OPINION | The Future Of Banking Security Isn't OTPs. It's AI That Spots Fraud Before It Happens

Financial organizations have been utilizing transaction alerts, OTPs, and post-transaction reviews to safeguard clients from financial scams for years. But with the emergence of digital payments getting quicker and fraudsters implementing novel ways of committing fraud, just detecting fraud after the money has been sent is no longer sufficient. The new era of financial security is associated with artificial intelligence (AI), which is capable of detecting suspicious activities and acting before the funds leave the client’s account. 

Unlike traditional fraud detection solutions using strictly defined rules for fraud detection, AI-based technologies can analyze millions of transactions at once and identify unusual patterns of behavior, estimating the chances that fraud might take place.

As all transactions and their details are analyzed (including how often the transaction takes place, where it goes, from which device and where the user is located, as well as the client’s previous spending behaviors), suspicious transactions could be detected within seconds.

How Does AI Detect A Suspicious Transaction?

Suppose a user who normally makes small payments online suddenly decides to make a large transfer to an unknown recipient. While traditional solutions might react to the size of the transaction, AI systems have the advantage of being able to analyze several contextual indicators at once and determine if the payment is legitimate. 

Thus, the systems can notify clients about further verification, stop the transaction, or send it for further investigation depending on the risk level and the banks’ policies.

The Importance Of Real-Time Intelligence

The success of fraud prevention via AI relies on its ability to process information and adapt to new threats. The machine learning models can accumulate knowledge about suspicious behaviours all the time due to new cases of transactions and fraud.

This can result in fewer fraud cases for banks, fintech companies and payment providers as well as more effective investigations and targeted interventions. Consumers will experience fewer unnecessary payment refusals because intelligent systems will be able to identify rightful suspicious behaviours and avoid unnecessary declines.

However, these systems should be regarded as not being perfect. The use of low-quality data, sophisticated fraud methods and incorrect models can produce false alarms or skip suspicious transactions. Financial institutions should test their models regularly and maintain operational monitoring mechanisms. 

Finding the Right Balance between Safety and Customer Convenience

The challenge that everyone faces when implementing a system for making payments is the need to create a more secure payment system without complicating day-to-day transactions. Too much safety procedures can annoy clients while too little assistance can lead to losses. AI provides an opportunity to align these needs by using risk-based authentication when some actions are taken partially. Strong privacy assurance and clear decision-making will be needed.