Alternate-data credit scoring that goes beyond CIBIL. Collections prioritization that recovers 20-35% more with the same team. Real-time transaction fraud scoring under 100ms. Early default warning 60 days ahead. Every score ships with SHAP explanations your risk team and RBI can both defend.
India's credit bureau data covers 400M-odd people. That leaves 800M+ adults invisible to traditional scoring, including most gig workers, small business owners, and first-generation earners in their 20s. Your rejection rate on that segment is 90%+, and the ones you do approve default at 4-6x your normal book.
Alternate-data ML changes the shape of this problem. Bank statement analysis, UPI transaction patterns, GST filings, telecom recharge behaviour, device signals all combine into a score that works on thin-file customers. Approve more of the safe ones, reject fewer of them wrongly, price the risky ones for what they cost.
Bank statements (via Perfios / Karza / Finbox), UPI patterns, GST filings, telecom recharge, app usage. Scores new-to-credit customers CIBIL can't see. Straight-through processing on the confident bucket.
70-80% AUC on NTC segmentsPredicts which performing loans will slip into 30 DPD or 90 DPD 60 days ahead. Your risk team intervenes early with restructuring or step-up collections while recovery is still possible.
10-20% reduction in NPA formationRanks delinquent accounts by expected recovery per hour of agent effort. Collections team calls the accounts with highest expected recovery first, skips the ones the model says won't pay regardless.
20-35% collections upliftScores every incoming UPI, card, wallet, or net-banking transaction in under 100ms. Rules plus ML combined. Auto-approve, step-up-auth, or hold-for-review based on score.
Sub-100ms real-time APIPredicts which existing customers will accept a top-up loan, credit card, insurance, or investment product. Your CRM gets a ranked propensity list per product per customer.
3-5x cross-sell conversionNot strictly predictive ML but often bundled: OCR plus LLM extraction on Aadhaar, PAN, bank statements, ITR, salary slips into structured fields with confidence scores. Speeds up onboarding.
60-80% onboarding time cut15-min call. Tell us the product (personal loan, business loan, credit card, BNPL), monthly volume, current scoring approach. We come back with a data-audit checklist and prototype scope.
Book Free 15-min CallProduct, book size, current scoring, data availability, RBI constraints. Written feasibility doc.
Baseline model on your data. Accuracy report, SHAP samples, false-positive analysis. Your risk team reviews.
Feature store, retraining pipeline, RBI audit trail, SHAP explainer, API integration into LOS or collections, security review, deployment.
Drift detection, quarterly retraining, bias monitoring, RBI-audit-log maintenance, model performance reviews.
Book a 15-min call. Tell us your product and monthly volume. We come back with a data-audit checklist and prototype scope in 48 hours.