I really didn’t want to invest in this company.
Yes, you read that right. Probably not the opener you’d expect but (sadly) it’s true.
I was introduced to Ophelos by two separate people — both of whom I trust and both had strong endorsements of the founding team — and yet both times I turned down the initial invitation.
Ophelos were pitching themselves as a “challenger debt collection agency”. My lazy lizard brain told me I didn’t want to be in the debt collection business and as for building an ‘agency’, well, it’s almost a dirty word amongst technology startups. Two easy reasons to say no. And, as it turns out, two reasons I was wrong. I’ll explain why but first let me set the scene with the founding team and origin story.
Note to self: Keep an open mind. Powerful outcomes can come from overcoming my preconceptions.
(*BIG thanks to @alexflamant for the initial intro and @mattwichrowski for persisting with me. We’re delighted to have led Ophelos’s $2.3m pre-seed round alongside our friends at Fly Ventures.)
Amon (co-founder CEO) and Paul (co-founder COO) met whilst working at ASAPP, a New York-based venture-backed AI startup. Amon was a director of their EMEA business and Paul was Head of International. They were the first of the ASAPP team to land in London and quickly became close. ASAPP’s proposition was AI enablement for enterprise contact centres. Whilst selling into the financial services industry, Amon & Paul saw first-hand how large the internal debt collection teams were as part of these contact centres (e.g. in one case, there were 4,000 call centre agents devoted solely to debt collection). They also saw how analogue the phone-based practices were within these teams. Amon became obsessed with the idea of applying technology and machine learning to optimise and solve many of the problems associated with debt collection (both enterprise and end-customer problems). Paul had previously been Head of Watson Group at IBM in EMEA and didn’t need much persuading. As part of their learning, they realised there had only been a handful of technical research papers written on the debt collection subject in the last 50 years. Only one of these papers was from the last 5 years — enter Qingchen (Ophelos co-founder and Chief Scientist). Qingchen, who is now also a professor at the University of Hong Kong, had written a paper titled: Data-driven Consumer Debt Collection via Machine Learning and Approximate Dynamic Programming. Not the catchiest of titles but his unique knowledge and experience meant that the stage was finally set for Ophelos.
Why I was wrong...
Your own reaction when reading “debt collection” might have been similar to mine. It’s definitely not sexy. It conjures up all sorts of images we’d prefer not to think about — bailiffs, fear tactics, injustice and ultimately an uncomfortable amount of personal hardship. I’m not sure anyone grows up wanting to innovate in this market. And yet this is exactly the reason not to bury our collective heads in the sand.
There are some markets we’d prefer not to exist because of the societal consequences they create. Debt collection isn’t one of them. So long as we want to keep paying for products and services whilst we consume them, there will be debt. And for as long as there is debt (regardless of what you call it) there will be debt collection — because life isn’t predictable or within our individual control. Quite simply, our economy and society can’t function without debt or indeed the practice of enforcing unpaid debts.
Rather than pretending debt collection doesn’t exist, the most powerful thing we can do is focus on the quality of people, products, and services tackling this market. Or as the Ophelos team would say: “Reimagining debt collection — for good.”