At the recent White Clark Group conference at the Hilton Tower Bridge in London, the Captives Forum looked at how technology is not only fundamentally changing cars, but also fundamentally changing finance as well. Motor Finance reports on the key discussions and developments

“There has never been anything like the scale or pace of change that we face today. And what’s going on is disrupting just about every industry in every country.”

This was part of the opening address from Brendan Gleeson, CEO at White Clark Group, as he introduced his company’s Auto Captives Summit 2016 in November.

The topics of the conference covered some of the aspects of change which could, ultimately, make some fundamental changes to the car itself, how the vehicle is sold, and – in turn – how finance companies operate.

For Gleeson the biggest, most important innovation to have come about in recent years has been the rise of artificial intelligence.

The most obvious impact the rise of artificial intelligence will have, and has had, is on the use of self-driving cars, which Gleeson described as “a piece of artificial intelligence on wheels”.

How well do you really know your competitors?

Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.

Company Profile – free sample

Thank you!

Your download email will arrive shortly

Not ready to buy yet? Download a free sample

We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below form

By GlobalData
Visit our Privacy Policy for more information about our services, how we may use, process and share your personal data, including information of your rights in respect of your personal data and how you can unsubscribe from future marketing communications. Our services are intended for corporate subscribers and you warrant that the email address submitted is your corporate email address.

Other areas – which maybe are not quite so obviously related to automotive – are image and voice recognition software, such as Apple’s Siri, or the recent launch of Amazon Echo, with its Alexa assistant.

This type of software will have an impact on the automotive space, however, and Gleeson argued that it was in fact already doing so.

As an example of this, BMW in Europe has begun using IBM’s artificial intelligence software, Watson, and is experimenting to see how it could be used to manage some of its customer services, in terms of email traffic.

“We’re going to see more of that,” Gleeson added.

One area in which AI will grow is something Gleeson described as online “intelligence portals”, which he says have to be seamless, end-to-end, simple and intuitive.

“Now the problem with that is that designing for simple and intuitive is the key to digital success. If you can make it simple and intuitive, then you will be successful online. But designing for simple and intuitive, that’s really difficult,” he warned.

One answer, he suggested, is the use of voice interaction, noting some predictions suggest 50% of all online traffic will be by voice interactions in the next few years.

This advanced ‘chatbot’ technology will have other benefits, including making the service feel more personal – assuming the technology is advanced enough, and guaranteeing compliance.

Another area in which AI could help auto finance companies is big data, Gleeson said, adding: “We have seen an emergence of alternative data models for credit scoring, and some of these have proved to be quite aggressive, and quite successful.”

He said traditional credit scoring leaves a small number of statistically as strong variables.  The alternative is big data and artificial intelligence, which can create credit models based on a huge number of weaker variables.

This was the topic of a later speaker, Richard Harris, head of international operations at Feedzai, who looked at how the industry could use machine learning to mechanise and automate processes that used to require manpower.

Looking at Amazon, Harris noted the online retailer knows a huge amount about him, and that he is quite happy for Amazon to know information about him because it makes his life easier, such as predicting what he might buy next.

This type of predictive AI requires computing power, and 10 years ago when Amazon and companies like Google began looking at this, there was a prohibitively high cost in acquiring that computing power. However this has come down substantially; what would have previously cost millions of dollars now costs just a few tens of thousands of dollars, if that, he said.

In the future, this will have a large impact on credit decisioning, and the key to this will be machine learning algorithms.
“In the past,” said Harris, “we built score cards. We built rules to say if you fit this kind of profile or if you live in this postcode or if you have this kind of college degree etc – we put people in buckets.”

Companies collect a huge amount of data on customers, and often the challenge is sifting through all this data to find patterns. With the rise of these machine learning algorithms, it’s now possible to get answers quickly.

As a result, Harris said a company can enter all the data it has on a customer, regardless of whether the data looks useful or not.

“I don’t need to work that out; I’ve got an algorithm that can work out if there is a correlation now. So let’s let the algorithm work out if there is a correlation.

“Just get all the data in one place. Because it’s now quicker and easier just to put all the data in and then work out afterwards what the correlations are going to be.”

He added that there are four key parts to making this effective.

For a start, companies need to stop putting people in boxes, as algorithms are now able to profile people to such a fine level of detail; second, the more data that is entered the better; third, you have to be able to explain a computer’s decision; and finally it has to be in real time.

The millennial customer

Companies looking at these technological solutions often have an eye on the younger generation of customers, either the so-called ‘millennial’ generation, or in some cases the following generation, Generation Z.

According to Robert Reveal, partner at EY in the US, a survey EY conducted of lenders found that, while lenders may focus on millennials, a lot of the concepts have bled into other generational units.

Gleeson also mentioned this topic in his introduction, noting in the US, millennials and Generation Z would account for a combined purchasing power of close to $5trn by 2020.

Not that the two generations should be looked at as one and the same: Gleeson noted that Generation Z is regarded as being more pragmatic, and is actually more interested in face-to-face interactions.

