• Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing

  • By: Risk Insights: Yusuf Moolla
  • Podcast

Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing

By: Risk Insights: Yusuf Moolla
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  • Summary

  • Insights for financial services leaders who want to enhance fairness and accuracy in their use of data, algorithms, and AI.

    Each episode explores existing and emerging challenges and solutions related to algorithmic integrity, including discussions on navigating independent audits.

    The goal of this podcast is to give leaders the knowledge they need to ensure their data practices benefit customers and other stakeholders, reducing the potential for harm and upholding industry standards.
    © 2024 Risk Insights Pty. Ltd.
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Episodes
  • 6. Balancing Security and Access for increased algorithmic integrity

    6. Balancing Security and Access for increased algorithmic integrity
    Sep 17 2024

    Spoken (by a human) version of this article.

    When we talk about security in algorithmic systems, it's easy to focus solely on keeping the bad guys out.

    But there's another side to this coin that's just as important: making sure the right people can get in.

    This article aims to explain how security and access work together for better algorithm integrity.

    About this podcast

    A podcast for Financial Services leaders, where we discuss fairness and accuracy in the use of data, algorithms, and AI.

    Hosted by Yusuf Moolla.
    Produced by Risk Insights (riskinsights.com.au).
    Show more Show less
    6 mins
  • 5. Equal vs Equitable: Algorithmic Fairness

    5. Equal vs Equitable: Algorithmic Fairness
    Sep 10 2024

    Spoken (by a human) version of this article.

    Fairness in algorithmic systems is a multi-faceted, and developing, topic.

    In episode 4, we explored ten key aspects to consider when scoping an algorithm integrity audit.

    One aspect was fairness, with this in the description: "...The design ensures equitable treatment..."

    This raises an important question. Shouldn't we aim for equal, rather than equitable treatment?

    This episode aims to shed light on the distinctions between equal and equitable treatment in algorithmic systems, while acknowledging that our understanding of fairness is still developing and subject to ongoing debate.

    About this podcast

    A podcast for Financial Services leaders, where we discuss fairness and accuracy in the use of data, algorithms, and AI.

    Hosted by Yusuf Moolla.
    Produced by Risk Insights (riskinsights.com.au).
    Show more Show less
    14 mins
  • 4. Structuring the Audit Objective: 10 Key Aspects of Algorithm Integrity

    4. Structuring the Audit Objective: 10 Key Aspects of Algorithm Integrity
    Sep 3 2024

    Spoken (by a human) version of this article.

    In Episode 1, we explored the challenges of placing undue reliance on audits.

    One potential solution that we outlined is a clear scope, particularly regarding the audit objective.

    In this episode, we focus on algorithm integrity as the broad audit objective.

    While it’s easy to assert that an algorithm has integrity, confirming this assertion is a bit more complex.

    To help simplify this, this episode breaks it down into a set of key areas to consider.

    About this podcast

    A podcast for Financial Services leaders, where we discuss fairness and accuracy in the use of data, algorithms, and AI.

    Hosted by Yusuf Moolla.
    Produced by Risk Insights (riskinsights.com.au).
    Show more Show less
    13 mins
Management Economics
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