AI Risk & Compliance Online schedule

• How are AI-driven risk models enhancing predictive accuracy & real-time risk monitoring?

• What is the evolving role of AI in credit risk assessments, liquidity management, and operational risk reduction?

• How are leading banks & financial institutions leveraging AI for smarter risk decision-making?

• Balancing AI efficiency with regulatory constraints—how much autonomy should AI have in risk management?

• What are the biggest barriers to AI adoption in traditional financial institutions?

• What new AI-driven risk assessment tools are emerging in 2025?

• How do black box AI models pose compliance & legal risks?

• What are the risks of opaque AI decision-making in lending, fraud detection, and credit scoring?

• Explainable AI (XAI): Best practices for ensuring AI transparency in risk assessments.

• Regulatory expectations: What the SEC, OCC, and CFPB require for AI-driven financial decisions.

• How can banks audit and validate AI models to comply with fair lending laws?

• What steps can be taken to minimize bias and ensure fairness in AI-driven decisions?

• The role of human oversight: Should AI have the final say in financial decision-making?

Sriraman Pattabiraman, Data Governance and Risk Reporting Lead, State Street 

Jitender Jain, Engineering Lead - JP Morgan  

• How can machine learning models detect fraud patterns in real-time?

• AI in AML (Anti-Money Laundering) & KYC (Know Your Customer) compliance: Reducing false positives & improving detection.

• The rise of deepfake scams, synthetic identity fraud, and AI-enabled cybercrime.

• How are financial institutions using AI-driven anomaly detection to prevent transaction fraud?

• What are the biggest challenges in balancing fraud detection accuracy with customer experience?

• How are leading banks using AI to prevent financial fraud at scale?

• What core design principles help AI agents remain compliant in regulated financial environments? 

• Why is explainability critical in autonomous AI decision-making for finance? 

• How can explainability and regulatory awareness be embedded into agentic AI systems? 

• How can financial institutions balance innovation with auditability and trust? 

• How is AI automating compliance monitoring, reporting, and regulatory processes?

• What are the challenges of aligning AI with financial regulations (SEC, BIS, GDPR, AML, etc.)?

• How RegTech solutions are reshaping AI governance for financial institutions.

• The role of NLP & AI in automating regulatory reporting—reducing manual work for compliance teams.

• How can AI ensure continuous compliance tracking across jurisdictions?

• What are the biggest compliance risks in adopting AI-powered financial tools?

• How will the EU AI Act & U.S. regulatory proposals shape AI adoption?

• What are the key compliance challenges for banks & fintechs implementing AI-driven risk models?

• Predictions for the next decade of AI regulation & enforcement.

• How are global regulators addressing AI ethics, fairness, and accountability in finance?

• What policies should financial institutions adopt to proactively manage AI-related compliance risks?

• Are financial regulators prepared to oversee AI at scale? What new frameworks are needed?

Erum Manzoor, Senior Vice President - Citi 

Todd Covert, Chief Information Security Officer - Allstate 

Adam Ennamli, Chief Risk Officer - General Bank of Canada