How do you manage that? You know, private credit in The U. S. Is blowing up right now. I mean, you see Blue Owl limiting redemptions. You see Apollo KKR going crazy. You see Vista Equity launching a private credit fund to go after distressed private credit books. I don't know if you're seeing the same patterns in Europe, but are you seeing any sort of non accrual rate spikes on your outstanding capital balance and borrowers?
Due to macro and kind of a consumer squeeze on spending, our customers are struggling a bit and that affects us of course, in terms of a little bit higher default rates, but we're still doing, we're still profitable, we're still doing well. We have this nice growth, which we think will accelerate as macro improves.
The closest comp I have to this is when you go back and look at OnDeck pre COVID, they obviously were public. So we could see their, you know, default rates, their average gross yield, they're putting dollars out at and their net interest margin. You know, they were very comfortable and they could operate profitably with like a 10 to 15 default rate because the margin, what they're putting money out at was, you know, 35, 40, 45% sometimes, which look, you could argue it's expensive or not, but the point is no one else was lending to that market, right? So it's either 40% or nothing, right? It's a new product. How do you think about those numbers for at Froda?
I think it was important for us from the start and still is that we want to be a fair lender. We want to be able to offer the best possible terms. The average APR, just to put it into context on that is with us is 16%. So it's lower than some of the MCA players, but it's still a bit higher than the high street bank. Back to your point, Nathan, I mean, customers today, they would get
the no from the bank, right? So they have no...
Exactly. I
think that we are really the best alternative for them. And in many cases, the investments they do would give returns that are like threefold or tenfold. So although interest is a little bit higher, it makes total sense to do that investment.
And Oliver, don't know what the regulation is like in Europe but I know in The U. When you're a bank like this, you've got to have some historical cohort or vintage analysis so that you can use sort of CECL methodology to put together a go forward loss projection and allowance for bad debt. Know, some folks say we're gonna hold back 1.5% of all new originations for a future allowance for bad debt. Others are more aggressive, they say 5%. How do you think about that cushion for Froda?
It's the same in Europe. So we need to hold some buffer for losses and basically we take that loss upfront, right? So if we lend to a customer, we have to take cost for loss as soon as we do the payout. It's about three to 5%. What have actual sort of losses been?
Has it been like two, three, four, 5% on historical vintages?
Before this current macro squeeze, we were around like 3%, it's a little bit elevated now, but we project that we will go back to around the 3%, 3.5%, that's where we want to be. It's a higher risk appetite than the traditional bank, but it makes sense considering the segment that we're serving, we think that's a good kind of balanced level.
Yep, and how do you know that 16% average APR is the right and correct risk adjusted pricing for a new lender getting a $23,000 loan from you? What does your credit box look like?
I think we could probably charge more because just as you said, they don't find external financing elsewhere or at least it's not abundant. We have been coming back to kind of the vision of offering the best possible terms. We are kind of the cost driver or the price driver downwards here because we want to offer as good a loan as possible.
I know for example, if a software company has been around for ten years in business and has more than 7,000,000 of ARR, they're way less risky than a new AI startup with less than one year of history. So the pricing and the effect of APR is going to reflect that. I imagine you have some guidance like this in terms of Oh yeah, yeah, definitely.
So, I mean, from the start, the idea was to really use transaction data and other credit data points that we can get
to build machine learning algorithms, basically to find patterns and important data points to really score these small businesses as well as we can. I mean, what we've seen now with ten years of experience and a couple of 100,000 of businesses sharing data with us is that we can really leverage that large data set to find patterns that can enable
us to understand what's the risk in this business going forward. And that would set both the credit volume that we would offer. So the maximum credit line that we can offer and also pricing that we offer.