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AIGF: AI Governance for Financial Services

This AI Governance for Financial Services course, led by Sunil Soares, offers a focused curriculum on governance frameworks, regulatory compliance, and risk management in banking and insurance. Participants will explore key regulations like SR 11-7, ECOA, DORA, and Colorado Reg 10-1-1, while learning to manage AI model risk, ensure accountability, and align with cybersecurity standards. Through case studies and maturity assessments, the course provides practical tools to implement responsible, compliant AI governance in financial institutions.

As AI becomes more embedded in the operations of banks and insurers, financial institutions face both immense opportunity and growing responsibility. From reducing fraud to optimizing customer experiences, AI offers transformative benefits—but it also raises critical challenges related to bias, accountability, and cybersecurity. Navigating this complex environment requires a strong governance foundation that aligns innovation with regulatory and ethical standards.

AI Governance for Financial Services, led by Sunil Soares, equips professionals with the tools to manage AI responsibly across its lifecycle. The course explores governance frameworks, risk management strategies, and key regulations such as SR 11-7, ECOA, Colorado Regulation 10-1-1, and the EU's DORA. Participants will learn how to implement accountability mechanisms, mitigate bias in models, and integrate AI governance into broader operational and compliance practices.

Through practical case studies and maturity assessments, learners will gain a clear roadmap for designing and leading AI governance programs in financial services. Whether you're in banking, insurance, or fintech, this course will help you apply best practices that ensure AI is secure, fair, and aligned with evolving regulatory expectations.

By the end of the AI Governance for Financial Services course, participants will be able to:

Establish accountability for AI through governance frameworks and operational risk management committees.
Assess regulatory risks, including global AI-specific and sector-specific regulations across banking and insurance.
Design and implement AI model risk management, incorporating transparency, cybersecurity, and explainability.
Identify, inventory, and prioritize AI use cases based on cost, value, and risk.
Address issues of bias, fairness, and accessibility in AI applications within the financial sector.
Apply a maturity model to assess organizational readiness and guide the evolution of AI governance practices.
Integrate human oversight and ensure data privacy throughout the AI lifecycle.
Support safe deployment of AI by aligning with cybersecurity frameworks and privacy laws.
Realize strategic value from AI initiatives while managing operational, reputational, and third-party risks.

Who Should Take This Course?

This course is designed for professionals in the financial services industry who are responsible for managing, implementing, or overseeing AI systems. Ideal participants include data governance leaders, compliance officers, risk managers, IT and AI project managers, auditors, legal and regulatory affairs professionals, and business leaders involved in digital transformation. Whether you’re working in banking, insurance, or fintech, this course is valuable for anyone looking to ensure AI initiatives are aligned with regulatory standards, ethical practices, and organizational risk frameworks.

This Course Includes: