Rutger van Faassen: Hello and welcome to the Curinos (F)insights Podcast. Today my guest is Danae Perkins, who is Senior Analyst Small Business Lending here at Curinos. Welcome, Danae, to the podcast.
Danae Perkins: Thanks, Rutger. Thanks for having me.
Before we dive into talking about Small Business Lending Portfolio data, can you share with us what your role at Curinos entails?
Yeah, so my role here at Curinos has been focused mainly on our LendersBenchmark Analyzer solution for small business lending and ensuring we deliver valuable insights to our clients as it relates to everything small business lending. I work closely with our clients on a regular basis to understand their key objectives for accessing our dataset, and provide support and additional analytics to help them achieve those objectives.
Now, we have invited you to the podcast today because Curinos is launching a new benchmark for small business lending, which covers portfolio data provided by participating lenders. This is in addition to the small business originations benchmark that has already been up and running for a while now. In your role, you’re working closely with customers, what is top of mind for them these days when it comes to their small business lending portfolio?
I think in terms of lending, top of the list is risk management. We’ve been talking about this for a while now, but with the ongoing economic uncertainties, small businesses are facing unprecedented changes and challenges with the stubborn inflation rates, there’s a difficult labor market, as well as rising interest rates. These combined really make it hard to do business, as well as make it very expensive to borrow.
So yeah, I think banks also have been preparing for a recession for over a year now, and they have a heightened attention and exposure to the importance of identifying and monitoring overall risk in their portfolio when it comes to small business lending. So lenders also recognize that they need to be strategic in this approach as they continue to onboard new loans and effectively manage their existing portfolios.
So on the origination side, lenders are looking for insights at both macro and micro perspective to determine what demands look like in the market – so what type of clients are getting originations, what demand looks like, how their buy box should be positioned based on the market, and also at what price point are they booking these clients at. Then to take that to a step further, they want to know how those clients then are performing once they are on the books and where does the market see the vulnerabilities versus opportunities.
They can look at that internally, but really what they need to see is the peer set in the market overview at that level. And some of those key metrics that they do want to be looking at are tracking delinquency rates, as well as utilization rates because these metrics will be vital in the lender’s ability to determine early warning signs and properly manage their risk appetite.
I think another main focus for our clients has been pricing. In case you’re living under a rock, interest rates are up. Lenders have a heightened focus on how to effectively price that product with regards to risk, because there’s a fine balance of pricing according your risk while not out pricing yourself from the market. And I think having the ability to look downstream at the impact of the rates that has on the ability of those clients to afford those loans in a raising rate environment is crucial.
And I also just want to hit on, this doesn’t come up too often in my conversations about lending, but it is definitely something that banks are hyper-focused on, which is liquidity in terms of deposit retention, as well as growth strategies. And small business lending relationships in general are crucial in that strategy. So, according to our data set, customers with a lending relationship have a deposit value more than two times that of customers without a lending relationship.
So we see a huge benefit in developing and maintaining that small business lending relationship. You need to manage that relationship. It’s essential to yield a strong and long-term deposit relationship with that client.
So many things that are top of mind for the lenders that are currently engaging with us. The new portfolio data will be updated on a monthly basis, allowing participants to compare their results to peer lenders. Why is it important in the current environment to review your relative market position on a monthly basis?
Yeah, that’s a great question, because when it comes to portfolio performance, many banks only have access to quarterly or even biannual market data. By the time they can review the insights, the insights are stale and may no longer be relevant to the current environment. LendersBenchmark dataset is unique because it is based on transactional-based data that is provided by participants of the consortium on a monthly basis, like you said.
The data is scrubbed through our audit process. It’s aggregated and it’s published out on an anonymized basis to our participants, so they access that database and the insights on an on-demand basis. I think this is important for lenders to have the ability to view these key metrics against peers and market trends. It gives them relevancy in the data as it is real-time data, as well as it gives them time to act upon the insights that they they’re receiving.
We discussed that the portfolio data set is an addition to the originations data set that has already been up and running with a growing group of lender participants. How do the two data sets work together and what insights can lenders get by having both views in the same platform?
To give our listeners some background, LendersBenchmark Analyzer for originations launched in April of 2022. It tracks transactional data from application to booking. Similar to the portfolio dataset, it’s that give-to-get model. Clients provide transactional level data. For originations, it’s on a weekly basis. It’s scrubbed, it’s aggregated, and then it’s available to our participants with insights based on previous weeks’ production volume. The available metrics on the origination side, those would be market share production volumes, both in units and dollars. We have pricing metrics, as well as operational metrics such as pull through and turnaround time KPIs.