Another insight Reveal was able to offer was that, despite motor finance’s reputation of sometimes being a little conservative, companies were actually focusing on digitalisation to improve the speed and simplicity of their customer touch points.

One interesting change that has occurred compared to 15 or so years ago is in how companies view acquisitions. When the internet and e-commerce was still a lot younger, Reveal said, most companies would sit back and watch the market.

They often would not have something like an innovation budget, and would instead look to acquire models once they had proved successful.

Now, however, he said: “Folks are partnering, they’re investing in parallel; they’re trying a lot of different things in smaller ways, and figuring out what works for them.

“In some cases they are going to acquire some of these folks; in other cases they’ll just establish longer-term agreements with them over time.”


One such technology company which is starting to make an impact is Docusign, which has signed agreements with a number of industry players, including conference hosts White Clark Group.

Although Jesper Frederiksen, vice-president of enterprise sales, EMEA, at Docusign said the company’s founding was a traditional American story of the founder seeing a problem, and finding a fix – in this case the amount of paperwork involved in buying a house – the truth is that e-signatures, such as those provided by the company, are having an increasing impact on the industry.

Looking at the topics that Gleeson, Harris and others spoke about, Frederiksen suggested: “As long as you present me as a partner with a stack of papers when I lease my new car, you can’t do all the other stuff.

“How can you do AI and machine learning and all this stuff if, at the moment of truth with me as a consumer, it’s a piece of paper.”

The company has seen success in recent years, however Frederiksen said it has also seen the reason why companies come to Docusign change slightly.

Originally, the main reason was to see if implementing the technology could save money. Increasingly the first question clients ask now is around the product’s ease of use, and impact on the user experience. On top of this, the ability to provide a more thorough audit trail than paper is another selling point.

While e-signatures are becoming increasingly common in finance agreements, the idea of the blockchain is just starting to be understood. While many think of blockchain as something more related to bitcoins, increasingly people are realising its potential use in increasing digital security and saving costs.

Danny Williams, chief innovation officer at IBM UK, noted that currently, in most supply chains, each organisation will have its own ledger, which allows for inconsistencies. Moving over to a blockchain, which is a distributed ledger, would prevent such inconsistences. What’s more, the blockchain could provide a mechanism for provenance checking.

Giving an example, Williams said: “Imagine if Party A is going to buy something from Party B. They’ll both have a record of that transaction. And then Party A sells it on to Party C, and then that Party sells it on to Party D. Where is the provenance? How do people know that what they’re actually buying is the real thing? And that it hasn’t – if it’s a car – been involved in an accident?

“Imagine if you are the bank, and you’re lending money on the basis of this transaction, what level of reassurance do you have that you’re actually lending against an asset that has the value that people say it has?”

A shared ledger would solve some of these issues – assuming all parties had the correct permissions: Party D will be able to trace the asset’s history all the way back to party A.

Of course, everyone having a permission is not always practical, or indeed ideal, and so companies give and receive permissions. In order to trust this, it’s important to be able to trust the encryption, and Williams assured that blockchain has “incredibly strong encryption”.

Arguably the most revolutionary idea of the day came from John Ellis, connectivity strategist at Ellis & Associates, who outlined his vision for a “zero-dollar car”.

Noting that this did not mean a free car, Ellis suggested that recent increases in the amount of data cars were collecting meant it may soon be possible to subsidise the cost of a car to the point where it cost nothing to the consumer, through the selling of data the car collects.

Quoting a statistic from a friend, Kevin, Ellis noted that he was able to calculate that Kevin and his family of four earned $5,500 in revenue for Google in 2015, just by using the ecosystem. Google and Apple are now looking at the automotive industry as a way of increasing this revenue, he warns.

Explaining where the money could be made, Ellis noted that the sensors in cars could be used to send real-time weather reports to weather companies, reports on road quality to the municipalities, and, of course ,driving data to insurance companies.

Companies such as Google and Apple wish to place their ecosystems in cars so they can access this potential revenue.

This is a threat to the industry, and so Ellis said car companies should be looking to build their own ecosystems so they could use this new revenue stream to subsidise the price of the car.

While this idea might prove to be a threat to captive finance companies in some respects, Ellis said captives especially will be key if auto companies are to build an ecosystem which can survive pressure from the outside world.

“You [the finance companies] are seeing a far broader exposure to tech than most of the guys in the product side of the car companies. They see very car-centric tech; you are seeing a very broad ecosystem of tech,” Ellis explained.

“That combines with business. You’re business-minded: You know how to collaborate and be business-minded.”

There are four key points Ellis noted. First, he said, a mobile platform is, at its core, a piece of hardware with some API technology added. OEMs already have the hardware, and some APIs; what they need is a business-minded approach to evolve.

Second, companies should reach out to third-party companies building dongles, and get them to integrate into vehicles.

Third, companies need to reach out to concerned parties, but not as a product company, but as a mobile platform service company.

Finally, the finance companies need to teach their parent brands this is serious, and that the days of selling a car and forgetting it are over.

Companies need to find a way of reaching customers for more money for added value.