By
Matthew Hearfield
April 1, 2025
Updated
April 1, 2025
As AI reshapes global industries, fintech is leading the charge — and that means new opportunities for talent, businesses, and innovation.
In this episode, Dmytro Voronenko, Co-Founder & CEO of TurnKey Lender, shares how automation and AI are making digital lending as easy as e-commerce, and what that means for companies, job seekers, and underbanked communities around the world.
Listen to the full episode below:
The evolution of Fintech & AI integration
We’ve done some great stuff for larger corporations. That business I founded showed neural networks but it was the beginning of 2000 They weren't as sexy as they are right now.
Dmytro began his career working in traditional banking and AI research, particularly in neural networks before they gained mainstream attention. His unique background led him to recognise early on the potential of combining AI with financial systems, especially in areas like credit scoring and automation. This eventually inspired him to found and lead companies that bridge AI and lending, long before these technologies became buzzwords.
He’s seen firsthand how AI evolved from experimental modeling into an essential layer for automation, especially in financial decision-making processes. His entrepreneurial journey was shaped by the belief that technology could transform the scalability and accessibility of financial services.
Democratising lending: From big banks to small businesses
We were focusing on enabling digital lending, in a way that even a relatively small company or lender can start doing lending similar to e-commerce, a mom and pop shop can open e-commerce website pretty easily.
A core mission for Dmytro’s company was to empower small and mid-sized lenders, not just large financial institutions. His analogy to Shopify democratising e-commerce highlights his belief that any business should be able to offer financial products, especially lending, with the same ease and quality as the biggest players.
This theme speaks to a shift from centralised financial power to decentralized accessibility. By lowering the technical and financial barriers to entry, Dmytro envisions a world where startups and SMEs can function like fintechs.
Embedded lending: Financing inside other services
They embed lending inside of their main business offering, they tell customers, ‘Look, if you buy my service or if you will buy my goods, I will finance you.’
Dmytro introduces embedded lending as a strategic evolution in fintech, where non-lending businesses integrate financial services directly into their offerings. Rather than referring customers to third-party lenders, companies like telecoms, retailers, or healthcare providers can finance purchases or services internally.
This approach not only increases conversion rates and loyalty for businesses but also offers instant financing solutions to customers at the point of need. It's a shift toward contextual, just-in-time credit that's tightly woven into daily life and consumption.
Financial inclusion for the underbanked
A powerful motivator behind Dmytro’s work is bringing affordable, accessible credit to underbanked or unbanked populations. These are communities often left out by traditional banks due to high operational costs or lack of credit history.
AI enables micro-loans and lending models that operate at scale with minimal human intervention, which is critical for reaching lower-income users. He cites examples like small loans in the Philippines and other developing regions, highlighting both the social and economic impact of this democratization.
Real-world use cases
Dmytro highlights how AI-powered digital lending is already transforming a wide range of industries through practical, targeted implementations. These examples show how businesses can tailor financial solutions to fit their customers’ specific needs:
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Healthcare Financing: Clinics—such as fertility or plastic surgery centers—offer installment-based payment options, making high-cost treatments more accessible.
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Telecom Microloans: Companies like Globe Telecom in the Philippines provide credit to users who can’t top up immediately, allowing them to pay later for essential connectivity.
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Pay-Per-Use Equipment: Customers can finance products like lawnmowers based on actual usage—if they don’t use the product, they don’t pay.
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Retail Installments: Businesses embed “buy now, pay later” (BNPL) models directly into their offerings, eliminating the need for third-party credit providers.
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Geographically Remote Services: In areas with limited banking infrastructure, embedded lending enables transactions where traditional credit options are unavailable.
Key takeaways
- The Evolution of Fintech & AI Integration - Dmytro transitioned from early neural network modeling to building AI-driven fintech platforms
- Democratising Lending - He aims to make digital lending as accessible to small businesses as Shopify made e-commerce to retailers.
- Embedded Lending - Non-financial companies can now offer financing directly within their products or services, transforming customer engagement and revenue models.
- Financial Inclusion – AI enables micro-lending for underbanked and unbanked populations by making low-value, high-volume loans operationally viable.
- Real world use-cases - Digital lending is already improving accessibility and affordability across sectors like healthcare, telecom, retail, and even home services.
Article and quotes have been edited for brevity and clarity.
