Summary
Furkat Suvhanov, COO of Ayan Capital, joins the show to talk about the rise of halal car finance in the UK. He explains why a young, underserved Muslim demographic makes this a growing market, how Ayan prices risk through an asset-backed leasing model instead of interest, and how in-house technology lets the team automate most credit decisions. He also covers Ayan's move into dealer partnerships and its plans to apply for a UK banking licence.

Keywords
halal finance, halal car finance, Shariah-compliant finance, Islamic banking, Islamic fintech, UK car finance, automotive finance, asset-backed leasing, risk management, underwriting, dealer partnerships

Key topics
Growth of halal car finance in the UK
Market potential and demographic insights
Risk management through asset-backed leasing
Technology-driven underwriting and decision-making
Expansion plans, including dealer partnerships and a global outlook

Sound bites
"Car finance is just the beginning."
"We don't charge interest. It doesn't imply that there's no cost for providing this vehicle. So we charge rent."
"We believe that adoption and scale comes from offering competitive pricing, from having technology being able to underwrite customers quickly and having good service."

Chapters
00:00 Introduction to Furkat Suvhanov and Ayan Capital
01:14 Background of Ayan Capital and its heritage in Islamic fintech
02:03 Why start with car finance in the UK market
03:03 Market growth and demographic insights in the UK
03:43 Underserved Muslim demographic and market opportunity
04:20 Current landscape of halal car finance products in the UK
05:10 New product launches: breakdown plans and instalment options
06:01 Furkat's journey from real estate to Islamic fintech
07:39 Speed of licensing and regulatory environment
08:35 Risk management and asset-backed leasing model
10:11 Use of data and AI in underwriting and decision-making
12:08 Market size, growth projections, and future opportunities
14:14 Early-stage growth and team expertise
15:24 Dealer partnerships and distribution strategy
17:18 Comparison with US market and global expansion
18:07 Advice for auto finance entrepreneurs and service quality
19:26 Resources and contact information for further engagement

Guest links
Furkat Suvhanov on LinkedIn: https://www.linkedin.com/in/furkat-suvhanov/
Ayan: https://www.ayan.co.uk

Summary
Peter Smith, founder and managing partner of The Lion Partnership, draws on a 30-year automotive career to explain how luxury retail thinking can transform volume dealerships. He covers the hidden cost of staff turnover, why the industry's 30-day measurement cycle holds it back, how AI and new retail models are disrupting the market, and what dealers need to decide now to stay in the business.

Keywords
automotive, luxury retail, dealership, AI, disruption, customer retention, data analytics, automotive innovation

Key topics
Luxury vs. volume retail strategies
Customer retention and lifetime value
Impact of AI and technology in automotive
Disruption and future trends in automotive retail
Data analytics and decision-making in dealerships
The importance of relationship management
Innovative dealership models like Ford Signature 2.0 and Carvana
Challenges of vendor proliferation and market transparency
Turnover costs and operational efficiency
The future of mobility and shared ownership

Guest links
Peter Smith on LinkedIn: https://www.linkedin.com/in/peterwsmithlion/
The Lion Partnership: https://www.lionpartnership.com/

Sound bites
"When you buy your first Porsche, they're already designing your seventh."
"Most dealerships are losing $2 million a year just in turnover costs. And they don't see it."
"We won't play the long game in this business because we're measured on the short game."
"So we fight for acquisition rather than retention."
"It's not about cars. It's about economics."

Chapters
00:00 Introduction and guest background
02:23 Customer lifetime value and brand loyalty
04:37 Market size and vendor visibility challenges
07:18 Data deciphering and operational insights
10:07 The problem with 30-day performance measurement
12:25 The importance of specialised hiring and long-term planning
14:10 Innovative dealership models like Ford 2.0
15:32 The success of Carvana's distribution and customer experience
16:40 The efficiency of digital transactions and fast ownership
17:45 Upselling through pre-knowledge of aftermarket options
19:14 Small dealerships outperforming large ones through relationships
22:23 The importance of relationship-building in sales
24:36 Value-based purchasing and customer loyalty
25:15 Customer retention as a key to long-term success
27:16 The future of dealership formats and technology
28:49 Mobility changes and shared ownership trends
30:31 Chinese brands' rapid growth and market share
32:17 Data security, privacy, and geopolitical concerns
33:16 Advice for dealerships preparing for the future
33:49 The importance of strategic investment and relationship focus

Summary
Jonny Clayton founded Oodle Car Finance and is now building Bobi, an AI car buying agent. He explains why product discovery is already moving into large language models, what that means for marketplaces like Auto Trader, and why he wants dealers to pay on success rather than listings. He also covers how finance fits into an agent-led journey and what he calls "vibe retailing".

