Business Reporter – Finance – Tackling financial fraud with AI

Financial fraud is an ever-evolving challenge – and it’s becoming increasingly sophisticated. As criminals develop ever-more advanced techniques, many organisations find themselves limited by outdated, rules-based fraud detection systems that struggle to respond in real time.

Traditional methods, such as flagging transactions based solely on transaction thresholds or geographic locations, are proving inadequate against contemporary threats. The rise of deepfake scams, synthetic identities and elaborate financial “mule” networks demand a more sophisticated approach. Once an account has been opened by a mule, it enables them to take out loans and gain access to card products and credit. This ultimately creates more fraudulent transactions and increases the overall fraud rates banks will experience.

Thankfully, artificial intelligence (AI) is revolutionising fraud prevention by enabling dynamic, AI-powered models that continuously adapt to emerging threats. Feedzai, an AI-native risk management platform, is leading this transformation, helping financial institutions fight fraud while maintaining customer trust.

The changing landscape of financial fraud

Financial fraud happens in various ways. Account takeover occurs when cyber-criminals gain unauthorised control of accounts through phishing attacks or credential-stuffing techniques. Authorised push payments and scams can take many forms – from romance scams, where fraudsters attempt to establish romantic relationships via fake profiles before extorting money from their victims, to CEO identity fraud, where deepfake technology is used to impersonate senior executives. Meanwhile, money laundering operations use synthetic identities and networks of mule accounts to move illicit funds undetected through the financial system. Each of these techniques requires different detection and mitigation strategies.

In the Middle East, financial services regulators are intensifying their focus on fraud prevention, creating new compliance requirements for banks. Saudi Arabia’s SAMA regulations refer to AI several times as a tool for strengthening fraud management. Similarly, the UAE Central Bank has implemented a stringent anti-fraud framework that mandates 24/7 monitoring systems, placing pressure on financial institutions to modernise their fraud detection systems with AI.

The region faces a particular challenge with the proliferation of financial mules – individuals who, knowingly or unknowingly, allow their accounts to be used for laundering money. The growing threat of deepfake technology is another challenge, as it allows criminals to generate entirely new digital identities rather than recycling known fraudulent ones, as they did in the past.

These evolutions in criminal tactics have rendered traditional fraud detection methods, which rely on recognising previously identified patterns, increasingly ineffective.

AI in fraud detection

Traditional fraud detection systems use static, predetermined rules to identify risky transactions and are typically siloed to individual channels. But because of this, they are slow to adapt and limited in scope. In contrast, AI-driven solutions, such as those developed by Feedzai, use real-time behavioural analytics to detect the anomalies that may indicate fraud is happening. This is done on an omnichannel basis to build a holistic picture of the customer and better identify anomalous activity.

This approach enables what’s known as “segment-of-one profiling”, where each user’s unique behavioural patterns, including subtle characteristics such as mouse movements, typical device usage and transaction habits, are analysed to identify small instances of unusual activity that may be indications of attempts at fraud.

The system dynamically assesses risk by evaluating transactions against hundreds of potential risk factors simultaneously. This analysis enables financial institutions to deliver responses that are appropriate to the nature and level of the risk. For example, low-risk transactions are allowed to proceed unimpeded while high-risk payments are blocked or subjected to additional identity verification procedures. All fraud must have a tailored approach to detection.

Feedzai processes data from over $8 trillion of transactions annually, creating a large and robust dataset that is used to train and improve its AI models. To keep evolving and stay ahead of fraudsters, the company spends 25 per cent of its profits on research and development to stay at the cutting-edge of fraud detection, detecting emerging threats before they become widespread problems.

Building trust with AI

Effective fraud prevention extends beyond simply stopping criminals. Customer trust in financial institutions must be maintained. Feedzai has developed a comprehensive trust framework built on five foundational principles that guide its AI development and implementation.

AI is used in a transparent manner, with traceable data and clear explanations of when it is being used and how decisions are arrived at. Robust anti-fraud processes powered by AI are always in place. Outputs from the system are unbiased, ensuring that people are treated fairly. The AI systems used are secure, operated in line with cyber-security best practices. And AI systems are regularly tested, checked and updated to ensure quality.

Alongside its trust framework, Feedzai has a strong focus on customer convenience. Interventions are appropriate to the type and level of risk, so that when risks are low, customers are not unduly inconvenienced, such as by having a transaction stopped or by being asked for extra identification.

Privacy is also important. Feedzai’s newest innovation, Feedzai IQ, uses powerful data analytics. But its data processing uses only metadata. No personally identifiable data (PII) is processed, so consumers can be confident their privacy is being preserved. This helps support privacy regulations such as GDPR and the requirements of the Saudi SDAIA.

As well as consumer metadata, third-party data can also be beneficial when identifying financial fraud. The integration of the Demyst data orchestration platform into Feedzai enables financial institutions to access third-party data, such as network activity and behavioural insights, allowing them to convert raw information into actionable insights in real time.

All of this happens very rapidly. With Feedzai IQ, transactional data is turned into actionable insights in real time. The normal time to set up a new method of detecting fraud using rules-based tools might be three months. But with Feedzai, results based on the actionable insight generated from its global customer base can be provided within a day, which is especially beneficial to financial institutions who may not have mature fraud-labelled data. This means that, as the fraud evolves, so do the defences.

Fraud prevention in a digital world

The fight against financial fraud has entered a new era, one where artificial intelligence serves as the critical differentiator between vulnerable institutions and organisations capable of providing truly secure digital financial services.

As fraudsters continue innovating, equally innovative defences will be needed. Feedzai’s platform demonstrates that AI, when properly implemented, can enhance the safety of financial transactions while preserving the exceptional customer experiences that drive business growth. In this evolving battle, AI-powered protection isn’t just preferable, it’s becoming indispensable.

Feedzai is a global leader in fraud prevention providing AI-powered tools to identify fraudulent payment transactions in real time and minimise risk in the financial services and e-commerce industries. Feeedzai has a global presence with significant investments in the Middle East. To learn more about Feedzai’s AI-native financial crime prevention services, click here.