Using Analytics to Prevent Auto Finance Fraud

There are various forms of auto finance fraud that can make it incredibly difficult to flag suspicious transactions.

Recently I had the pleasure of presenting in Toronto, at the Canadian Auto Remarketing Conference. While the audience was comprised of a diverse group of stakeholders involved throughout the automotive lending lifecycle, pretty much everyone had one thing in common; they had all the unfortunate experience or had knowledge of some sort of fraud in their line of work.

Like most things, auto finance fraud has evolved over time. As technology becomes more advanced, fraudsters are becoming more innovative, meaning the measures organizations are having to take to protect themselves require innovation as well. You can’t solely rely on checking a driver’s license anymore to verify someone’s identity; it’s simply not enough. Auto lenders are always asking themselves, is this individual who they say they are, or do they intend to pay for the loan.

Fraudsters and legitimate consumers have a number of avenues in which they can now initiate a purchase and each one comes with different challenges for a dealership or lender to navigate—which requires quick decision making.

No matter the industry, the challenges remain consistent. There are various forms of auto finance fraud that can make it incredibly difficult to flag suspicious transactions.

  • True name application fraud is straight forward as it’s a real person and real information. This means it’s simply a bad person, with bad intentions.
  • Manipulated fraud is challenging as the information can seem legitimate but has some small inaccuracies—these could be small misspellings in a name or slight changes to an address. The information seems authentic but makes tracking delinquent payments nearly impossible.
  • Synthetic fraud takes parts of a legitimate identity and attaches fake information to it. This can mean using legitimate personal identification and assigning them to fraudulent people. These cases are also difficult to identify because they look like and act like a true and good individual.
  • Stolen identity fraud, while most often talked about, is actually the least common type. This is when a fraudster fully uses the identity of a stranger, resulting in a damaged credit score and future.

In the days when consumers were required to come into a dealership or bank to obtain financing, judging the validity of an identification made ruling out some of these fraud types a bit easier. An 18-year old man can’t claim to be a 60-year old woman without raising some serious red flags in person—but it’s easier to slip through the cracks online.

No matter the industry, fraud causes real issues. However, the stakes are seriously high when it comes to auto finance fraud. Once that vehicle is driven off of the lot, it’s gone, and lenders have begun to be held increasingly responsible for payments that default.

What this means is it’s becoming increasingly important for any agency responsible for making credit decisions to become more vigilant in evaluating credit worthiness, which means putting analytics to work. A low credit score is no longer the biggest indicator of a risky candidate, but analytic tools can alert lenders to the crumbs of information that are easily overlooked by simple qualifying questions alone.

Auto Lending or Dating?

If you ask me, evaluating application and originations fraud risk is a lot like dating. This might sound crazy but bear with me.

While many people go through phases of their lives where they are looking for something “casual,” for the most part, the goal of dating is to identify a potential long-term partner whom you can build a lasting relationship with. A lending relationship is no different. Lenders and merchants are looking for trustworthy, dependable candidates.  They are lending money to individuals who are committed to the relationship as much as they are to pay back those car loans.

In both scenarios you can expect the truth to be stretched a little bit during the initial stages of the relationship as you’re getting to know one another. Perhaps your potential partner exaggerates their cooking skills on your date, or perhaps your financing candidate exaggerates their income a bit—there’s usually a little white lie somewhere in the equation. In both scenarios, you have to decide what fibs you can live with and which are total deal-breakers.

There are different levels of risk associated with the strategies you choose to vet your potential partner no matter the type of relationship you are pursuing.

  • Referrals = friend of a friend Arguably the least risky method when dating is meeting a potential partner through a mutual friend. In these cases, while you don’t know the individual personally, if the friend setting you up is a trustworthy person, you can assume that they will have used their own judgement to suggest someone who will be compatible with you. The same applies when it comes to lending. If a referral comes in from a strong client relationship or has pre-qualified for an offer, you can assume that the candidate is likely legitimate.
  • In-dealership = speed dating Having a candidate walk from the street into a lending institution is the equivalent of meeting a potential partner through speed dating. You don’t know anything about them entering into the interaction (aside from what you can see physically) and you only have a limited amount of time to make your judgements about them. In this sort of interaction there are some things that cannot be falsified; gender and age (within reason) for example, but there is little time to evaluate more than that before deciding whether the person is a good candidate.
  • Applying online = online dating Online relationships are hard—everyone lies online. According to a recent survey about online dating, 53 percent of people using sites to find partners admit to lying on their profiles and applying online for financing is rarely different. Both scenarios can leave you feeling deceived and disappointed.

When it comes to evaluating risk for an organization though, online applications do have benefits. While it is easy for fraudsters and scammers to lie online, they also leave many breadcrumbs, which if properly monitored, can alert an organization to red flags. Many of these breadcrumbs—like addresses and IP addresses not lining up or registering using brand new email addresses—might not be alarming on their own but can alert an organization to some big issues if analytics are properly being utilized.

In dating or finding reliable customers, there is some effort involved. You can’t expect Mrs. or Mr. Right to come strolling up to you at the grocery store without taking measures to meet the right people with the right qualifications.

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