Keywords
car buying, AI, automotive retail, digital transformation, car finance, online car marketplace, dealer strategies, customer experience, AI agents, future of auto industry

Key topics
The evolution of online car discovery and finance
The role of AI agents in car buying
Disintermediation of marketplaces and dealers
Building trust and provenance in digital transactions
The impact of large language models on customer experience
Future of dealer and customer interactions
Integration of finance and car selection through AI
Changing role of marketplaces like Auto Trader

Sound bites
"I think the way that people buy cars is going to change dramatically."
"We want to get paid on success, not on listings."
"You've got to skate where the puck's going, not where it is today."

Guest links
Jonny Clayton on LinkedIn: https://www.linkedin.com/in/jonathan-clayton-5b09971a/
Bobi: https://www.bobi.car

Chapters
00:00 Introduction and Jonny Clayton's background
01:02 Transition from structured finance to the auto market
02:13 Market opportunity in UK used car credit
03:22 Moving online in car discovery and finance
04:55 Designing customer journeys and platform architecture
06:12 Market shift towards online brokers and disintermediation
08:43 Future of car buying in three years
09:36 AI-driven discovery and transaction layers
11:44 Transforming the customer experience with AI agents
13:27 Creating trusted dealer relationships
16:02 Dealer engagement in AI-driven car buying
18:56 Marketplaces' evolving role and product catalogues
21:14 Disintermediation and direct dealer-to-customer connections
24:53 Efficiency gains for dealers through AI
27:11 Finance integration and success-based dealer models
30:50 The future of AI in automotive retail
35:06 Building engaging, intuitive car discovery experiences
36:49 Vibe retailing and personalised customer journeys
37:34 Adoption timeline and future outlook
38:09 Jonny Clayton's advice for industry players

Summary
Philip Nothard of Cox Automotive explains how data is reshaping the automotive industry, and why the hard part is no longer getting hold of it but reading it properly. He covers the shift toward real-time analytics, where the blind spots still sit, and what AI can and can't be trusted to decide.

Keywords
automotive data, real-time analytics, AI, vehicle remarketing, market insight, retail demand, electrification, data governance, data ecosystems

Key topics

• The shift from retrospective to real-time data
• Why interpreting large data sets is the real challenge
• How lenders and valuation providers have matured
• The case for end-to-end integration across the sector
• Macroeconomic pressure on vehicle demand and pricing
• AI, data quality, and decision-making
• Blind spots in today's automotive data ecosystems
• Where connected, real-time data goes next

Sound bites

• "Combining expertise with vast data is the biggest shift."
• "Better data doesn't automatically mean better decisions."
• "Visibility of actual retail demand is key."

Chapters
00:00 Introduction
01:14 The biggest change in data use over 30 years
02:34 From data shortage to data abundance
03:34 How different sectors have progressed
05:28 Decision speed versus genuine understanding
07:56 The biggest blind spots in automotive data
09:26 Macroeconomic factors and real-time consumer demand
11:16 Why the industry still leans on averages
12:58 Prioritising retail demand and transactional data
14:39 COVID-19 and the market shifts since
16:20 The risk of misreading demand
18:34 What AI can and can't do with automotive data
19:56 Governance, transparency, and explainability
21:29 Balancing human judgment with AI
23:43 What a connected automotive data ecosystem looks like
25:03 Why data quality and interpretation decide who wins

Summary
Jared Dryer explains how OnPath Credit Union approaches auto lending automation, decision engines, and member loyalty. He makes the case that decision speed is the real competitive lever in indirect lending, and that the data you feed the engine matters more than the engine itself.

Keywords
auto lending, decision automation, credit unions, member loyalty, risk management, decision engines, auto decisioning, underwriting, secondary market, digital banking

Key topics

• Auto lending automation and decision engines
• Member loyalty and retention strategies
• Risk management and underwriting in auto loans
• How decision speed shapes dealer relationships
• Using data analytics for credit decisions
• Where the growth is in the auto lending market
• Secondary market participation and liquidity management

Sound bites

• "Auto lending is our bread and butter."
• "Speed of decision gives us a competitive advantage."
• "Automated decisioning can be a daunting task, but it's achievable."

Chapters
00:00 Introduction and background
01:24 Jared's route into auto lending and decision automation
02:17 How auto decisioning evolved at credit unions
03:18 Why OnPath has a lower auto denial rate
04:16 The case for comprehensive data in auto lending
05:36 Loyalty and long-term member relationships
06:40 Growth of indirect auto lending at OnPath
07:40 Decision speed as a competitive advantage
09:01 Market opportunities as lending standards tighten
10:26 Member lifecycle and long-term engagement
11:14 Digital tools for member self-service
12:35 Handling swings in vehicle collateral value
14:04 Pricing and underwriting against member history
15:40 Depreciation and vehicle value considerations
16:35 Member behaviour and debt management insights
17:49 Advice for automating auto lending decisions
19:17 Introducing Decision Engine Labs

Summary
David James, founder of Total Car Check, digs into vehicle data, fraud prevention, and where automotive data integration is heading. He explains how democratised data is changing the way people buy cars, and why trust and transparency matter more than volume in a vehicle history report.

