How real-time data and AI can be used to optimise the auto trade cycle

Summary

“Most lenders are drowning in data today – but they’re starving for insights.” This comment from Eva Kellershof captured the central theme of Finance Connect’s latest webcast, sponsored by NETSOL Technologies: the auto finance industry already has access to huge amounts of data and AI capability, but the real challenge is turning that information into actionable decisions across the trade cycle.

The webcast, chaired by Finance Connect’s David Betteley, brought together Eva Kellershof (NETSOL Technologies), Ian Smith (FinboCX Inc.) and Owen Edwards (Interpath) to explore how real-time data and AI are reshaping trade-cycle management, customer retention and portfolio optimisation.

EV residual values remain the industry’s biggest concern

One of the strongest themes running through the discussion was the continued uncertainty around EV residual values.

Eva Kellershof, vice president of sales (North America and Europe) at NETSOL Technologies, argued that traditional valuation models are struggling to keep pace with rapid pricing changes, evolving battery technology and changing customer demand.

“Historic data is a rearview mirror,” she said. “In a market where Tesla can drop prices by 20 percent overnight, ten years of auction data is simply irrelevant.”

Rather than relying purely on historic auction trends, the panel discussed the growing need for live asset intelligence – including battery health, mileage, telematics and real-time market pricing – to support both underwriting and remarketing decisions.

Owen Edwards, director and co-head of automotive, UK at Interpath, added that software-defined vehicles and rapid battery innovation are creating “leaps” in vehicle evolution, making long-term forecasting even more difficult for lenders and captives.

He also pointed to the pressure created by the ZEV mandate, with OEMs continuing to push EV volumes aggressively to hit targets – a strategy that is itself affecting used vehicle pricing and residual values.

AI is moving trade-cycle management from reactive to proactive

A second major theme was the shift away from traditional end-of-contract management towards continuous portfolio optimisation.

Ian Smith, managing director of FinboCX Inc., argued that most lenders still operate with a highly traditional mindset, waiting until the end of the agreement before engaging customers about replacement opportunities.

“Everybody is waiting to the end of the cycle before they’ve taken action. And that therein lies the problem.”

Instead, the panel explored how AI and real-time data could help lenders identify opportunities much earlier, whether that means spotting customers with positive equity, identifying assets in high demand or recognising when changing customer circumstances may trigger replacement needs.

The discussion repeatedly returned to the idea that lenders should begin managing portfolios more dynamically, rather than relying on fixed finance cycles and static customer journeys.

Kellershof described this as moving from static origination to “dynamic origination”.

“Traditional origination is only a snapshot in time… dynamic origination is almost like a movie.”

The implication is that finance providers could eventually move towards continuously managed customer and asset relationships, rather than relying on fixed 36- or 42-month finance cycles.

Data overload is not the same as insight

While the industry often talks about data shortages, the panel argued that the real issue is extracting meaningful insight from the vast amounts of information already available.

“Most lenders are drowning in data today, but they’re starving for insights,” said Kellershof.

The discussion focused on the importance of actionable intelligence rather than simply building dashboards or collecting more information.

Smith said AI tools are now capable of helping lenders proactively identify risks and opportunities within portfolios in ways that would previously have been impossible.

He described how AI can now identify customers with positive equity positions, vehicles likely to be in strong market demand or customers who may be approaching financial stress – allowing lenders to intervene earlier and more effectively.

“If we’re not leveraging AI within our businesses, we’re missing opportunities.”

AI is already delivering measurable value

One of the more striking findings from the webcast polling was that respondents were split on whether AI is already delivering meaningful ROI or remains more hype than reality.

However, the panel itself was clear that real use cases are already emerging.

Kellershof pointed to areas such as automated document verification, underwriting support, customer servicing and digital journey optimisation as areas where firms are already seeing measurable operational gains.

The panel also discussed how AI voice technology and customer service automation are becoming increasingly sophisticated.

Owen Edwards highlighted examples where AI voice systems are now handling customer interactions outside normal business hours, leading to significantly higher customer engagement and booking activity.

“You’re missing customers out because you don’t pick up the phone.”

The webcast panellists agreed that one of AI’s biggest advantages is its ability to provide continuous engagement and responsiveness, something increasingly expected by customers used to always-on digital experiences.

Regulation remains a major factor

Although the webcast focused heavily on technology and AI, regulation remained an important undercurrent throughout the discussion.

Kellershof argued that compliance cannot be treated as separate from innovation.

“Regulation isn’t necessarily a brake. It’s a design requirement.”

The panel discussed how explainable AI, transparency and compliance frameworks will become increasingly important as lenders begin embedding AI deeper into underwriting, servicing and customer engagement processes.

At the same time, the speakers noted that changing regulation around EVs, tariffs, data ownership and consumer finance continues to add complexity for lenders, OEMs and software providers alike.

Final takeaway

The webcast highlighted that the next stage of innovation in auto finance is unlikely to come from simply adding more technology.

Instead, competitive advantage will increasingly depend on how effectively lenders, captives and OEMs connect customer, asset and market data together in real time – and how quickly they can turn those insights into action.

The discussion also reinforced that AI is no longer a future concept for the industry. The tools already exist. The challenge now is implementation, integration and identifying where AI can genuinely improve customer outcomes, operational efficiency and portfolio performance.

As the panel concluded, the firms that move first from reactive portfolio management to proactive trade-cycle optimisation are likely to be the ones best positioned to improve retention, protect residual values and drive profitability in a far more volatile market.

Watch the full webcast on-demand here.