Reimagining GRC for BFSI with a GenAI-Embedded Framework
Banks and financial institutions are under unprecedented regulatory pressure. AI adoption is accelerating across credit, fraud, onboarding, and advisory functions, while regulatory expectations around explainability, fairness, and auditability continue to rise. Manual, document-driven compliance models can no longer keep pace.
ACL Digital’s latest whitepaper introduces a GenAI-Embedded GRC Framework designed to help BFSI organizations operationalize governance at system speed. It shows how GenAI, when combined with deterministic controls, enables real-time regulatory enforcement, continuous assurance, and audit-ready compliance across both legacy and AI-driven environments.
What You’ll Learn
- Regulatory Intelligence as Code (RIaC) and its role in converting regulatory text into machine-executable policies
- The role of the Compliance Fabric in enforcing policies in real time across core banking systems, APIs, and GenAI applications
- How Responsible AI Monitoring and Insights (RAIMI) supports continuous audits, bias detection, and explainable reporting
- The impact of GenAI in reducing regulatory interpretation cycles from months to days
- A practical use case demonstrating the automation of Basel III capital adeququacy checks
- A phased roadmap for operationalizing GenAI-enabled GRC without disrupting existing infrastructure
Why Read This Whitepaper
Discover how BFSI leaders can:
- Achieve near real-time regulatory response to policy changes
- Extend compliance enforcement to unstructured LLM and RAG outputs
- Reduce audit preparation time through automated narrative evidence
- Improve traceability across legacy systems and AI workloads
- Embed Responsible AI oversight aligned with EU AI Act, NIST AI RMF, FCA, RBI, and BIS expectations
Build Regulatory-by-Design BFSI Systems
Compliance is no longer a periodic activity. It must be embedded, continuous, and measurable.
Download the whitepaper now to reimagine governance, risk, and compliance for the AI era.
