How Do We Balance AI Innovation & Data Security In Credit Unions?

How Do We Balance AI Innovation & Data Security In Credit Unions?

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The Challenge You Face

Credit union leaders are grappling with the challenge of harnessing AI's potential while safeguarding sensitive member data.

Relying on public AI models like ChatGPT raises concerns about data security, as these tools may inadvertently expose confidential information.

Additionally, training employees to use AI responsibly is complex, given the limited control over the data they input.

What Credit Union Leaders Are Doing

“We are looking at doing about four or five projects that are in the pipeline that involve artificial intelligence. But our worry is, can we get our own? Can we get something that's just for us?” - John Salgado, MBA

John Salgado, Executive Vice President and Chief Information Officer at DuGood Federal Credit Union , is addressing the challenge of integrating AI while safeguarding member data by implementing the following measures:

Controlled Access: Limiting AI tool usage to specific devices, such as iPads, to monitor and manage how these tools are utilized within the organization.

Employee Training: Educating staff on the appropriate use of AI tools, emphasizing the importance of not inputting sensitive member information into public AI platforms.

Exploring Proprietary AI Solutions: Investigating the development of an internal AI system tailored to the credit union's needs, aiming to maintain data privacy and control.

"If you're asking ChatGPT to write a policy for your financial institution, there could be some information that you put in there that you don't want out in the public.” - Becky Reed

Becky focuses on:

Raising Awareness: She compares AI to early technology phases, emphasizing that misuse can lead to breaches of intellectual property.

Educating on Responsible AI Use: Highlighting the potential for misuse, such as creating synthetic identities, Becky underscores the need to educate both employees and members on AI risks.

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Key Takeaways

? Data Security Risks

Utilizing public AI models can expose sensitive member information, as these platforms may not guarantee data confidentiality.

? Employee Training

It's crucial to educate staff on responsible AI usage, emphasizing the importance of not inputting confidential data into AI tools to prevent potential breaches.

? Need for Proprietary AI Solutions

Developing internal AI systems tailored to the organization's specific needs can enhance data control and security, reducing reliance on external platforms.

? Ethical Considerations

AI can be misused for malicious purposes, such as creating synthetic identities or deepfakes, highlighting the need for robust ethical guidelines and monitoring.

? Balancing Innovation and Security

While AI can automate repetitive tasks, it's essential to implement safeguards to protect member data and maintain trust.

Other Topics From The Episode

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?? The Blueprint For Nurturing Employees

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Sources For Our Topics

?? [2024] 150+ Trade Show Stats That Reveal All - Trade Show Labs

?? Leaders at all levels: Close the gap between hype and readiness - Deloitte Insights

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