Most reports indicate that the global digital lending market is valued at more than $11 billion. Yet 75% of fintechs – a statistic that includes online lenders – are expected to fail within their first few years of operation.
For those that don’t fail, many don’t realize their profit potential because their loan products aren’t fully optimized.
If you offer an online loan product, not only are you at the forefront of a digital transformation in finance, you also play an important role in expanding responsible access to credit. But you risk dropping out of the market, if you ultimately fail.
So, don’t fail. Here are six signs your fintech loan product is headed toward failure – and how to fix it.
1. You don’t have enough money.
This is an obvious one, but we’re mentioning it anyway. You can have a top-rated product offering, but if your underlying company hasn’t secured enough capital, the product is probably doomed. Being underfunded means you don’t have enough to cover the loans, manage operational costs, absorb losses, and maintain regulatory compliance, all of which are critical for sustainability.
In our experience, some lenders grossly underestimate all related expenses when launching a new loan product. Expenses like data costs, lead buying, sturdy risk and marketing analytics, call center operations – it all adds up.
Some lenders may even manage to be profitable, but the margins aren’t anything to brag about.
One of the ways to avoid having your loan product completely tank or render suboptimal profits is to complete a unit economics study ahead of a launch. It really forces you to analyze the gritty details of the revenue generated per loan against the costs associated with issuing and servicing it. With this data-driven approach, you can make informed decisions on where costs can be reduced or efficiencies can be gained, such as in customer acquisition, loan processing, or default management.
2. Your consumers aren’t making enough payments.
Another common mistake is to underestimate loan runoff. If borrowers are paying in full earlier than expected or too many are defaulting on their loans, the loan portfolio will shrink sooner than anticipated.
Managing loan runoff is crucial for maintaining a stable or growing loan portfolio. It’s a process that requires a healthy mix of historical data analysis, borrower behavior modeling, and advanced predictive analytics. Leveraging a really smart team of data scientists to predict default and Paid in Full (PIF) rates can help you develop a sustainable loan product.
3. Your loan size and/or APR need tweaking.
When you’re trying to work with limited funding, it’s tempting to say, “We only have this much money to lend out, let’s offer lower loan sizes and get a lot of volume out of this.”
Not always the best approach.
It’s not impossible to be profitable in the subprime lending market, but if all your loan offerings are too small, you could risk losing out on the leads that need higher amounts to fulfill their financial goals. Those types of leads also typically convert into better quality applications because they can afford to repay at that level.
In short, there are times where you may be better off with fewer loan offerings, higher loan sizes, and tight underwriting to actually get you the results you’re looking for – more revenue not just more loan volume.
With annual percentage rates (APR), it’s important to have good analytics that can accurately measure an applicant’s ability to pay the loan back. This allows you to maximize revenue per loan and minimize default. Fractional changes to APR can make a large difference in revenue as your loan volumes increase.
4. Your underwriting is flawed.
Flawed underwriting can show up in a myriad of ways.
One way is if your requirements are overly strict or in the opposite extreme, too loose. If your underwriting requirements are too strict, you might end up turning away potential borrowers who could actually repay their loans, but just don’t fit into a rigid set of criteria. This kind of approach can stifle growth and make your loan product less competitive in the market. On the flip side, if your underwriting is too loose, you’re opening the floodgates to risky borrowers who are more likely to default. This not only leads to financial losses but also tarnishes your brand’s reputation.
Segmentation plays a big role here too. If you’re not properly segmenting your borrowers, you might be applying a one-size-fits-all approach that just doesn’t work. For example, just because one borrower performed well on a payday loan, it doesn’t mean the same person will perform well with an installment loan product. Different borrower segments have different needs and risk profiles, so failing to account for these nuances can lead to high default rates or missed opportunities.
Add in other issues like relying on outdated data or not considering market conditions, and you’ve got a recipe for a loan product that’s bound to fail.
The devil is in the details when it comes to underwriting, so paying attention to every possible credit metric is critical.
5. Your loan management system (LMS) is not robust enough.
We’ve seen a lot of different loan management systems in our line of work. Some have all the bells and whistles when it comes to front-end design, but many are missing key elements on the back-end logic.
A strong LMS has to consider every borrower scenario. For example, what happens:
- If there’s a deferral?
- If the borrower makes an extra principal payment?
- If a borrower is short on a payment?
- If a payment comes in on a weekend?
If the technology supporting your product is inefficient, you’ll soon find that your loan performance metrics will fall below your expectations, and you’ll likely be missing out on revenue.
To avoid this pitfall, map out every borrower repayment scenario, set clear requirements for your LMS based on these scenarios, and finally test, test, and test again to make sure you’ve met all your objectives.
6. You don’t have solid frameworks to handle compliance.
If your credit decisioning engines aren’t designed with compliance in mind, you’re setting your loan product up for failure. Lenders operate under the umbrella of more than 18 different federal laws, such as the Truth in Lending Act (TILA) and the Equal Credit Opportunity Act (ECOA).
Many of these laws are in place not only to ensure that consumers are treated fairly, but also to dictate how lenders handle risks, especially when dealing with third-party relationships.
Having a deep understanding of these regulations, along with staying updated on any new laws, is crucial when building credit models. Failing to do so can lead to costly federal audits where millions of dollars could be on the line if you can’t justify the decisions made by your credit models.
Bottom line: neglecting compliance can quickly turn your promising loan product into a liability.
This is yet another reason why it’s so important to have a knowledgeable team of data scientists building and monitoring your decisioning engines. A team that’s well-versed on all relevant regulations can be the defining line between profit and loss.
Wrapping It Up
A digital lending or customer financing product with a strong strategy behind it can perform well. Predictable results for profit are not beyond your reach. You can avoid the pitfalls listed above with good planning, a strong team, and business management consulting as needed.
Learn more about how Bloom Analytics can help you successfully launch or optimize your loan product. Schedule a consultation today.
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