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AI In Banking: Detecting Fraudulent Transactions

By Jacob Wolinsky. Originally published at ValueWalk.

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AI in Banking: CEO of Fraud Management Solution Speaks About Working with 15 Top US Banks


Q2 2020 hedge fund letters, conferences and more

Visa unveiling its powerful AI tool that approves/denies card transactions clearly reflects the growing use of AI in banking. As we turn to deep-learning applications to makes more accurate decisions on behalf of banks experiencing network disruptions, DataVisor, an advanced fraud management solution who is working with 15 of the top banks in the US shares his thoughts.

The Advantages Of Using AI In Banking

Yinglian Xie is CEO and Co-Founder of DataVisor says:

“Fraudulent transactions are extremely difficult to catch because the decision to block a transaction must occur within seconds. Adding to the problem, the number of transactions has increased along with the number of payment channels, and fraudsters take advantage of these complexities, using AI to automate online and mobile attacks. Traditional security technologies are ineffective because they can’t continuously adapt to the new AI-driven threats. Furthermore, rigid authentication schemes can frustrate legitimate customers by adding friction to the customer experience, leading to churn. Advanced AI and machine learning algorithms that leverage holistic data analysis and intelligence across multiple customer touchpoints are the only way to detect and stop fraud early, before damage occurs, and without adding friction to the customer experience.”

What do you think? Is AI just marketing buzz or the real deal? Can it help in banking and fintech to stop fraud? Let us know your thoughts by sounding off in the comments section.

The post AI In Banking: Detecting Fraudulent Transactions appeared first on ValueWalk.

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