What Every Risk Leader Needs to Know About AI Decisions
You don't need to understand how AI models work—you need to know how to govern them.
This session is for risk, compliance, and business leaders who are being asked to approve AI use cases but don't have a framework for what "good" looks like. We'll skip the technical jargon and focus on what executives actually need: the right questions to ask, the governance structures that work, and how to turn robust AI controls into a competitive advantage with your banking clients.
Position AI as regulated infrastructure, not a shiny feature. This executive session is designed for leaders who own customer trust, regulatory relationships, and P&L in credit and fraud-heavy businesses.
What You'll Be Able to Do:
Ask your data science team the 5 questions that separate robust AI from regulatory liability
Explain to your board why you approved (or rejected) an AI use case—in plain English
Recognize when a vendor's "explainable AI" claims are real vs. marketing fluff
Build governance structures that don't become bottlenecks as AI use cases scale
Walk away with practical frameworks to approve use cases and hold technology teams accountable, transforming AI governance from compliance burden into sales advantage.
This Session Is NOT:
❌ A deep dive into machine learning algorithms
❌ A tutorial on building AI models
❌ Vendor demos or sales pitches
This Session IS:
✅ A practical guide for business leaders who need to govern AI without becoming data scientists
✅ Real scenarios from credit, fraud, and AML—and how executives responded
✅ Frameworks you can use Monday morning to evaluate your team's AI proposals
Perfect for:
Risk and compliance leaders tired of sitting in AI meetings they don't understand
Executives who need to approve AI use cases but don't know what questions to ask
Business leaders who own customer trust and regulatory relationships—not the tech stack
Anyone who's been told "don't worry, the model handles it" and thought "that's not good enough"
Specific roles include:
Chief Risk Officers and Compliance Leaders
VP/SVP Credit Risk & Fraud Operations
General Counsel and Regulatory Affairs
Product Leaders at Lending and Fraud Prevention Vendors
No technical background required. If you can read a P&L, you can govern AI.
Core Topics:
Risk Landscape in AI-Powered LOS & Fraud
How AI changes fraud detection and credit assessment—and where false positives become business landmines. Scenario work: reconstructing AI decisions for regulators.
Governance Models That Work
Compare centralized vs. hybrid structures. Define decision rights, responsible AI roles, and steering committees suited for vendors serving global banks.
Explainability & Audit Trails
Why black-box models are liabilities. What complete audit trails look like: data sources, thresholds, overrides, and human-in-the-loop intervention.
Continuous Monitoring & Incident Response
Leadership playbook for drift, bias detection, and what to do when AI fails—including client communication and regulatory reporting.
From Risk to Differentiator
How demonstrable governance (scorecards, FINOS AI frameworks) becomes part of your sales narrative with conservative clients.
You'll Leave With:
AI Risk & Compliance Charter template (roles, forums, decision thresholds)
One-page AI model risk scorecard for pre-launch review
Customer/regulator messaging on explainable, resilient AI systems
Our Speaker
Rahul Garg, Engineering Manager & AI Architect, Celestial Systems
With deep expertise in building production AI systems for regulated industries, Rahul Garg leads AI architecture and engineering at Celestial Systems. Rahul specializes in translating complex AI capabilities into governance frameworks that business leaders can actually use—focusing on explainability, audit trails, and operational resilience in high-stakes environments. His work bridges the gap between what AI systems can do and what risk leaders need to approve, monitor, and defend those systems to regulators and customers.
About Celestial Systems
Founded in 2001, Celestial Systems combines a heritage of industry leadership in application engineering with deep expertise in AI solutions. With headquarters in Vancouver and a fully in-house engineering team, Celestial empowers organizations to leverage the power of AI in practical, responsible ways—unlocking new opportunities, reducing risk, and sharpening their competitive advantage.
Space is limited to ensure meaningful conversation. Register now to secure your spot.