How to defriend friendly fraud chargebacks – freshly-minted best practices

When companies are tackling fraud, it can be a challenge to distinguish between criminal fraud, friendly fraud, and legitimate disputes. Yet, the ability to quickly and accurately segment fraud can help businesses do more than mitigate their fraud challenges – it can also improve operations and increase revenue.

Kount, the AI-driven digital fraud prevention solution provider, offers the industry’s first complete solution to accurately uncover and address the following:

• Criminal fraud: fraud from stolen credit card numbers or other types of financially malicious activity that result in chargebacks;
• Friendly fraud: when a consumer makes a purchase with their credit card and then disputes the charges with the issuing bank rather than requesting exchanges or refunds from the merchant. In some cases, the customer intends to dispute the payment and keep the goods or services, but more often, there may be a misunderstanding. For example, a consumer may not recognise a charge due to a confusing billing descriptor, or they may have forgotten a spontaneous purchase, or the purchase was made by a family member;
• Legitimate disputes: authentic customer disputes and chargebacks resulting from these, for example, a product arrived damaged, late, was misrepresented in sales materials, or lacks customer service contact information.

Deflecting friendly fraud requires technology and tools that are often different from those used to protect against criminal fraud. With a fraud solution that includes a complete set of tools for addressing types of fraud and use cases, chargebacks are no longer difficult to isolate and identify, and fraud that impacts a businesses’ bottom line can be addressed.

Identifying criminal fraud

The first step in Kount’s solution is to accurately identify and protect against criminal fraud. Kount’s AI-driven digital fraud prevention solution 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.

For a business with a strong criminal fraud prevention program, friendly fraud can account for as much as 40-80% of a company’s fraud losses. Friendly fraud chargebacks are often classified under the same reason codes as criminal fraud, making them difficult to pinpoint.

After deploying tools for stopping criminal fraud, the remaining chargebacks are primarily friendly fraud, with a much smaller percentage of criminal fraud and legitimate disputes.

Addressing friendly fraud

Kount’s friendly fraud prevention solution includes an integration with Visa Merchant Purchase Inquiry (VMPI) services and advanced data analytics through Kount Datamart, as well as optional representment services through partners.

1. VMPI

With Kount’s integration to VMPI, businesses can immediately begin to deflect friendly fraud chargebacks. VMPI helps issuers and businesses reduce unnecessary payment disputes by allowing issuing banks to request information from businesses to help cardholders recognise a transaction at the time of inquiry. The details provided by the business to the issuer can include information such as customer name, email, shipping address, mobile phone, shopping cart information, and device used. This friction is typically enough to remind the cardholder of the authorised purchase or sway them from any malicious or exploitative intent since they can see their personal data, beyond just the payment information associated with the purchase.

     2. Datamart Advanced Data Analytics

One of the unique advantages that Kount’s solution provides is the depth of data essential for sorting criminal from friendly fraud. A component of Kount’s Friendly Fraud solution is Datamart – a feature that enables the use of advanced data analytics and intelligence so businesses can analyse the remaining fraud by diving deeper into qualifiers such as email address, product, and data types. This helps to surface patterns not easily recognised, and isolate legitimate disputes from friendly fraud. Businesses can rely on the data to take action to further reduce complications from fraud.

     3. Representment

After reducing most of the friendly fraud through VMPI, some disputes will remain. Businesses have the option to use Kount’s data analytics through Datamart to challenge these disputes on their own or engage Kount’s partners for representment services. Kount’s data is readily available to back up these disputes and help businesses resolve them quicker.

Legitimate disputes and business insights

For a business to operate successfully in digital commerce, they need to first address criminal and friendly fraud. Of the remaining fraud, there are often legitimate reasons for the customer disputes. These can include product quality issues, merchant mistakes, service deficiencies etc. The data can help businesses understand the gaps between what is promised and customer expectations and identify the problems that impact business outcomes. Only after addressing criminal and friendly fraud, is to possible to dive deeper in order to understand where and if there are broken links in the business.

Improving business outcomes

Through Kount’s comprehensive Friendly Fraud Prevention Solution, businesses are empowered to look beyond chargebacks to pinpoint how to improve the customer experience, margins, and revenue. Once business challenges are untangled, merchants can address them and increase sales margins, improve user experience, customer satisfaction, and retention rates.