A canary in the credit mine, with James Fell
"At its core, Credit Canary is a data platform that consolidates and reconciles multiple different data sources in a standardised way to produce a really rich set of flags and real contextual insights. And the essence of that is flexibility within lending. With the data that we have, there is a great opportunity not just to help make better decisions, but to help make better lending products." - James Fell, Founder and CEO
All too often, a borrower and their unique circumstances are thought about at the point of application and then entirely forgotten until a payment or two is missed. That might have been OK in a world of slow and scarce data, because what else could you do, but that excuse doesn't hold up any more - and with credit data, open banking data, and more, Credit Canary are helping us to put that right.
You can find Credit Canary and view their offerings at https://www.creditcanary.co.uk/
James gives his email in the episode, or you can find him on LinkedIn https://www.linkedin.com/in/jamesafell/ In fact, the whole team is available there (https://www.creditcanary.co.uk/about)
And while you're there, find and connect with me at https://www.linkedin.com/in/brendanlegrange
Meanwhile, my action-adventure novels are on Amazon, some versions even for free, and my work with ConfirmU and our gamified psychometric scores is discussed at https://confirmu.com/ and on episode 24 of this show https://www.howtolendmoneytostrangers.show/episodes/episode-24
If you have any feedback or questions, or if you would like to participate in the show, please feel free to reach out to me via the contact page on this site.
Keep well, Brendan
The full written transcript, with timestamps, is below:
James Fell 0:00
I very much, in completing my MBA, drank the Kool Aid and set off to find an opportunity in the FinTech space - to serve an area of the market which is largely untapped, which was something that I was really passionate about.
And that focus was a key driver and motivation for founding Credit Canary. The credit data which is used to make a lending decision is effective at that moment in time, and every day that goes by its ability to predict reduces in its potency. What Credit Canary is doing, is we build a combination of credit, open banking/ transactional data, the self-assessment data given at the point of lending, and then the loan performance data. With that, we then monitor the credit health of that individual over time, so that lenders then can serve at scale, personalised treatments, leveraging generative AI and large language models, to give customers the information that they need at the time that they need it.
Brendan Le Grange 1:05
My late father-in-law was a brilliant man: unusually qualified as both an electrical and mechanical engineer. he was the right hand man to some mining magnets whose names you would know if you were in the resources game. And yet, despite that, his favourite self-depreciating comment was, 'but what do I know, I'm just a coal miner'.
It is one of three things I now know about coal mining, the others, being again from him, is that not everyone in coal mining is a crook, but all the crooks are in coal mining and that coal miners used to take a caged canary down into the pits with them to act as an early warning indicator for bad air. Because the miners knew that no matter how safe the mine was when it was opened, no matter how save it was yesterday, things could change... and if they did change, you'd want to know about it as soon as possible if you want to have any chance of doing something about it.
Welcome to How to Lend Money to Strangers with Brendan le Grange.
James Fell, CEO and founder of Credit Canary, welcome to the show.
James Fell 2:23
Thanks for having me.
Brendan Le Grange 2:24
It's a pleasure. James, we're here to talk about your latest venture that's now putting financial peace of mind within everyone's reach. But before then, you're kind of a model of the FinTech entrepreneur, reaching where you are today via stints in marketing, in tech, and some early stage startups.
So let's set some context right up front, what did your career path look like before Credit Canary?
James Fell 2:50
Well, firstly, thanks so much for giving me the confidence that I'm a model entrepreneur, that it's always a good one to hear. It started out in 2006, at a time when there would mindset was that you would take the first job that came your way: and the first job that I landed on was working within advertising.
And I did that for a number of years before kind of going in to found a corporate education business, which I set up a couple of years afterwards, and scaled with very little, or zero, investment, basically to the point where it was turning over a decent amount. We had offices in UK in the US. And really, it was my first taste of what it can be like to work as an entrepreneur. In 2015, I then did an Exec MBA for my sins. That was kind of like my first exposure to venture backed fast growth businesses. And I was just in awe and consumed by this idea of being able to get my minds together, get things happening really quickly, and then set off, post completing it, to find an opportunity in the FinTech space - which was something that I was really passionate about.
