What Does Mitigating Fraud Look Like? – Part 2

What Does Mitigating Fraud Look Like? – Part 2

February 27, 2020

By Janet Wagner for Card Not Present (Sponsored by Ekata)

CAPTCHAs, 2FA, and KYC are security measures customers can see. But what does mitigating fraud look like behind the scenes? 

In the background, digital platforms use any number of tools and technologies to prevent fraud. Those tools could include machine learning, rules-based fraud models, and identity verification APIs. Online businesses use many of the same tools and technologies, but they use different approaches when it comes to fraud decisions. For example, some companies have systems that make fraud decisions after authorization (post-auth) instead of before authorization (pre-auth).

Many Sites Use Post-Auth Fraud Decisioning

Consumers are usually unaware of the fraud prevention tools running in the background before and after checkout, but notice if their good transactions are flagged as fraud, cards are declined due to error, or if fraud prevention tools slow down the payment process. 

Most sites with a checkout process make fraud decisions after the payment authorization instead of before. And many e-commerce sites use rules-based fraud models to assess risk at checkout. These models are prone to false positives, causing undue friction for some customers. False positives are a serious problem for merchants as 32 percent of consumers will stop shopping at a merchant if their card is falsely declined.

No merchant wants to decline a good customer, so they sometimes take a chance and let the payment go through. But making decisions post-auth is not the best approach to preventing fraud. 

A Better Way: Pre-Auth Fraud Risk Screening

A growing number of companies are using machine learning to automate fraud decisions. They are also setting up systems to assess the risk of transactions before payment authorization. Pre-auth risk screening usually means focusing on fraud prevention at account creation, preventing bad actors from accessing your digital platform in the first place. It means using tools that automatically verify identities at sign-up. 

Pre-auth risk screening is something that every online merchant should implement. And for some online businesses, it’s something that is required because of regulations like PSD2. Assessing risk before authorization and optimizing that process with machine learning enables companies to:

  • Improve customer experience
  • Adhere to regulations like PSD2
  • Affect authorizations positively

With machine learning and pre-auth risk screening, much of the fraud prevention process can be done behind the scenes without adding a lot of friction for customers at sign-up or checkout.

Consumers Want Fast and Secure Digital Experiences

Ninety-two percent of surveyed consumers expect modern digital platforms to provide a fast and frictionless experience, while, at the same time, delivering an experience that is as trustworthy and secure as possible. Consumers don’t need to see every fraud prevention tool your digital platform uses. But they do need to see that your company can protect them from fraud. With machine learning and the right data, companies can gain better control of customer experiences while also fighting fraud. 

Download our report: “Infinite Want: Consumers Demand Speed and Security in the Digital Experience.”

Read Part 1 Here...

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