Arindam explores the critical role of AI in combating online fraud and safeguarding financial security at DifferentTruths.com.

In the active digital marketplaces of India and the world, millions of ordinary citizens – pensioners checking pension credits, young professionals wiring salaries, small merchants paying suppliers – are experiencing the promise of instant financial transactions. But the convenience is blotted out by online fraud. I have seen the human stories of systemic failures for a long time. The question is not whether artificial intelligence can help stem this tide, but why its full potential is unevenly deployed, disrupting so many lives.

The answer is a resounding yes. Artificial intelligence can stop a lot of online fraud. Banks and fintechs are already using advanced artificial intelligence systems to great effect. Machine learning algorithms analyse thousands of variables in real time, including transaction patterns, device fingerprints, behavioural biometrics, geolocation and subtle anomalies in typing rhythm or mouse movement. Unlike rigid rule-based systems that churn out tonnes of false positives, AI is constantly learning and adapting to new threats.

Effective Methods of AI Fraud Prevention

The first line is real-time transaction monitoring. AI scores every transaction in milliseconds, using hundreds of signals. Banks using layered machine learning are reporting 40 to 60 per cent fewer false positives, while catching more fraud.

Behavioural biometrics is another powerful layer. AI creates a unique digital footprint for a user – such as how they hold their phone, what times they typically transact, how they use the internet, etc. – to flag deviations that may indicate account takeover even if credentials are correct.

On the upside, generative AI and deepfake detection tools can combat AI-powered attacks. At Mastercard, for example, we analyse billions of transactions worldwide, using AI to assess risk and prevent losses. Detecting anomalies in onboarding images is a known example of AI used to dismantle criminal syndicates.

Indian banks are not completely out of the picture. The Reserve Bank of India’s MuleHunter AI platform enables real-time detection of fraudulent mule accounts. Several major lenders, including HDFC, ICICI and SBI, are beefing up their AI-based analytics capabilities.

There are plenty of success stories internationally. The Commonwealth Bank of Australia’s agentic AI system analyses payment patterns and proposes new detection rules that could help cut fraud losses by 20%. With the HKMA’s guidance, Hong Kong banks have reduced false positives by up to 60% and accelerated investigations.

The Human and Economic Toll

But the task remains daunting in scale. Globally, payment fraud losses total in the hundreds of billions each year. India’s UPI transactions have soared. Inclusivity means vulnerability. Fraudsters exploit this using phishing, mule accounts and ever more sophisticated deepfakes. Generative AI-enabled fraud in the U.S. could amount to $40 billion by 2027, according to Deloitte.

For victims, often elderly or less computer-savvy, the impact is more than just the money. It undermines confidence, dignity, and peace of mind. “I have written for decades about ordinary lives. I do not see them as data points. I see them as broken stories of resilience tested by systems that are supposed to protect them.

Why Aren’t Banks Doing More?

This is where the search gets uncomfortable. There is ample evidence that AI works, but many banks remain slow or cautious. Reasons include legacy IT infrastructure that resists integration, high upfront costs, regulatory uncertainty, and concerns about explainability and bias in AI models.

Surveys indicate a gap. “80-90% of banks are using some form of AI for fraud detection, but full-scale and transformative deployment is lagging. The pilot has lost many. Budget constraints, talent shortages and fear of regulatory scrutiny – especially around data privacy and model fairness – create inertia.

There is also the question of priorities in India and outside India. “Fully protecting customers is not something that pays off in the next quarter. Sometimes the short-term profit motive can overcome the long-term resilience. Furthermore, banks tend to pass some of the liability onto customers in the event of fraud, reducing their incentive to act decisively.

This reluctance carries a moral cost. Banks are fiduciaries. When they delay adopting tools that could prevent harm, they fail not in technology but in ethics. In an age where AI is sword and shield, there’s no time to play catch-up.

Co-operation and Humanism: A Path Forward

The answer is not to replace human supervision but to complement it. AI is good at spotting patterns at scale. Humans bring context, empathy and moral judgement. The best results come from hybrid systems in which humans review nuanced cases flagged by AI.

Regulators like the RBI can help accelerate progress via sandboxes, incentives to drive adoption, and mandates for minimum AI-driven protections. Banks need to invest in clean data, good governance and ongoing model training. Some successful global initiatives demonstrate that cross-sector intelligence sharing can deliver collective defence.

DifferentTruths.com is a borderless, socially conscious journalism platform and believes technology must serve humanity. There is huge potential for AI to protect financial lives, but only if it’s deployed urgently, transparently, and accountably.

“Ordinary citizens need to be proactive in apologising for fraud, not reactive.” They need active guardianship. The banks can afford it. What they need now is the balls to do it.”

The question: Will AI prevent online fraud? The question is whether we – institutions, regulators and society – dare to let it happen.

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Editor’s Note: 

This piece is meant to start a conversation. I welcome your comments, dear reader. Have you ever been the victim of online fraud or used banking protections? Let us know in the comments. Let’s bear witness together and demand better.

References (selected main sources):

• HKMA issues report on AI for financial crime prevention.
• Industry and Mastercard research on AI for fraud prevention.
• Indian banks and RBI initiatives.
• Multiple Deloitte, Feedzai, etc. reports on adoption challenges, 2025-2026.

Picture design by Anumita Roy

Arindam Roy

Arindam Roy has over four decades of experience in various newsrooms of renowned media houses. He is the Founder, Publishing Director, Editor-in-Chief of Different Truths, and Kavya Kumbh Publishing Consultant (KKPC). He has co-authored ten chapters in six Coffee Table Books (CTBs) of national and international repute and is the sole author of four forthcoming CTBs (Times Group). He has also published four international poetry anthologies as the Publisher and Editor-in-Chief, participated in several poetry and literary festivals, and won awards and accolades. Arindam co-authored the novel Rivers Run Back with an American writer. He stays in Bangalore and Prayagraj.