BOISE, ID–Kount, the leader in AI-driven fraud prevention, today introduced the most comprehensive solution to protect digital businesses from criminal and friendly fraud. Kount’s Friendly Fraud Prevention Solution features Visa Merchant Purchase Inquiry (VMPI), a component of Visa’s Claim Resolutions process, which helps businesses save the sale, prevent chargebacks and reduce dispute timeframes. Kount’s solution is the industry’s first to quickly and accurately identify both criminal and friendly fraud, helping companies achieve positive results including improved revenue, customer experience, operational efficiencies and customer retention rates.

Kount’s award winning, AI-driven digital fraud prevention emulates an experienced fraud analyst and protects against criminal fraud in a highly accurate and scalable manner by combining unsupervised and supervised machine learning with a universal data network built over 12+ years and billions of transactions. Together with Kount’s Friendly Fraud Prevention Solution featuring VMPI and Kount’s advanced data analytics and partnerships, Kount helps businesses distinguish between criminal fraud, friendly fraud and legitimate disputes.

Brad Wiskirchen, CEO

“Many businesses struggle with distinguishing friendly fraud from criminal fraud, limiting their ability to effectively fight chargebacks and deliver an optimal customer experience,” said Brad Wiskirchen, CEO, Kount. “Through Kount’s Friendly Fraud Prevention Solution, digital businesses can now speed up case resolution and gain improved chargeback data to optimize their fraud prevention strategy.”

Friendly fraud, which results in chargebacks and lost revenue due to disputes by real customers, can account for 40-80% of a business’ fraud losses. Kount’s Friendly Fraud Prevention Solution offers a comprehensive tool set including VMPI, advanced analytics, and representment and alerts through partnerships. VMPI allows issuing banks to request information directly from businesses to help cardholders recognize transactions before proceeding with a dispute. Kount’s solution makes it easy for businesses to take advantage of the program and reduce chargebacks, reduce dispute timeframes from weeks to seconds, and build customer loyalty through improved communication and faster resolution.

“Customer experience is key for both merchants and issuing banks, and friendly fraud poses a unique challenge, especially for those who operate in digital or remote channels,” said Krista Tedder, Director of Payments at Javelin Research*. “More effective information sharing between issuers and merchants can help consumers quickly identify purchases to prevent disputes while also providing issuers the insights they need to identify friendly fraud claims.”

A key component of Kount’s Friendly Fraud Prevention Solution is Datamart, which delivers advanced data analytics and empowers businesses to look at qualifiers such as email address, product, and data types. By having the ability to classify, segment, and address different types of fraud, Kount enables businesses to gain clarity into legitimate customer disputes, which are often due to product quality deficiencies, merchant error, or service gaps. Armed with this information, companies can isolate legitimate disputes from friendly fraud and use the rich dataset to improve the success rate of chargeback representments. Businesses can then focus on addressing operational inefficiencies, allowing them to increase revenue and deliver a better customer experience.

The solution is simple to set up, and implementation does not require any additional technical integration for customers who already rely on Kount’s AI-driven fraud prevention to drive business outcomes and protect their digital innovation. With the addition of its Friendly Fraud Prevention Solution, Kount offers the most comprehensive fraud prevention solution in the industry, protecting against both criminal and friendly fraud.

Previous post

Mogo launches newly designed mobile app and introduces Canadians to the 4 habits of financial health

Next post

EMV snapshot