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AI Becomes the Banker: 21 Case Studies Transforming Digital Banking CX

Finextra

This broad applicability in banking (from automating fraud reviews to generating customer communications) underscores how financial firms are integrating GenAI into their core workflows more aggressively than most. Indeed, 64% of finance leaders report using AI for fraud detection and risk management in their institutions.

AI
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The platform risk paradox: Managing digital commerce fraud at scale

The Payments Association

Navigating evolving regulatory requirements, leveraging advanced detection technologies, and implementing scalable strategies for managing merchant risk have become critical capabilities. Global e-commerce fraud is projected to surpass $100 billion by 2029. billion in return-based fraud in 2022.

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Navigating AML obligations in the age of virtual IBANs

The Payments Association

Partnering with regional providers, leveraging AI for fraud detection, and conducting regular audits will ensure compliance, transparency, and operational excellence. Since vIBANs are often treated as extensions of master accounts rather than independent relationships, firms fail to apply appropriate risk assessment frameworks.

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Can Agentic AI in Fintech Transform Financial Services Through Autonomous Intelligence?

Fintech News

Commonwealth Bank of Australia (CBA) is making significant strides in leveraging artificial intelligence to reshape the financial services landscape, already using AI to handle up to 15,000 payment disputes daily, a volume too high for its call centres.

AI
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Building the Backbone: Future-Proofing Fintech Infrastructure for the Next Decade

Finextra

AI and Edge Computing: How to Power Data-Driven Finance Artificial Intelligence (AI) is revolutionising fintech through real-time fraud detection, automated trading and risk assessment. But these use cases generate vast volumes of data that require near-instantaneous processing.

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Tech-Driven BNPL: How Sophisticated Technologies Are Reshaping the BNPL Market

Finextra

PayPal’s BNPL solution, Pay in 4, incorporates sophisticated fraud prevention technology and machine learning models to assess creditworthiness quickly. Among other things, Sezzle is using machine learning for customer risk assessment and to offer tailored financing options. It also makes sense for the superapp platform.

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Payments regulation roadmap: Q3 2025​

The Payments Association

Both UK-based and overseas companies can be prosecuted if the fraud occurs in, or targets victims in, the UK. Covers a wide range of frauds, including false representation, failure to disclose, false accounting, fraudulent trading, and cheating the public revenue.