OPay adopts AI, Data Analysis to protect customers against fraud

OPay, Nigeria's leading fintech platform, has adopted artificial intelligence and advanced data analysis to bolster its fraud protection measures. The company has implemented over 5,000 monitoring and blocking rules, along with more than 10,000 risk-feature profiles, to evaluate transaction behavior and detect potential threats in real-time. This sophisticated system has helped OPay maintain a transaction fraud rate below 0.001%.

The rapid expansion of digital payments in Nigeria, estimated at ₦384 trillion in July 2025, has necessitated robust fraud prevention strategies. In the first quarter of 2026 alone, transactions processed through Point-of-Sale terminals reached ₦18.78 trillion, with OPay's transaction value more than doubling to $358 billion from $166.2 billion a year earlier. Monthly active transacting users also surged from 25.13 million to 39.32 million.

To combat financial crime, OPay developed an Anti-Money Laundering and Counter-Terrorist Financing (AML/CFT) risk-control system that combines AI, big-data analysis, and real-time transaction monitoring. This system independently created by the company, retains its intellectual property rights and benchmarks against global fintech practices. The system can block transactions and, if necessary, freeze or permanently suspend accounts where suspicious activity is detected and verified.

OPay has also introduced digital identity verification and live facial-detection technology to detect identity forgery and impersonation attempts. The company has blocked over one million fake identities and blocks tens of thousands of attack attempts daily with its live facial-detection system. Know Your Customer (KYC) processes are crucial in this context, as weak identity controls can expose payment platforms to account takeover, impersonation, money laundering, and other financial crimes.

Compliance and risk management are central to OPay's operations, as the company recognizes the importance of protecting both consumers and legitimate economic activity. The integration of AI and data analytics allows OPay to analyze customer and transaction information, identify behavioral patterns indicating suspicious activity, and examine transactions within the broader context of account behavior. This real-time analysis is essential as digital payment volumes continue to rise.

For OPay, the success of its compliance framework hinges on the balance between strong fraud prevention measures and avoiding unnecessary disruptions to legitimate transactions. The company's commitment to investing in AML/CFT controls, identity verification, and AI-powered monitoring reflects a proactive approach to detecting financial crime early, rather than reacting to losses after they occur.