And in doing so, I landed within the open banking/ credit data space, just as open banking was starting to emerge. So seeing it kind of evolved from where it was in 2018 and 2019, all the way through to where it is now, very familiar with the nuances that exists within that space. So from that perspective, the generalist mindset that I went into the world of work with is see me through, because when you exist as an entrepreneur, you have to wear lots of hats.
But on the flip side, you know, I've needed to kind of build that team around me.
Brendan Le Grange 4:30
Yeah. And so when it came to Credit Canary, it wasn't your first dance as it were. But I guess on the flip side, that also means you knew the size of the challenge you were taking on when you decided to take this big step. So what was it that you saw, or perhaps didn't see, in the market that made you decide that founding Credit Canary was something the world needed?
James Fell 4:50
From a business perspective I'd done two other fintechs as COO, as a founding employee, and in doing so, I started to build up a series of values and non negotiables, that I wanted to put forward before I was to go ahead and then found my own business and take the lead and take the hot seat.
There's lots of businesses out there that aren't necessarily underpinned by a really strong problem statement: and where I found that problem statement, that focus, was actually when I started working with community finance lenders, specifically, an experienced that really exposed the problem, to me that exists within consumer lending. And that is that very little is given to the customer management side of the credit lifecycle.
And I've had the opportunity to sit within the community finance lenders office, I mean, this was right on the front line. And I remember there was a lady that came in, and she had lots of children with a, she was stressed because she was in arrears. And she come into this lending office to arrange an arrangement with the lender to ensure that she could stay on track with her payments. And I just sat there observing, and she sat there and she was getting more and more stressed, as the advisor was saying, Well, can you afford this much a week? Can you afford this much a week, and having the awareness as to all the data behind the lending decision, and everything that they had about it, I just felt like, there's got to be a better way to engage this customer and use this information to help her make sounder financial choices.
That was my lightbulb moment.
And then what happened is that we then started to build out the founding team for Credit Canary. And I felt there was a big opportunity to use all of this data to drive contexts from it to catch customers early and create better customer outcomes for customers throughout the lending lifecycle, helping them if their situation changed, either in a positive or negative way. And that really was the key driver that saw us move forward with Credit Canary, and look to change mindsets within consumer credit, to look to help customers throughout the term of their loan, and not just making those decisions at the front end.
Brendan Le Grange 7:05
Yeah, I love that. Because I think there's a few points here that really resonate with me, the risk we measure upfront, a huge portion of that is unknown. So you know, we're making predictions from scant data. So we see it as as risk and we price it as risk. But each month, the customers with us, you know, we learn more about them from their payment patterns, but also, depending on the products available, like what they spending where they are, their stability, you can learn more and more. And that naturally should be reducing the risks. And it's great to hear that focus in brought about and we're going to talk about the nuts and bolts of that in a minute.
But first, I want to stay for a little bit longer on the entrepreneurial journey. Because, you know, when I first came across your profile on LinkedIn, you were talking a lot about short, you know, the context of the Credit Canary business, but also a lot about this entrepreneurial journey. So talk to me a little bit about that. When the rubber hit the road when you were getting Credit Canary off the ground pulling together this team, what was the reaction like?
James Fell 8:11
Whislt I've had great co founders around me, you know, I was taking the CEO position for the first time - there's a lot of talk within founders about their loneliness. Everybody's got an opinion. And it doesn't necessarily need to say that everybody's right. But everybody is quite vocal in saying, 'oh, you know, you should be thinking about this, you should be thinking about this, why haven't you considered this'? And from a founder perspective, I always wanted to come at this with minimal ego where possible. On the flip side, you know, that is challenging, because if people will look to guide you, and you never know what people's agendas are, when they share information, or share viewpoints, or share opinions with you, trying to decipher that it's quite a challenging thing. That is something that you just have to keep yourself very grounded on.
Building on that in founding Credit Canary, we raised a pre-seed round earlier this year, and the fundraising activity from that came many months before and it's a challenging time to raise, you know, I've had scenarios where angel investors will be like, Yeah, this is all great, but my mortgage has gone up four grand a month.
