioning
AI/ML Engine
Custom credit scoring, fraud detection, and predictive analytics powered by machine learning.
Highlights
Multi-layer fraud detection
Explainable AI decisions
- Reduce defaults with better underwriting
- Catch fraud before disbursement
- Personalize offers for each customer
- Continuously improve with learning models
Features & Capabilities
Everything you need for ai/ml engine.
[ 01 ]
Credit Scoring Models
Custom ML models trained on your portfolio data for better risk assessment.
[ 02 ]
Fraud Detection
Real-time fraud scoring with device fingerprinting, velocity checks, and pattern recognition.
[ 03 ]
Income Analysis
AI-powered income estimation from bank statements, ITR, and alternative data.
[ 04 ]
Collection Propensity
Predict payment behavior and optimize collection strategies.
[ 05 ]
Risk Segmentation
Dynamic portfolio segmentation for pricing and collection prioritization.
Use Cases
How businesses use AI/ML Engine.
Use case
New-to-Credit Scoring
Score thin-file customers using alternative data like UPI transactions, social signals, and device data.
Use case
Application Fraud
Detect synthetic identities, document tampering, and first-party fraud in real-time.
Use case
Dynamic Pricing
Risk-based pricing with personalized interest rates for each customer segment.
Use case
Early Warning System
Predict accounts likely to default 30-60 days in advance for proactive action.
Technical Specifications
Enterprise-grade infrastructure built for scale and security.
Model AccuracyHigh AUC
Inference Time< 100ms
Data Sources20+
Model UpdatesWeekly
ExplainabilitySHAP/LIME
ComplianceFair Lending
What it does
The capabilities this module ships with.
- Alternative credit scoring
- Real-time fraud detection
- Income & expense analysis
- Customer segmentation
- Predictive default models
- Continuous model improvement
Frequently Asked Questions
Common questions about AI/ML Engine.
We use your historical portfolio data combined with our proprietary features to train custom models for your specific use case.
Loan applications, bureau data, bank statements, and performance history. More data = better models.
Yes, we provide SHAP-based explanations for every score, showing which factors contributed most to the decision.
Models are retrained weekly with new data to adapt to changing patterns and improve accuracy.
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Pre-Built Connectors
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