Think of Kaaj as an AI-powered underwriter that sits next to your credit team. It reads all the financial data, policies and historical loans, then automatically proposes whether to approve, decline or price a loan, while keeping a clear audit trail for regulators.
Automates and accelerates credit risk assessment and underwriting, reducing reliance on manual spreadsheets and fragmented legacy systems, while improving consistency, explainability and regulatory compliance in lending decisions.
If successful, defensibility will come from deeply embedded workflows in lenders’ credit processes, proprietary labeled performance data from clients, and hard-to-replicate domain-specific templates for different credit products and geographies.
Classical-ML (Scikit/XGBoost)
Structured SQL
High (Custom Models/Infra)
Model governance and regulatory validation cycles for new models, plus data integration/quality issues across heterogeneous core banking and credit systems.
Early Adopters
Positioned as a modern, automation-first credit risk and underwriting layer rather than a full loan origination system, likely focusing on configurable decisioning, AI scoring and workflow automation that can plug into existing LOS/core systems rather than replace them outright.