• When and why should AI be used in AML practices? What are its benefits and risks?
• What considerations should payments organisations take to comply with new AI regulation?
• How are payments firms elevating their risk based assessments to keep up with financial crime compliance and compete more effectively?

As payments transaction and mobile banking systems become more complex, and new waves of regulation roll into the digital banking sector, the cost of compliance is weighing heavily on payments companies. However, it is essential for companies to keep up with regulatory requirements as the cost of non-compliance is far greater.

The global payments sector is coming under increased regulatory scrutiny for its approach to Anti-Money Laundering (AML), where previously this spotlight was aimed more specifically at banks. Issuers, processors, and payment service providers need to invest to upgrade financial crime compliance technologies and processes. However, there are ways to manage and even offset this cost for payments organisations. Enter AI, which is fast becoming table-stakes in a modern AML approach. Leveraging AI for efficiency in AML operations is obvious, but must be done with an extreme focus on ‘explainability’ to be compliant.

Less obvious but no less impactful for payments, is leveraging AI’s insights for product development and pricing differentials, and commercialising those insights back to customers. Compliance with new data and AI regulations is critical. Data must be fully traceable so that it can be properly audited. Where and how payments firms approach AI and data regulation in the future will become major factors in the battle against financial crime and money laundering, as well as competitive differentiators in an increasingly crowded marketplace.

Sign up for this Finextra webinar, hosted in association with Napier, to join our panel of industry experts who will discuss different approaches to risk mitigation using AI technologies.