Multi-Bureau Credit Intelligence ModelFirst in India

ScoreBoost API

India's first proprietary credit optimization model. Predicts past bureau performance with 92% accuracy (v3.0), identifies 50+ actionable improvement levers per user, and projects best achievable scores at 3, 6, and 9 month horizons.

Past Bureau Performance Prediction

Predict the Past Before Projecting the Future

Before recommending any action, ScoreBoost first proves it understands the user. The model ingests bureau data and predicts the user's historical score trajectory purely from tradeline features — validating its behavioral understanding.

Only when past bureau performance prediction accuracy exceeds our confidence threshold does the model proceed to generate forward projections. Every recommendation is grounded in validated understanding — not generic heuristics.

Model Accuracy by Version

v1.0
69%
v2.0
84%
v3.0
92%

v3.0 currently live · Trained in-house on Indian bureau data

Actual Bureau Score
Model Predicted Score

Past Performance: Predicted vs Actual

10-month validation window · Single user sample

v3.0 Live
92% Acc.

Personalized Score Projection

Every user gets a unique projection. The model identifies 50+ actionable levers from their bureau data and projects the best achievable score at 3, 6, and 9 month intervals.

Current Score

680
Per User
50+
Actionable levers identified
Projection
3/6/9 mo.
Temporal impact horizons
Model
Proprietary
Trained in-house on Indian bureau data
First in India

The only model in India that validates past bureau performance prediction before generating forward score projections. Proprietary, trained in-house.

Model Pipeline

End-to-end inference pipeline from raw bureau data to personalized, time-bound score improvement plans. Every output is unique to the user.

01

Multi-Bureau Data Ingestion

Consent-driven ingestion from CIBIL, Experian, Equifax, and CRIF. Raw tradeline, enquiry, and DPD data is normalized into a unified credit feature vector.

02

Past Bureau Performance Prediction

The model predicts the user's historical score trajectory purely from tradeline features — validating its understanding of their credit behavior before generating any forward projection. Currently at 92% accuracy (v3.0).

03

Action Discovery (50+ Signals)

Identifies 50+ actionable levers unique to each user — from utilization reduction and tradeline age optimization to dispute-eligible errors and strategic credit mix adjustments.

04

Temporal Impact Projection

Projects best achievable score at 3, 6, and 9 month intervals assuming positive actions are taken. Each projection is personalized — no two users get the same output.

Core Capabilities

Purpose-built for India's multi-bureau credit ecosystem. RBI-compliant. DPDP Act-ready. Fairness-audited.

Multi-Bureau Feature Fusion

Unified feature extraction across CIBIL, Experian, Equifax, and CRIF — resolving entity mismatches, duplicate tradelines, and reporting lag across bureaus.

Counterfactual Simulation Engine

Causal inference-driven "what-if" analysis that predicts exact score delta for any financial action before execution — with confidence intervals.

Interpretable Action Plans

SHAP-based explainability layer generates step-by-step, human-readable action plans ranked by predicted impact and effort.

Anomaly Detection & Auto-Dispute

Statistical anomaly detection flags reporting errors and inconsistencies across bureaus. Generates RBI-compliant dispute drafts automatically.

Integrate ScoreBoost into Your Pipeline

Request API access for your lending platform, fintech app, or credit decisioning workflow.

Get Early Access
Coming Soon