It definitely has changed the principle but you know, we endured and we push through it, and it's a good reminder building on the opinion point that if you just firmly believe in you are pushing towards a really clear problem statement, you can push through, you know, whilst we are coming into the market at an uncertain time, we're positioning a proposition which is counter cyclical as well. So it's looking to help lenders to address challenges that they are either aware of out or it's kind of a passive thought that it's gonna become a problem as they move through into 2024 and 2025.
You talk about interests rates and it's it's unlikely that we will ever see the interest rates that we've seen over the past 15 years and for lenders, their historical scorecards and their historical knowledge that they've built up in lending in a very fortuitous time where cash was very cheap from one where cash has become a lot more expensive. And as a result, they're looking to change those scorecards to avoid a position where they see high loan attrition, and there is a credit shrinkage in market.
So whilst it has been challenging on the entrepreneurial journey, and I'll be the first person to put my hand up and say that, I do firmly believe that we are coming at this at the right time with the right solution. And the commercial progression that we've seen with lenders is really backing that up.
Brendan Le Grange 10:45
Particularly in a time when affordability is the driving source of risk, you know, where there's people that are from a credit risk point of view, not that different from before, might now be falling into arrears from affordability, it's incredibly important that we catch that and we work with that early on, because naturally, the majority of us are going to be trying our best to make our payments, we're going to maybe cut some corners where possible.
And by the time we default, that means we really then fully stretched.
So if we're doing that old approach of put all the focus upfront to get people on board, and then leave them until they've missed a payment. We've gone through this period where maybe we could have actually helped them and kept things on track. But we've waited until they defaulted. And now there's sort of very little that can actually be done. You say Credit Canary enables banks and lenders to foresee repayment risk to engage borrowers proactively and to strengthen lending performance.
So, let's get into the nuts and bolts of how you do that. What does the Credit Canary offering look like?
James Fell 11:51
Credit data, in its own right, is immensely powerful as an initial indicator for identifying risk... it's just how it's then used in practice. And it's a great marketing message to say, well, let's just cast that aside and focus on assessing affordability risk. And actually, this then comes on to what Credit Canary does, which is actually use both of those.
Rather than saying, well look, we're going to reject like, what's what's happened in the past in the way that we've appraised debt to one where actually we leverage multiple datasets to better understand customers and use that as a way to unlock the context to better serve them going forward. You know, over time, the key drivers that lead to customers falling into arrears, and falling into default is driven primarily from income and expenditure shock. And the observation that we've seen in the market is that the credit data which is used to make a lending decision is effective at that moment in time. And every day that goes by its ability to predict for those elements reduces in its potency.
And effectively what Credit Canary is doing is, firstly, we combined a combination of credit, open banking or transactional data, the self assessment data, which the individual is given at the point of lending. And then lastly, the loan performance data. And effectively with that, and aligned to the scorecard that was used to lend to that individual, we then over time, monitor the health of that individual, which allows us to provide a propensity to miss pay and a propensity to default model.
And then secondly, with the transactional data, we break it down using a standard vice financial statement format, to then look at each individual Costco to forecast what the likely disposable income of that individual will be going forward so that we can have a real clear idea as to where income and expenditure shock is being driven from.
And then we use that as the context to drive personalised treatments with customers designed to keep them in a regular pain pattern. And they are either going to be time based.
So getting customers giving them more time to pay or value based changing the value or changing the way in which they pay. So potentially forbearance measures, so that they then can then serve at scale, personalised treatments, leveraging generative AI and life language models, to give customers the information that they need at the time that they need it.
And we've had some really good success initially in changing payment dates for customers that are in arrears situation, aligning them to that personal disposable income and double collection rates as a lender. It's also about making sure that it's ethical as well. So in a consumer duty world, the model incorporates key essential spend as well.
So it ensures that depending on the nature of the repayment that you're not positioning to take payment before essential spend.
Brendan Le Grange 14:51
Obviously, we've got the traditional credit world where the customer is given consent during the application and thereafter all that data has been shared by the bank. And it's it's always delayed by a few months because of the design of the system. But it's always been updated.
