Collections Effectiveness vs Efficiency
Updated: Apr 15
Finding the right balance between collections effectiveness and efficiency is important to your bottom line. Hire too many agents and your staffing cost will exceed its utility. Staff too light and you’re leaving dollars on the table. Optimization is key, and finding the right balance takes experimentation—and some important math.
It's well known that modern risk tools paired with innovative collection strategies have the potential to increase monthly collections substantially while decreasing operations cost (a win-win!). But getting this right is not easy, and the larger your organization is the more difficult it can be to rein-in and control all the necessary components. First you need the right building blocks in place: behavioral scores identify the riskiest accounts; treating high balance accounts differently should factor-into your strategy; you may want to assign the toughest accounts to your best collectors; forecasting collateral values should factor-in, and are you heading toward a period of widening or narrowing loss severity if a default were to occur? Also important, are you truly setup to run champion/challenger campaigns in an unbiased manner? Other considerations involve how easily and accurately you can measure the results of your champion/challenger campaigns, and can you frame those results in a way that tells you if staff counts are above or below the point of peak optimization?
In principle, C-level execs easily buy-into the idea of optimizing efficiencies—it’s a no brainer to CFO’s because they already see the world in terms of top-line/bottom-line profitability. But tell a branch manager you’re limiting their resources this month and see what happens! If branch managers are graded on effectiveness alone (e.g., lowest DQ pct, or most dollars collected), some will look to undermine a passive challenger strategy because it’s messing with their month-end numbers.
Yes, becoming a modern call center is not for the faint of heart. It takes serious planning. It takes top-down buy-in. It takes serious software and absolute control of the situation. We know of one lender that rolled-out champ/challenger campaigns on the dialer only while manual calling schedules remained unchanged. And since there was still pressure on these branches to bring delinquency down, the result was a bit of a mess: each branch created its own champ/challenger campaigns that were different from each other, and some, realizing their dialer strategies were now more passive than before, decided to ramp-up their manual calling strategies even more aggressively as a countermeasure. To make matters worse, by mid-month two of the branches had noticed they were falling behind on their goal and decided to go back to the old way of doing things to hopefully salvage the month (without telling anyone). We’ve also heard where some collectors, now realizing certain accounts had dropped from their calling queues on certain days, created paper lists so they can still make those calls. And while all of this is going on (mostly undetected), it’s often the risk department that’s tasked with measuring results. In many organizations, the risk team isn’t fully aware of the operational goings on in the branches. They simply interpret what the data reveals, not realizing there was significant bias in the results brought on by a sloppy operational rollout. None-the-less, these “learnings” become facts within the organization and influence future campaign strategies for years to come. Garbage-in garbage-out
Despite all the growing pains that come with rolling out modern, innovative collection strategies, if you continuously work toward more centralized control you should be able to iron out the wrinkles over time. But better yet, why not avoid the growing pains in the first place? You just need a rock-solid plan from the start—including the right technology that prevents slippage and bias from mucking-up your results.
And while this rock-solid plan applies to lenders of all shapes and sizes, we’d like to address the small to mid-sized lenders specifically in this post. The big guys have enough resources to make lots of mistakes—you don’t. The big guys that are doing risk management strategies correctly (which may be less than half) enjoy a nice competitive advantage. You’re probably aware of these modern risk strategies and their potential lift to your operation, but you are a realists too. You’re probably thinking you can’t afford to build all this risk management infrastructure—not in the way that’s necessary to truly do it right. You may be right, but that’s all about to change.
So let’s summarize the situation in a more dollars-and-cents kind of way. Just how much more $ should a loan servicer generate if properly using all of these risk tools and strategies? The answer depends on how deep into the subprime space you operate. Our experience is a properly executed risk management framework should improve monthly collections by around 30% each month as it pertains to your past-due portfolio. So ask yourself, what percentage of your portfolio is typically 1 or more days past due? There’s your answer.
So let’s define what a properly executed risk management framework is. It’s one that employs numerous risk management features that each bring incremental lift to your monthly collections.
As we alluded to in our prior post, most of the pitfalls when rolling out a risk-based collections platform can be addressed through technology. Lendisoft has engineered a software with all of this in mind—in fact risk management was the central inspiration of its design architecture—more so than any other LMS being offered as a SaaS solution. When you have long careers seeing and remedying so many mistakes over so many years, you know how to engineer a solution that solves all the problems before they exist. This is what Lendisoft Servicing does.
Let's have a deeper dive into how Lendisoft approaches champion/challenger campaign architecture.
First, all accounts are assigned a risk grade of A,B,C,D or E using internal scoring models (there are 19 scorecards under the hood, included with Lendisoft). Next, our campaign builder tool lets you create staggard calling schedules for each risk grade. You can create different campaigns for manual calling queues, SMS notifications, and email notifications—all in a manner where odd account numbers have different schedules than even account numbers for random testing, based on when an account first becomes X days past due. All of this is configured in a single place, and done in a way that agents aren’t privy to the schedules.
Notice how even account numbers are assigned to the Champion segment, and odds are assigned to the Challenger. The “Q” in the various cells indicate when accounts are scheduled to appear in the collector’s work queues. Of course there are infinite possibilities, but in this example you are testing a strategy where all accounts are called when they become 6 days past due regardless of risk grade (the Champion); while simultaneously testing another strategy where “A” accounts (the riskiest) are called when they become 3 days past due, B’s when they become 7 DPD, C’s at 11 DPD, etc. Once all your campaigns are created, they will begin running on the 1st day of the upcoming month and they will run in the background all month long unless canceled.
Once campaigns have run their course, it’s time to measure the results. With other LMS software, analysts must query the database to pull data extracts outside of the LMS, and perform significant analysis (usually in Excel) to learn how the champion and challenger segments performed. Usually, analysts are measuring KPIs like end-of-month delinquency percentage for each segment, and other performance-based metrics aimed at measuring effectiveness. But are they also measuring efficiency to make an overall determination of which segment won the contest? Many are not. Lendisoft includes several built-in reports, one of which frames the contest in a manner that estimates how many agents are needed to support each strategy, along with each segment’s corresponding staffing cost based on hourly rate assumptions you can edit. Next, it estimates how much Cum Net Loss each segment will incur (e.g., less aggressive schedules will incur more CNL to some degree). Finally, it determines the winning strategy after factoring-in both considerations, and produces an overall estimate of Net Savings. If the savings is > $0, the challenger wins and you should strongly consider making this the new champion strategy going forward.
All of this is managed within Lendisoft, so one person can sit in the cockpit and have total control of the situation. Think of Lendisoft as an enterprise solution made for lenders of all shapes and sizes. Lendisoft is the premier choice for lenders who want enterprise-level risk management capabilities without all the complexity and cost of managing a complex risk management department. And best of all, our pricing model is volume based according to how many accounts make up your portfolio, so we are affordable to lenders of all sizes.