Model Risk and AI Governance

The Model Risk and AI Governance Solution, developed by Tiger Analytics and powered by the Databricks Data Intelligence Platform, enables institutions to implement a centralized, scalable, and audit-ready framework to manage models across credit, fraud, AML, collections, marketing, pricing, and more. This turnkey solution combines Tiger’s deep BFSI domain expertise with Databricks-native capabilities to automate model validation, monitoring, and governance at scale. It comes equipped with:

• Pre-defined validation and variable-level metrics, including PSI, CSI, precision, recall, and accuracy
• Automated MLOps pipelines using Lakeflow Jobs and Asset Bundles for orchestration
• Robust ML observability, enabling real-time drift detection, benchmarking, and performance tracking
• Reliable, versioned data via Delta Lake to support consistent model analysis and reproducibility
• Rapid performance analysis through Databricks SQL, delivering faster AI risk assessments
• Centralized governance using Unity Catalog to enforce secure, role-based access to model artifacts
• AI enablement capabilities, including readiness for GenAI and integration with MosaicAI for future use cases

The solution also supports a rich functional architecture, from model training and bias/fairness evaluation to scenario simulation, cost monitoring, model documentation, and enterprise dashboards, designed to streamline collaboration across validation teams, model developers, and risk governance stakeholders.

With this solution, BFSI leaders achieve:

• 60-80% reduction in manual effort of managing model risk
• 100% auditability across the model lifecycle
• Business value within 3-4 months, from setup to enterprise deployment