And then we've got the more modern open banking approach where we've got far more data into types of spend and types of income and all that glorious stuff we can use. But the customer needs to give us consent for that, either one sort of on an ongoing way.
How do you marry those together?
James Fell 15:29
Yeah, so with regards to the data point, so we historically had sat purely on top of the lenders existing datasets, and then done the triangulation work based on a standardised data schema to unlock the insights. Whilst that's been a great way to allow us to build the product and move it forward, as we've dealt with more and more lenders, it has exposed challenges because the data maturity of lenders is not consistent across the board.
So what we've done is, we're just in the process of creating a number of data integrations so that we can actually offer open banking and other data sources to lenders so that we can then aggregate it on their behalf.
We're in a position right now, where we're actually going to be able to dramatically reduce the cost of open banking.
So that one, we can make it more accessible on a price point for lenders to be doing kind of recurring consent with individuals, because it is very expensive. So we deal with a lot of credit unions. And they can get charged for one pull of data for 12 months between £1 to £2, where the overall revenue for that loan is about £50-£70. And then you've got the cost to serve and the cost to make the decision the underwriter time, it all starts to mount up. And then secondly, the treatment engine is effectively driving towards the value exchange.
And it's all about putting forward propositions to the customer, that they feel duly rewarded to keep that consent running over time.
Brendan Le Grange 16:59
The other thing you mentioned there, which I think is maybe underestimated in its value is the use of generative AI.
I mean, I think we hear about a lot in all the headlines, but this use case is particularly intriguing for me, because actually, just this morning, I was looking at some numbers for one of the other shows to record the intro and there was a term in there, a UK mortgage term that I assume is quite commonly used, but I didn't quite understand what it meant, I didn't understand if it was quite what I was looking for, you know. I've worked in lending 20 years, I've got two business degrees, I didn't understand what the explanation was telling me it was so full of jargon and made so many assumptions about underpinning knowledge that it lost me. And that's where something like Chat GPT, I think could be great, where you can train her to fully understand the numbers, but you can then package it in a way that's easy to interpret, especially when they might be stressed because times are tight.
James Fell 18:04
That is one of the areas that I'm personally really, really excited about.
A couple of years ago, I wrote an academic paper with a colleague, Nick Money, who is a specialist within the community finance base, which is all to do with the role of credit decline and the information that's given to customers when they are declined for credit.
And the reality is, is like when customers have declined for credit, they're given very little information as to what are their options available that are specific to their own personal situation. And then you get scenarios whereby customers will go, and they'll try and borrow from friends and family, which is really detrimental.
They will go to loan sharks, so we're seeing a kind of rise in illegal money lending, or they'll do nothing can endure through it. And we felt there was an opportunity to at the point of decline, give customers clarity as to why they've been declined, but what their options are.
And I think the real interesting thing with generative AI is that we can really standardise their decision points that have led to say, within this context of decline decision, and kind of what their next step, it can be used really to create this safe space for lenders, they can set the rules, they know they're gonna stay within the regulation, you know, you're not gonna get kind of hallucinations, where customers are gonna get something completely sporadic. But from a customer perspective, they can get the content strategy, speaking to them in a way that they want to be spoken in reflective of how they might feel were the tonality is changed automatically with GPT.
And I talked about the credit decline example, but it goes right the way through because if you've got customers that say, for example, have a positive change in impersonal status, could it help them transition to more cost effective lending, but I think it's a super powerful way of providing at scale, very personalised in interactions for customers, which have been validated, there's kind of an underlying smart contract, so you're not going to go too far.
We've still got a bit of a way to go on that, but ultimately, that's the long term direction is to where Credit Canary is looking to go on.
Brendan Le Grange 20:14
www.creditcanary.co.uk I was scrolling through, you do talk about this customise nature of the product, that this is not about finding that customer who's about to default and sending a generic message. Your client can really use this in a number of ways, which can be just as likely to be positive and finding consumers. They want to give a better deal to, as it could be finding those customers that are sort of early warning flags.
James Fell 20:41
Yeah, I mean, at its core, at this point, Credit Canary is a data platform that consolidates and reconciles multiple different data sources in a very standardised way to produce a really rich flags to allow them to provide real contextual insights.
