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Microsoft Debuts AI Solution to Prevent Mobile Banking Fraud in Two Seconds

In recent years, mobile banking adoption has grown, so does mobile device fraud has inevitably increased as well. “Over 800 million people use mobile applications every day, with an increasing amount of relying on mobile banking apps, banks, and stores,” Microsoft stated.

Therefore, the need to detect and prevent these fraudulent mobile device activities has become all the more important for customers and banks.

As the company explains, the mobile fraud occurs through a mobile number, hijacking better known as “SIM swap attack.” This cloned phone thus starts receiving all the calls and messages that were originally sent to the victim’s mobile phone.

Then by using the information obtained through social engineering, phishing, fishing, or an infected downloaded app, they impersonate a bank customer, register for mobile access, and immediately start to request fund transfers and withdrawals. This technique was even used by the American student who managed to steal $5 million from 40 people.

In order to reduce these activities, Microsoft has created a fraud detection solution that will detect bank fraud through artificial intelligence (AI) in less than two seconds.

“Latency and response times are critical in a fraud detection solution. The time it takes a bank to react to a fraudulent transaction translates directly to how much financial loss can be prevented. The sooner the detection takes place, the less the financial loss,” the company wrote.

This AI model works within Microsoft Azure and creates a user behavioral profile, evaluate transactions and define an action to be taken. This behavioral-based AI approach is more responsive than rules-based or other approaches in changing fraud patterns, says Microsoft.

Microsoft explain the architecture around the model involves three main components Azure Functions, Azure SQL, and Azure Machine Learning.

Furthermore, the platform is based on three factors: “Engineering resources to create customer profiles and accounts,” “Azure Machine Learning to create a fraud classification template,” and “Azure PaaS services for real-time event processing and end-to-end workflow”, Microsoft stated.

To help understand more about the architecture behind this AI solution and what it could achieve, Microsoft has published a Mobile bank fraud solution guide. The guide explains the logic and concepts and gets you to the next stage in implementing a mobile bank fraud detection solution.

You can download the Mobile bank fraud solution guide HERE.

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