And since this data is collected on a transactional level in both originations and portfolio, participants are able to view the data in an anonymized benchmark way where they are able to segment the metrics in a more granular level. So they have abilities to do a group by functionality, as well as 20 or 30 different filters in the tool itself that they can really drill down and get that apples-to-apples comparison to what they’re originating, as well as to what is originated and also what is currently in their portfolio.
Participants are able to access, like you said, on the same platform originations and portfolio. We have a Microsoft Excel add-in that we call Curinos Connect, and then they also can access the data through a data analyzer, which is a web-based tool.
Although the metrics are different that we’re tracking on the origination side versus portfolio, they’re able to access it via the same platform and they’re able to build those same views of those key metrics at the macro level so that they can track that from originations all the way through to portfolio and see what those similar originated loans are doing, how they’re performing over time on the portfolio side.
Now let’s dig into what this new portfolio data set lets lenders who participate in it understand. It’s a monthly snapshot of all small business loans on the portfolio of the lender. What are some of the key metrics and filters they’re able to access?
For our portfolio side, the key metrics – we have six of them, so we do provide the market share, so it allows the user to quantify their market position amongst their peers. We also have balance metrics, so we track units of your portfolio, as well as dollars and how that is in comparison to your peers and how it trends in comparison with your peers. We also have delinquency metrics such as charge-offs and delinquency rates. In addition, we have interest rates – how your portfolio is priced and how that correlates with the rest of the metrics you may be tracking as well. We have servicing metrics, and then another key area of interest is those utilization rates on the revolving lines of credit.
Participants are able to see all of those metrics on a macro level, as well as a micro level where they can filter and drill down into a more granular level, as they can with originations. I think just to highlight quickly some of those segments we are able to drill down by product. We also have SBA and non-SBA, so you can look at a certain segment there. You also can look at a specific client set, so you can drill down by the annual sales of the client or years in business.
You can drill down, as well, some risk segments, which would be industry codes, geography, as well as the personal credit score of the applicants that is originated obviously goes on the books and you can monitor their performance at those really granular levels. And I think that is what provides a lot of use cases for us.
Because of the granularity of the data, and the depth and breadth of the data, a product manager would be able to use this data. They could identify some white space and target specific areas of opportunity in the market by diving into the data pricing managers as well, so they can determine their pricing position and compared to their peers.
Circling back to risk, so risk managers too are very interested in this portfolio data. They’re able to not only look internally, but they’re able to see externally the exposure against a market average and strategize in real time of how they want to mitigate any risk that they may be seeing.
Now, as we’re launching the portfolio dataset, I assume you’ve been digging into the data provided by the different lenders. What are some of the insights that you can share with us about trends in the data when it comes to volume?
High level, year to date, we are seeing loan balances are up 6% compared to last year. However, we do see unit volume has dropped by around 4.5%. So I think that indicates that there’s balances staying on the books longer, as well as higher utilization across the revolving lines of credit. We’re seeing average balances are around 24% higher today than they were two years ago, and we’re seeing average interest rates almost doubled in portfolio compared to two years ago.
And what are you seeing when it comes to delinquencies? Does this vary by origination vintage?
Yeah, so kind of combining those views, right? So I have a view into origination. Our participants have a view into originations and then the back book of portfolio.
We are seeing a clear need for small businesses to access capital in originations. We’re seeing demand in the unsecured line of credit space is up year to date 14% compared to prior year. So we see that demand – how does that then equate on the portfolio side?
So looking at vintage, we see that accounts that have been on the books for three months have increased utilization from 25% that we saw in 2022 to 33% this year. So utilization is up within three months of originating the line of credit – again, to stress that need of access to capital. But with that, you can look at delinquency rate in relationship to that. And so we are also seeing those accounts that originated three months prior – their delinquency rates are up almost 80 bp from last year, so their average delinquency rates are 1.3% this year compared to 0.5% last.
Now lastly, what are you observing in the data when it comes to utilization?
There’s a lot to unpack around utilization rates and who are utilizing the lines and when they’re utilizing them. What we see in the data is that around 61% of our unsecured lines of credit in the portfolio have 0% utilization. This is a liability for banks to be holding those notes because they have to keep large reserves while also not realizing any interest revenue on those lines of credit that they originated.
In contrast to that, we also see that the lines of credit with utilization of over 95% are hitting some pretty substantial delinquency rates. In May of this year, we saw a spike of 2.4% delinquency on those lines of credit that have been on the books originated at a certain rate, but now are 300, 400 bp higher. And that is showing that there’s signs that the raising interest rates are beginning to cause a strain on those small businesses that are actually utilizing the lines at 95% or more.
So thanks, Danae, for joining us today on the podcast and for all these insights. If people want to know more, where can they find more information?
I would encourage our listeners to visit our website, curinos.com and click on LendersBenchmark Analyzer to explore the solution, and Rutger I believe will put in our show notes a direct email address to our sales solution expert and they can always reach out directly via email to him.