ZIMBABWE: Financial Institutions Under Threat from Credit Card Fraud, Researchers Develop Cutting-Edge Solution to Combat Problem

The Growing Concern of Credit Card Fraud

Credit card transactions have become a norm in Zimbabwe’s e-commerce landscape, with many financial institutions adopting this payment method. However, this convenience comes at a cost as credit card fraud attacks are on the rise, threatening the security of these transactions. Financial institutions that have invested heavily in this payment method are finding themselves vulnerable to fraudulent activities.

The Solution: A Distributed Application for Detecting and Preventing Fraudulent Activities

In response to this growing threat, researchers have developed a distributed application designed to detect and prevent fraudulent activities in financial transactions. This innovative solution uses deep neural networks, specifically:

• Hidden Markov Models (HMM): used to generate the spending profile of a cardholder
• Multilayer Perceptron (MLP): classifies transactions into suspicious and non-suspicious categories

The researchers were unable to obtain a real dataset from a bank due to confidentiality concerns, so they created a simulated dataset that mirrors a typical bank’s transaction data.

The Benefits of the Solution

The development of this solution comes at a critical time for Zimbabwean financial institutions, which are grappling with the increasing threat of credit card fraud. With the ability to detect and prevent fraudulent activities, these institutions can:

• Safeguard their customers’ sensitive information
• Maintain trust in the e-commerce ecosystem
• Protect against financial losses

Overall, this cutting-edge solution has the potential to significantly improve the security of credit card transactions in Zimbabwe, giving financial institutions the tools they need to combat the growing threat of credit card fraud.