Financial institutions are struggling to keep up with evolving fraud tactics. They tell us their top areas of concern are new account fraud, payment fraud and account takeover. However, the most pronounced growth in fraud is in loan products like car loans, mortgages and home equity lines of credit. In our recent webinar, Be a Game Changer: How to Outpace Evolving Fraud, we discussed how fraudsters are evolving and what financial institutions can do to fight back. Mike Urban, U.S. Identity, Fraud and Compliance Product Leader for Equifax, told webinar participants that the best defense is a strong offense. Here are five ways you can help thwart fraud.
1. Diversify your Data
For decades, we’ve used name, address, date of birth and social security number as our main identifiers. While these attributes are still the foundation of our identity, there are new pieces of personally identifiable information (PII) and non-PII data that can provide a broader picture of someone’s identity during the origination process. They include:
- Biometrics records
- Digital behaviors
- Email address
- Phone number
- Device type
- Geo-location information
- Employment records
- Financial records
- Known fraud
- Property records
2. Embrace Analytics
It’s not just about the data you bring in; it’s what you can calculate from that data to use in your analytics. Here are four steps to do that:
- Turn your discrete data into meaningful attributes. For example, you can calculate how long the consumer has lived in their current residence from just an address. From there, determine how many address changes he or she has had. If he or she moved twice in the last year, is that typical behavior for this consumer? You can then look at these attributes and identify anomalies.
- Layer in signals that deepen insights. Look at how consumers use these attributes over time. What does their phone or email usage look like? If the consumer didn’t use their phone for nine months, but made 20 calls in the last month, does that raise a red flag?
- Apply advanced modeling techniques to detect patterns, anomalies and behaviors. This can help you identify high-risk consumers.
- Finally, generate risk and trust scores. This can help you determine if you trust the consumer.
At the end of the day, you want to bring in more customers with less friction.
3. Orchestrate and Optimize
Authentication orchestration can help you make more nuanced decisions about how and when to challenge customers. By bringing in digital and analog data sets from multiple sources, you can look at hundreds of attributes to identify anomalies. Then, create rules to trigger some sort of step-up orchestration with the consumer – whether it’s automated or manual. The orchestration outcomes feed back into the machine learning algorithms in order to allow you to adapt to changes in the fraud environment.
4. Employ Multi-Factor Authentication
Multi-factor authentication verifies a user’s identity by requiring multiple credentials. By creating multiple layers of security, you can be more confident that a consumer is who they say they are. Companies are backing off of knowledge-based authentication (KBA) questions because that information can be found online or through social engineering. The latest solutions incorporate context and behavior, such as where a consumer is trying to access from or at what time of day.
5. Monitor Results & Adjust
This is a critical step because fraudsters are moving faster, and you need to react quickly to the changing environment. It can be hard, but much of the monitoring can be automated. First, implement feedback loops. Then, assess key metrics to determine what’s passing and what’s failing. Ask yourself if there are strategies to minimize them. Finally, use performance data to adjust your fraud strategies, models and business rules. To learn about growing fraud trends, watch our free, on-demand webinar, Be a Game Changer: How to Outpace Evolving Fraud.