Keywords
vehicle data, car history checks, automotive fraud, data democratisation, EV data, API integration, vehicle provenance, car buying tips

Key topics

• Vehicle data sources and the challenge of integrating them
• Detecting and preventing fraud in the automotive industry
• How data democratisation and APIs changed the market
• Verification challenges in vehicle provenance
• Emerging trends in EV data and consumer transparency

Guest
David James

Sound bites

• "The industry as a whole was gatekeeping access to data."
• "Everyone's working hard to outwit each other in terms of fraud."
• "Your love of certainty will ruin your outcomes."

Chapters
00:00 Introduction to David James and Total Car Check
02:09 Industry gatekeeping and data accessibility
04:23 Improving customer experience by remixing data
07:36 Simplifying data for consumer trust
09:30 Range anxiety and real-world EV data
11:30 Volume of vehicle checks and industry impact
12:14 The freemium model and data accessibility
13:00 Estimating the UK vehicle population
14:10 Remixing data and AI advances
15:16 Fraud types and evolving criminal tactics
17:03 Cyber fraud and credit card risk in vehicle checks
18:12 Vehicle cloning and fraud detection
19:38 B2B data access and industry applications
21:02 The future of API-driven automotive solutions
22:21 Dark matter developers and custom APIs
23:47 AI and rapid prototyping in data services
25:45 The quiet growth of bespoke data solutions
27:24 Regulatory and ethical considerations in data sharing
28:20 Entrepreneurial spirit and experimentation
29:25 Practical tips for car buyers

Summary
Dave McKay has spent 30 years in automotive data — a career that started, improbably, in music. He walks through what he's learned about collecting and connecting data across the automotive and insurance industries, and argues that the biggest wins come from understanding what customers are actually trying to do rather than from gathering more data.

Keywords
automotive data, auto insurance, data integration, customer insights, market strategy, ADAS, electric vehicles, internet data sources, data gaps

Key topics

• What data has changed in the automotive and insurance industries
• Challenges and opportunities in collecting and integrating automotive data
• Why understanding customer needs comes before applying data
• The shift from traditional data sources to internet-based ones
• Transparency and collaboration in data-driven decisions

Sound bites

• "Get out of the way of the data."
• "I lived in the holes that were in the data I had."
• "Internet data has become a massive resource."

Chapters
00:00 Introduction and guest background
01:17 From music to automotive data
02:15 Lessons from music and an early career in advertising
03:00 Moving into the automotive industry
04:22 Understanding data flow and why perspective matters
07:29 Learning the craft at Allison Fisher International and J.D. Power
09:55 Presenting to OEMs and making insights land
11:52 Transparency and honesty in data sharing
13:03 Joining MarketCheck and focusing on customer problems
15:29 Connecting data sources into valuable products
20:15 The biggest surprises and blind spots in automotive data
22:19 How data collection shifted to internet sources
27:49 Opportunities across the automotive value chain
37:48 Advice for taking data into new verticals
38:54 Focusing on opportunities, not just pain points
39:36 Leadership, culture, and the future of automotive data

Summary
Bryant Sheehy explains how automotive data can be read in real time to spot market trends, surface investment opportunities, and track the effects of shocks like COVID-19 and policy shifts. A look at how alternative data sources are reshaping automotive market analysis and the strategies built on it.

Keywords
automotive data, market analysis, investment insights, alternative data, real-time market trends, automotive industry, market signals, EV market, dealership data

Key topics

• Why automotive data is so much messier than financial data
• What dealer websites and inventory data reveal about the market
• COVID-19's effect on the EV and used car markets
• Satellite imagery, foot traffic, and other alternative sources
• The role of standardised data in investment decisions
• Where smaller funds can compete on analytics
• First-mover advantage in automotive data
• Using market data to anticipate stock movements

Chapters
00:00 Introduction and background in data and finance
01:20 From financial markets to automotive data
02:21 Data standardisation: automotive versus finance
03:21 The fragmentation of dealer data
05:23 What COVID did to MSRP and market dynamics
08:51 Tracking shifts daily instead of quarterly
11:44 How alternative data evolved in financial markets
13:23 Predicting performance with foot traffic and satellite data
14:14 Real-time inventory and sales data in investment analysis
18:21 Standardising alternative data sources
20:32 Optimal car placement and valuation models
22:04 Where the opportunities are for investors
24:11 First-mover advantage in automotive data
24:47 Building an investment thesis on automotive data