Secure Transactions with Transaction Risk API

What Stage of Identity Verification Are You At?



The rising number of mass data breaches and the increasing sophistication of fraudster networks keep even the savviest fraud managers awake at night. The recent surge in ecommerce activities has brought with it a rise in card-not-present (CNP) fraud. According to a new report from Forrester, merchants lost an estimated US$35.54B globally – and that was just in year one of the pandemic. More than ever, online businesses face mounting pressure to thwart criminal activity without rejecting good transactions. Never has the call for a greater use of identity verification and fraud management efficiency metrics been louder.

Balancing fraud prevention and a streamlined customer experience is a delicate balancing act. Erring too far in either direction can have negative consequences. Organizations with overly aggressive fraud policies risk losing the lifetime value of good customers. This happens when customers are mistakenly rejected or when they abandon their transactions due to friction. Meanwhile, companies with policies that are too lenient can result in unacceptably high financial losses and a damaged reputation.

Sophisticated businesses are addressing this challenge by putting more advanced fraud prevention measures in place with mature identity verification strategies that utilize Big Data, machine learning, and global data linkages and insights. These evolved practices help them more readily differentiate between good customers (and fast-track their transactions) and potentially fraudulent actors.

We find it helpful to discuss mature identity verification as a progressive four-stage scale with our customers. The higher you rise up the scale, the greater the ability to reduce fraud, the need for manual review, and the rejection of good customers. So how are the stages of identity verification defined?

Stage 1: Not currently performing identity verification.

These organizations either do not perceive a need (because they have not been the victim of confirmed identity fraud) or do not know how to perform identity verification.

Stage 2: Attempting identity verification, but not doing it consistently.

These organizations are utilizing a small percentage of available data. However, they are not examining the linkages between the data they use. Instead, they rely heavily on manual review to approve or deny transactions.

Stage 3: Consistently using identity verification, incorporating a larger proportion of available data, and experimenting with data linkages.

Often these organizations are on top of fraud management. They are highly motivated to reduce scams and to increase the speed and efficiency of the approval process. They are now driven to consider increased automation.

Stage 4: Have embraced holistic identity verification.

These organizations are verifying multiple data elements and linking them. They have embraced automation.

In early 2018, Ekata commissioned a survey of 150 North American online merchants and lenders of varying sizes to evaluate their level of identity verification. Respondents were asked about their current practices, motivations for – and perceived obstacles to – adopting more sophisticated identity verification practices, and the measurable business benefits that accrue for organizations as they become increasingly mature in their approach to identity verification.

Naturally, any report commissioned pre-pandemic would lack the emphasis needed for scalability. Preventing sophisticated fraudsters in this evolving digital-economy from taking advantage of your platform requires a multi-layered approach to identity verification. This means a fraud management system and identity validation solution that is all encompassing; combining rule-based decisioning and machine learning to maximize fraud prevention efforts.

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