And that liquidity analysis, which combined allows lenders to identify income and expenditure sharp, the overlay of those data points allows them lenders to be more personalised in how they approach customers, and is ultimately the sweet spot where these use cases all emerge from.
Brendan Le Grange 21:16
Yeah, and that 360 degree view that you create is what the regulator wants us all to be using when we make our decisions. It's what the customer wants.
So really, this is one of those situations where we're just making possible what we've always wanted to be doing, but had been unable to do due to system limitations due to data limitations in the past,
James Fell 21:38
We're kind of just on the cusp, right now of lots of new data sources to make it much more easier to appraise credit worthiness for these outside cases. I say outside that I think the stat is that a million new customers come into the UK market every year.
So it's a really sizable issue and a really sizable problem. So, you know, we personally believe that whether you're coming into the market, and you're earning £150,000, or you're coming into the market and earning £30,000, there are solutions available.
Brendan Le Grange 22:09
We also have this aspect of consumers that when they come into the market, and they come through one channel tend to be anchored somewhere to that.
So if you've got a customer who looks for all the world, like a risky customer, because of certain events in their past credit profile, or whatever the case may be, you might find somebody who takes a gamble on them says, well, I've got enough little bits of data here, I'm going to give you a loan, but it's going to be a very expensive loan, what we want is not a situation where because they entered the market looking risky, so we had to price highly, we don't want that customer continually paying a higher rate.
As soon as we know enough about them to see actually, this is their true risk, we want to be providing them the best available products. And so having these more automated type approaches working in the background. Yeah, I think there's a lot of upside to that
James Fell 23:04
I completely agree.
And going back to that story of that lady that I was observing and my lightbulb moment, our mission is to ensure that customers never miss a payment.
And the essence of that is flexibility within lending.
With the data that we have, there is a great opportunity not just to help make better decisions, but to help make better lending products, whereby over time customers who have progressed forward and have been priced at higher risk, get rewarded for their ability to make those payments where it's not just necessarily about paying less, maybe putting their savings aside and giving it back to the customer at the end of the loan as a lump sum.
There's lots of different ways and means.
So you know, I do feel that like whilst it is a very challenging time for consumer credit at the moment, these steps that we're taking will create a much better consumer credit market, where the ultimate needs of the consumer is remaining front of mind which is underpinned by that consumer duty mindset.
Because ultimately, life does happen. And nobody is immune to macro changes, especially if when that safety net as eroded. And you know, they are living in very pressed circumstances - as a founder, I'll put myself in that category - and it's, it's concerning. The reality that I saw was that customers have these crisis moments, they address the crisis, and then they get on with life until something happens again. And very much that was the idea with Credit Canary is that how do you engage customers at the point that they need it, rather than expect them to remain engaged over time?
Brendan Le Grange 24:46
Yeah, in terms I first learn to view and create a canary on LinkedIn and I see the whole team can actually be found there.
But if anyone listening is interested in this, maybe they're listening and realising that they aren't putting enough focus on A customer management side of their lending. Where could they go online to find you to start that sort of conversation? Yeah.
James Fell 25:07
So it feel free to like reach out connect on LinkedIn or just simply just ping me an email. It's an easy one. It's just Jim @ creditcanary .co.uk
Brendan Le Grange 25:16
I'll put links to you and to that on the show notes as well, James, thanks again for making the time. We've never had a time when it was easy to get all the bits of data we desired. And it sounds like we're entering a world where that is a possibility for us. So very exciting times ahead.
James Fell 25:32
Yeah, it's super exciting. And thanks so much for having me on the show today. It's been a great experience.
Brendan Le Grange 25:39
And thank you all for listening.
Please do look for and follow the show on your favourite podcast platform and share the updates widely on LinkedIn where lending nerds are found in our largest concentration. Plus, send me a connection request while you're there.
This show is written and recorded by myself Brendan le Grange in Brighton, England and edited by Fina Charleson of FC Productions.
Show music is by Iam_wake, and you can find show notes and written transcripts at www.HowtoLendMoneytoStrangers.show and I'll see you again next Thursday.