When, how and why should auto and equipment finance lenders deploy AI?

In this webinar hosted by Asset Finance Connect and sponsored by NETSOL Technologies, three practitioners with hands-on AI deployment experience share what actually works and what does not when integrating artificial intelligence into lending operations powered by NETSOL's Transcend Finance platform. Moderated by Richard Huston, founder of VAMOS and AFC's AI advisor, the session brings together Dario Morelli, VP of AI at NETSOL Technologies; Tony Lynch, founder and CEO of carpass.ai and entrepreneur in residence at Toyota Financial Services; and Andy Trimmer, Head of Technology at Simply, to deliver a grounded, practical discussion designed for lending professionals building or refining their AI roadmap.

About this webinar

The gap between AI ambition and AI execution is widest in regulated, data-intensive industries, and asset finance sits squarely in that category. Lenders have access to substantial volumes of historical data, established credit processes, and complex regulatory obligations, all of which create both the opportunity and the constraint for AI adoption. The challenge is not whether AI can add value in lending operations. It demonstrably can. The challenge is deploying it in a way that is practical, incremental, and aligned with existing business goals rather than requiring wholesale infrastructure replacement.

This session cuts through the hype. The panel shares direct experience of AI deployment across credit underwriting, document extraction, customer engagement, and portfolio management, covering both the automotive lending and equipment finance solutions sides of the market, to show what responsible, high-value AI adoption looks like in practice for lenders across both sectors.

What you'll learn

This session is built for technology leaders, heads of credit, and senior operations leads at auto captives, banks, and independent finance companies evaluating where and how to deploy AI across their lending operations. It covers:

• The three critical pillars of successful AI adoption in asset finance, and why most organisations that struggle with AI are missing at least one of them.
• Why many lenders still start, with traditional tools even when AI options exist, and what practical steps bridge that gap.
• Real-world examples of AI delivering measurable business impact across credit decisioning, document processing, and customer communication.
• How to keep humans in the loop in risk-sensitive lending decisions while still capturing AI's efficiency and accuracy benefits.
• A practical framework for moving from proof-of-concept to production without disrupting existing operations.

Key themes from the panel

Three themes defined the discussion:

• Treat AI as a tool, not a transformation. The most successful AI deployments shared across the panel were not announced as strategic revolutions. They were quiet, practical integrations, document extraction, email categorisation, contextual data support, that made specific jobs easier without requiring wholesale process change. Andy Trimmer's approach at Simply reflects what the panel broadly agreed delivers the most immediate and direct value: asking "where can we make people's lives easier?" rather than "how can we transform the business?" The AI trends in equipment leasing blog covers the specific lending use cases, from Gen AI to API-first strategies, where technology is delivering consistent, measurable returns across the equipment finance sector.
• Human oversight is non-negotiable in credit. Dario Morelli was direct on this point: full autonomy in credit underwriting is not appropriate at this stage of AI development. The reliability limitations of current language models, combined with the regulatory accountability requirements of lending, mean that augmenting human expertise with AI-generated insights is the right architecture, not replacing the underwriter, but equipping them to make better decisions faster. AI tells you what the data shows, not what to decide.
• Integration is the number one challenge ahead. The panel converged on a clear view of what the next 12 months of AI in lending will look like: not more chatbots, but AI embedded deeply within existing workflows and systems. Dario Morelli highlighted that integration with existing business systems is the frontier and the United Trust Bank case study demonstrates how NETSOL has built that kind of deeply integrated technology infrastructure for a real regulated lending institution in practice.

Going deeper: Related reading

For asset finance leaders building their AI strategy, the whitepaper AI gear shift in asset finance provides a strategic framework for how to approach AI as a business transformation rather than a technology upgrade and what the competitive consequences are for lenders who delay. Asset Finance Connect published a AFC's full session analysis including detailed takeaways from all three panellists and moderator commentary from Richard Huston.