The importance of AI fraud detection in banking

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Perspectives of the Banking CIO | Friday 03 September 2021

Machine learning is used to prevent transactional fraud before it happens. This not only protects customers from fraud, but also minimizes or eliminates friction for customers whose transactions have been detected incorrectly.

Frémont, California: Banks and financial organizations are naturally prone to fraud and scams, so detecting illegal activity is not an option. As the use of digital banking apps and online shopping increases, steps must be taken to detect and prevent fraud. One of the issues facing financial institutions is that fraud can take many forms. Many banks receive a large number of false positives per day, which are usually reviewed manually. However, in doing so, banks risk hindering customers who are attempting to make legitimate transactions.

Machine learning is used to prevent transactional fraud before it happens. This not only protects customers from fraud, but also minimizes or eliminates friction for customers whose transactions have been detected incorrectly. Simple apps only ask for a few personal details, such as payday advances, credit cards, and set up a direct deposit account. This facilitates application fraud. If a thief obtains sensitive information such as a social security number, they can complete an application and cause significant harm to the victim.

Mortgage fraud is perpetrated not only by professional cybercriminals, but also by industry insiders such as bank agents, brokers, appraisers and other associated professionals. These crimes are usually carried out for financial gain, in which a person takes advantage of the mortgage financing process to steal money from homeowners or lenders. By detecting fraudulent activity early in the process, AI can help fight and defeat app fraud. Algorithms can look for links between credit card and loan applications and monitor newly opened accounts to prevent financial harm before it happens.

While money laundering isn’t always easy to spot, AI’s ability to track spending and depositing patterns over time can alert employees to suspicious activity and prevent payments from being finalized. Additionally, algorithms can use a variety of data sources to uncover deviations from usual patterns, including origins of transactions, final destination, and more. The goal is that AI can help ensure payments are made voluntarily and reduce the number of false positives that traditional fraud detection approaches can produce.

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