Modernizing Online Application Fraud Detection and Prevention

Consumers today want the capability to make purchasing decisions—and gain purchasing power—through the Internet. In consumer finance,  the ability to apply and get approved for credit online has never been more in-demand, or under greater attack by fraudsters. Because criminals use stolen and false identities to apply for credit, a significant percentage of bad debt is actually due to fraud.

To help companies modernize the fight against identity fraud, Enova Decisions recently hosted a webinar about new trends and tactics. Let’s explore some of what was shared in this webinar.

Two Online Financial Fraud Trends

Before online fraud can be detected and prevented, it must be recognized and understood. For that reason, let’s start with a look at two modern forms of online account and application fraud.

  1. Third-Party Fraud occurs when a fraudster uses a consumer’s information to make a transaction without the consumer’s knowledge. For example, a fraudster can use a stolen identity to apply for credit, access the credit, and disappear. The challenge with detecting third-party fraud is that the fraudster is hiding behind a valid consumer.
  2. Synthetic Identity Fraud is a modified form of third-party fraud and occurs when a fraudster uses a blend of real and fake data to form a synthetic identity that is used to make a transaction. Fraudsters usually start with a valid Social Security Number or other credit identifier like a credit protection number that has been stolen. Then, a fictional name, address, and other personal information are created. With this fake identity, fraudsters begin building a real credit profile. Usually the fraudster will build up a critical mass of good credit before disappearing with tens or hundreds of thousands of dollars.

While other types of online fraud like account takeover are also on the rise, these two categories represent the bulk of fraud threats that are facing businesses and financial institutions today.

Two Key Ways to Use Data to Fight Online Consumer Fraud

Drawing from our 15+ years of detecting and preventing online fraud in consumer and small business lending, here are two key ways to leverage data to fight online account and application fraud:

  1. Multiple Data Sources. When it comes to data, there’s no silver bullet. By leveraging multiple data sources, internal and external, businesses will have greater success detecting fraudulent activity. For example, some data providers can help you confirm the consistency of a person’s name, phone number, and other personal information. Anomalies should be a red flag. Other data providers can help companies determine where and when an identity first became documented. If the first proof of existence is very recent or is associated with a credit file, this is a red flag.
  2. Network Analysis. Analyzing the data you’ve already collected about an applicant is another effective way to detect fraud. Network analysis is a technique used to evaluate the relationships between data. For example, if an applicant has a phone number that matches the phone number of an existing customer that was found to be fraudulent, this is a red flag.

In order to manage all that data and decision off that data appropriately, we recommend businesses invest in a decision management platform like Enova Decisions Cloud.

“A well-architected decision management platform can handle all sorts of decisions and fraud prevention analysis, and as those actions produce outcomes, information goes back into the platform to create better rules and better models. This is a seamless and scalable way to future-proof your business.”

To learn more about online consumer fraud detection and prevention, explore the full library of Enova Decisions webinars.

Enova Decisions

About

Enova Decisions is an analytics and decision management technology company that was formed in 2016 to to help mid-market organizations make smarter, faster risk decisions about non-prime customers and consumers through big data, machine learning, and the cloud.