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Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Risk Insights: Yusuf Moolla
27 episodes
7 months ago
Spoken by a human version of this article. TL;DR (TL;DL?) Testing is a core basic step for algorithmic integrity.Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems chang...
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Management
Business
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All content for Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing is the property of Risk Insights: Yusuf Moolla and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Spoken by a human version of this article. TL;DR (TL;DL?) Testing is a core basic step for algorithmic integrity.Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems chang...
Show more...
Management
Business
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Article 12. Risk-Focused Principles for Change Control in Algorithmic Systems
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
12 minutes
1 year ago
Article 12. Risk-Focused Principles for Change Control in Algorithmic Systems
Spoken (by a human) version of this article. With algorithmic systems, an change can trigger a cascade of unintended consequences, potentially compromising fairness, accountability, and public trust. So, managing changes is important. But if you use the wrong framework, your change control process may tick the boxes, but be both ineffective and inefficient. This article outlines a potential solution: a risk focused, principles-based approach to change control for algorithmic systems. Resourc...
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Spoken by a human version of this article. TL;DR (TL;DL?) Testing is a core basic step for algorithmic integrity.Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems chang...