Details
For financial institutions venturing into the realm of generative AI, ensuring robust data discovery and governance is essential. Join BigID, AWS, MongoDB, and EDM Council for key insights into navigating the intricate landscape of data governance while leveraging generative AI technologies alongside data security for the financial services sector.
Key Takeaways:
- Understanding the pivotal role of data governance in the adoption of generative AI within financial services.
- Strategies for establishing comprehensive data governance frameworks tailored to the unique challenges of generative AI.
- Addressing regulatory compliance requirements specific to financial services organizations.
Join us to gain practical insights and best practices for navigating the complexities of data governance while harnessing the transformative potential of generative AI in financial services.
Speakers
Post-event summary
The webinar titled “Data Governance Strategies for Leveraging Generative AI in Financial Services,” hosted by EDM Council and BigID, focused on the critical role of data governance and management in the application of AI and generative AI within the financial services industry. The conversation was led by experts in the industry:
- Stephen Gatchell, Sr.Director, Data Advisory, BigID
- Shiv Pullepu, Financial Services Industry Principal, MongoDB
- Peter Williams, Global Head of Financial Services Partner Technology, AWS
- Justin Heller, SVP, Chief Data Officer, Synchrony Financial
- Moderator: Eric Bigelsen, Head of Industry Engagement, EDM Council
Panelists addressed the industry’s need to navigate stringent regulatory landscapes effectively, and emphasized the importance of a robust data governance framework. They highlighted the necessity of addressing regulatory concerns to avoid biases and inaccuracies in AI outputs. Justin noted, “Governance is one of those capabilities. It’s largely people and process intended to put together an operating model to define clear roles and responsibilities, and to drive a program that ensures appropriate controls are in place for data.”
The speakers discussed the evolving focus on data quality due to AI, stressing the need for fit-for-purpose data. Stephen pointed out the importance of securing both structured and unstructured data and integrating third-party risk assessments into the governance framework. Shiv underscored the role of a comprehensive data governance framework in addressing potential security risks and ensuring efficient data flow within AI applications.
Peter highlighted the challenges and opportunities in managing data across multiple business lines, emphasizing the need for scalable governance capabilities to enable innovation while maintaining regulatory compliance. The panelists collectively underscored the significance of industry frameworks like DCAM and CDMC in establishing effective data governance practices. These frameworks help organizations align with regulatory requirements, promoting data quality, security, and privacy.
In conclusion, the webinar provided valuable insights into the strategies financial services firms can adopt to leverage generative AI while maintaining strong data governance and regulatory compliance. The emphasis on balancing innovation and control, driven by business value and supported by continuous education and training for employees, was highlighted as essential for successful data governance.