A dynamic AI-native company with a global presence is setting a new standard for securing financial transactions and making significant investments in the Middle East.
Financial fraud is becoming increasingly sophisticated. And as criminals develop ever-more advanced techniques, many organizations find themselves limited by outdated, rules-based fraud detection systems that struggle to respond in real time.
Traditional methods are proving inadequate against contemporary threats. The rise of deepfake scams, synthetic identities and elaborate financial “mule” networks demand a more sophisticated approach.
Thankfully, dynamic, AI-powered models that continuously adapt to emerging threats are revolutionizing fraud prevention. Feedzai, an AI-native risk management platform, is leading this transformation, helping financial institutions fight fraud while maintaining customer trust.
The changing landscape of fraud
Financial fraud happens in various ways. Account takeover occurs when cybercriminals gain control of accounts through phishing attacks or credential-stuffing techniques. Authorized push payments and scams can take many forms — from romance scams to CEO identity fraud. 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. 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. Deepfake technology is another challenge, as it allows criminals to generate entirely new digital identities rather than recycling known fraudulent ones.
AI in fraud detection
Traditional fraud detection systems use static, predetermined rules to identify risky transactions and are typically siloed to individual channels. But this means they are slow to adapt and limited in scope. In contrast, AI-driven solutions, such as those developed by Feedzai, use real-time behavioral analytics to detect anomalies, on an omnichannel basis.
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.
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. The company spends 25 percent 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
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 and how it is used. Robust anti-fraud processes powered by AI are always in place. Outputs from the system are unbiased, ensuring people are treated fairly.
The AI systems used are secure, and regularly tested, checked and updated to ensure quality. 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 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.
Third-party data can also help identify 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 behavioral insights, allowing them to convert raw information into actionable insights in real time.
All of this happens very rapidly. 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. As the fraud evolves, so do the defenses.
Fraud prevention in a digital world
The fight against financial fraud has entered a new era, where AI serves as the critical differentiator between vulnerable institutions and organizations capable of providing truly secure digital financial services.
As fraudsters continue innovating, equally innovative defenses 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.
To learn more about Feedzai’s AI-native financial crime prevention services, click here.
