No drift between origination and monitoring: a scorecard running on FINVIJ uses the same 1,500-entity ontology as NirnayaDecisionAI and PramanaRiskAI. The population you train on is the population you provision for.
Enterprise-grade scorecard development and deployment platform
Ready-to-deploy scorecards for personal loans, home loans, vehicle finance, and MSME lending built on Indian credit data.
Adjust score ranges, cut-offs, and weightages through an intuitive interface without rebuilding models.
Built-in Gini, KS, PSI, and CSI calculations with automated model validation reports for regulatory compliance.
A/B test new scorecards against existing models with statistical significance tracking and automated rollback.
Auto-generated model documentation including variable definitions, score distributions, and performance metrics.
Deploy scorecards to production with version control, rollback capability, and real-time monitoring.
Pre-built and validated for the Indian credit market
Comprehensive scoring models for individual borrowers across various loan products.
Specialized models for micro, small, and medium enterprise lending with limited data.
Predict future customer behaviour based on account performance and transaction patterns.
Score thin-file and new-to-credit customers using alternative data sources.
Proven performance across Indian lending portfolios
Discrimination benchmarked and validated on Indian retail portfolios
Time to deployment
Compliant documentation
Segments covered by pre-built models
Standalone scorecard vendors give you a model. FINVIJ gives you a model that shares its borrower definition with your origination, decisioning, and ECL systems. When the RBI asks why your scorecard population and your provisioning population diverge, FINVIJ's answer is: they don't.
PramanaRiskAI is the governance and monitoring layer for every scorecard you deploy →
Accelerate your credit decisioning with pre-built, validated scoring models.
