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By Ana Pereu, 5 October 2026 Corporate investigations are changing rapidly. Advances in data analytics, artificial intelligence and continuous monitoring have transformed how organisations identify and respond to potential misconduct. Tasks that once required weeks of manual review can now be completed in hours, while organisations are increasingly able to detect emerging issues before they escalate into significant risks.

This article is a free excerpt from inCOMPLIANCE, ICA's bi-monthly, member exclusive magazine. To gain access to more articles like this, sign in to the Learning Hub or become a member of ICA. Geographic risk frameworks in the AMLA era will be defined by dynamism and moving parts, writes Gary Youinou The days of using static country rating lists to assess geographical money-laundering risk are over.

For three years, the Western response to Russia's invasion of Ukraine moved in something close to lockstep: the US, the EU and the UK adding sanctions in near-simultaneous waves, each treating divergence as a risk best avoided. That unity is now over. Washington has spent the past year easing pressure and dangling relief as a bargaining chip, while Brussels and London have done the opposite, tightening measures and enforcement with a severity that now outpaces anything seen since 2022.

By Alon Kohalny, 22 September 2026 On 1 September 2026, new Financial Conduct Authority (FCA) rules brought serious non-financial misconduct more explicitly within the scope of the regulatory framework applying to financial services firms.[1] The changes concern conduct such as bullying, harassment and violence. At first sight, these may appear primarily to be matters for Human Resources (HR), employment law and workplace culture.

Since AI became a key fixture in their operations, most financial institutions have been attempting to answer the key question of whether it can be used responsibly. To address it, model risk frameworks, fairness testing and explainability standards have been introduced, giving institutions increasingly established ways of governing AI. Agentic AI, however, introduces some thornier issues. What decisions and actions are institutions prepared to delegate to AI agents?

By Dan Byrne, 15 September 2026 FIFA is becoming one of the governance disasters of 2026. We expect these kinds of stories to surface in big corporate names; rarely do we see it in non-profits, especially non-profits entrusted with running one of the world’s most-loved pastimes. But here we are, fresh from “the best World Cup ever”, and football’s governing body is in the middle of a governance nightmare. Why? Gianni Infantino.

Artificial intelligence has no shortage of compelling demonstrations across the industry. Yet for many financial crime teams, a more important question remains: who can point to measurable returns from a production AI deployment? As organisations move beyond experimentation, success can no longer be measured by whether AI can complete a task. The real test is whether it improves an outcome.

This article is a free excerpt from inCOMPLIANCE, ICA's bi-monthly, member exclusive magazine. To gain access to more articles like this, sign in to the Learning Hub or become a member of ICA. Jude Hilton looks at what it takes to move PEP screening from doing the bare minimum, to realistically reducing risk. Politically exposed persons (PEPs) continue to attract regulatory attention, supervisory scrutiny and media interest.

It’s worth asking the question directly, because dodging it does no favours to the case for learning. If the answer to almost any technical question is a few keystrokes away, and increasingly arrives pre-explained and ready-applied through AI, what exactly is training still for? This is not a new challenge. Search engines raised something similar years ago.

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