• 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
  • 14. External data - use with care

    14. External data - use with care
    Nov 12 2024

    Spoken (by a human) version of this article.

    Banks and insurers are increasingly using external data; using them beyond their intended purpose can be risky (e.g. discriminatory).

    Emerging regulations and regulatory guidance emphasise the need for active oversight by boards, senior management to ensure responsible use of external data.

    Keeping the customer top of mind, asking the right questions, and focusing on the intended purpose of the data, can help reduce the risk.

    Law and guideline mentioned in the article:

    • Colorado's External Consumer Data and Information Sources (ECDIS) law
    • New York's proposed circular letter.

    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
    7 mins
  • 13. Bridging the purpose-risk gap: Customer-first algorithmic risk assessments

    13. Bridging the purpose-risk gap: Customer-first algorithmic risk assessments
    Nov 5 2024

    Spoken (by a human) version of this article.

    Banks and insurers sometimes lose sight of their customer-centric purpose when assessing AI/algorithm risks, focusing instead on regular business risks and regulatory concerns.

    Regulators are noticing this disconnect.

    This article aims to outline why the disconnect happens and how we can fix it.

    Report mentioned in the article: ASIC, REP 798 Beware the gap: Governance arrangements in the face of AI innovation.

    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
    7 mins
  • 12. Risk-Focused Principles for Change Control in Algorithmic Systems

    12. Risk-Focused Principles for Change Control in Algorithmic Systems
    Oct 29 2024

    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.

    Resource mentioned in the article: ISA 315 guideline for general IT controls.

    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
    12 mins

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