BURNABY, British Columbia and EDMONTON -

Vladimir Kovacevic, founder and chief technology officer at Inovatec Systems, laughingly says Apple and Google have ruined it for all of us.

That was how an enlightening interview with the tech-minded entrepreneur began. Kovacevic helps run Inovatec, which provides lending infrastructure and cloud-based solutions for the automotive finance and lease sector, as well as a variety of additional markets.

“They’ve (Apple, Google and other tech giants) created such an amazing product and such amazing experiences that, you know,  is becoming the norm. That’s what people expect,” Kovacevic said.

That expectation of convenience has carried over into all aspects of consumers’ lives, including processes that used to be cumbersome or difficult, like getting a mortgage or buying a vehicle. 

“Younger people are basically saying, ‘Well, why is this (buying a vehicle) so hard?’” Kovacevic said. “It shouldn’t be this hard. Surely there is an easier way.”

And according to Evan Chrapko, co-founder and chief executive officer at Trust Science, “The credit underwriting industry is ripe for transformation” — contributing to what seems to be a prime environment for innovation. 

Alternative data & the changing credit-health profile

Part of the aforementioned transformation in auto finance and credit underwriting, in general, includes the use of alternative data in the lending decisioning process. This trend, in addition to the rise of AI, automation, big-data mining and machine learning, are changing auto finance.

These days, creditors and loan officers aren’t just using statistical analysis; they are looking at consumers’ past experiences and trying to analyze their risk profiles beyond traditional data sources.

One of the companies front and center in this space is Trust Science, whose website says it combines alternative subprime loan data and data-driven underwriting to make smarter, more profitable lending decisions.

Trust Science recently announced an integration with Inovatec, and is also integrated with LOS and LMS systems like AMS, Vergent, Infinity, defi Solutions and Shaw.

“Alternative data provides two things: 1) the means to reliably score thin-file and no-file borrowers; 2) the means to get more accurate insights based on loan type, borrower and market conditions,” Chrapko told Auto Remarketing Canada. “Alternative data provides insights into more facets of person, both negative and positive. This is what leads to more accurate assessments of a borrower’s capacity and propensity to repay a given obligation.” 

TrustScience was able to come up with their own risk score that’s not solely based on historical credit performance. The company finds that more and more, consumers aren’t fitting into the “old methods” of gauging credit health.

Social media, mobile-app usage, differences between generations (e.g. millennials vs. Gen Z) and even immigration and market changes are contributing to this shift.

“You can’t use a static scorecard in a fluid dynamic big-data world,” Chrapko said.

Kovacevic pointed out the traditional methods of gauging credit health are still there: your credit bureau scores, etc. That said, although he asserts these methods will never go away, “if you’re only using that, then I think you’re sort of missing the boat.”

Interestingly, consumers themselves may be the ones driving the change to fresh methods, through the adoption of apps like Credit Score Check and Pre-Qualification, for example.

These two mobile apps, in particular, address challenges with the “old method,” known as “credit last” in the industry,” Chrapko said.

“This is where a consumer is ready to buy, with vehicle, incentive and payment option chosen, and learns their credit is invisible or doesn’t qualify for incentive APR, lease option or affordable payment,” Chrapko said.

One thing that is particularly interesting when it comes to the use of alternative data is how consumers seem to be very happy to trade privacy for convenience, Kovacevic said. 

“So, what I’m seeing is more and more of these services that are making it easy for me as a consumer to do something and in exchange, it reveals a part of my behavior and a propensity to a company that’s providing that service,” he said.

And that’s why, for example, some services can be free or discounted on the Web these days — “They’re monetizing more on the data they’re getting from me as a consumer,” Kovacevic said.

Alternative data use seems to have government support behind it, as well. Regulators are weighing in and being supportive of innovation in the space, Trust Science leaders said. 

A Dec. 3 press release from the five major regulators in the U.S. (Federal Reserve Board, the Consumer Financial Protection Bureau, the Federal Deposit Insurance Corporation), the Office of the Comptroller of the Currency and the National Credit Union Administration)  jointly advocates for the use of alternative data to empower and serve more consumers.  

Where does AI come in?

“What we are seeing in the market is that there is more and more modeling done with the assistance of AI,” Kovacevic said.

AI and automation technology help to sort through the huge amounts of data available today and make sense of it, as well as draw connections and find value.

“The advances of machine learning and artificial intelligence are seminal to fintech. Finance is all about numbers and data; any related tech needs to be driven by big data. Big data underpins machine learning and AI,” said Chrapko.

No longer do you have to rely on the “best guess” to determine yay or nay on a loan application, the Trust Science leader said.

Instead, “Machine learning credit scoring models use loan data that is relevant and specific to the borrower and your business,” he said.

And although some consumers may be wary of AI and machine learning models, the technology is growing the potential for loan approval. 

“AI and machine learning can also assess thin-files and no-files. That means underwriters give out the right loans to the right people, and the right people can benefit from loans,” Chrapko said.

AI and the dealer

As for how Inovatec is using AI, in particular, Kovacevic said his firm is “leveraging AI to help us better understand a truly direct indirect lending scenario, where you have a credit analysis, have a discussion with a dealer — you know, working a deal, trying to put it all together.”

AI is now used to analyze those conversations and notes sent back and forth through Inovatec’s Compass Direct Portal, a framework which can be used as a lead origination channel.

So, when consumers go to a dealer’s website, they can use this tool to transition seamlessly to a full credit app without ever having to leave the dealer’s website.

“And then a dealer can pick it up and carry on from there,” Kovacevic added. 

For the consumer, they can start their shopping process on the dealer website, fill out the app, get conditional approval or full approval, and then when they walk into the dealership; “all of it is there.”

“So, we have a whole product that enables that sort of transition from digital to real life and back to digital,” Kovacevic said.

And again, AI plays a large role.

“We can actually have AI analyze the conversation and alert and highlight a credit manager on our side to basically tell them, ‘Hey look, this is a negative conversation. Something is not going well,’” he explained. “AI might not yet be able to tell you exactly what the problem is, but it can alert you to an issue.”

Kovacevic said that AI is slowly working its way into the more operational side of the auto business, like dealerships, helping manage the flow of work, and alerting dealership personnel to potential issues or lending situations that might need more attention to get approved.

Kijiji’s Leanne Kripp, head of autos, touched on yet another way AI is being integrated into the consumer process, this time via Kijiji’s Audience Engine.

“Audience Engine combines sales data — based on over 200 categories on Kijiji and Kijiji Autos — with insights from Facebook and the Google Display Network, which means that dealers can display their inventories to the people who are actually looking to purchase a vehicle, when they’re considering that purchase,” Kripp said.

The industry has known for some time now that a vehicle purchase is something that consumers “consider carefully,” Kripp pointed out. And while the internet and wealth of information available has brought this process down to seven weeks, as shown in the third annual Kijiji Autos Annual Dealer Research Report, that’s still a considerable amount of time to be marketing a consumer.

“We’ve also known for as long as this industry has existed that a car purchase tends to fit in with what we call ‘life-moments’: having a child, moving to university, a new house, retiring or that very first job,” she added.

AI, she said, “provides for the industry a new, more effective and efficient way to reach Canadians who are wanting to purchase a car … We’re excited to see how dealers can develop in 2020 by harnessing the power of AI and tools like Audience Engine.”