Collections agents are busier than ever before. With the number of non-performing loans (NPLs) reaching dizzying heights after the COVID-19 pandemic, collections agencies/departments must find ways to work as efficiently and effectively as possible.
This is where automation-based collections management software comes in. By leveraging the receeve platform, one of our customers, Pactum, saw a:
This blog will explore the key performance indicators (KPIs) that agents should focus on. It will then outline how collections software keeps agents focused on these crucial metrics going forward, making agents more productive and efficient in the process.
KPIs focus your agents’ efforts on what really matters, providing a measurable yardstick to evaluate their performance (and to assess your collections success more generally). The following KPIs need to be prioritised above all others.
1. Accounts per Collections Employee
This KPI is pretty straightforward. You take the total number of delinquent accounts that your agency or department is currently managing and divide this by the number of employees in your team. By analysing accounts per collections employee, you can roughly assess your team’s productivity. In other words, the higher the figure, the better.
However, if your accounts per collections employee figure is high but your collections recovery rate is low, it is clear that your employees are unable to successfully handle your department’s demand. You must therefore try to keep this number fairly high while also making sure there is no significant decline in collections performance.
2. Amount Collected per Agent/Employee
Simply divide the total amount of money that your department/agency has collected over a set period of time (for instance, over a quarter or over a year) by the number of employees within your department/agency.
This is a great way to analyse each employee’s productivity as well as the overall success of your collections department. If each employee is only collecting a minimal amount of money, this is a sign that you need to rethink your collections approach.
3. Percentage of Inbound/Outbound Promises to Pay Kept
Promise to Pay (PTP) is the verbal agreement usually made between the customer and collections agent when a payment is past-due. The customer promises to pay a certain amount on a certain date.
Percentage of inbound promises to pay kept refers to the number of delinquent accounts who kept their promises to pay through inbound calls, divided by the total number of promises to pay that you received via inbound calls over this time period.
Similarly, the percentage of outbound promises to pay kept relates to the number of outbound calls made that resulted in actual payment from promises to pay in relation to the total figure of outbound right party contact (RPCs) made by your team over this time period.
A low figure indicates that there is something wrong with your approach. Perhaps your script is ineffective or your payment landing pages are not working correctly. Or your employees are coming across the wrong way (leading to reactance, a phenomenon where a customer deliberately decides not to pay to assert psychological control over the dunning process).
4. Profit per Account
To calculate profit per account, simply take your department/team’s gross profit (total revenue minus total operating expenses) and divide this by the number of delinquent accounts that you are handling.
Low profits per account are indicative of an ineffective, and usually highly manual, collections process. In an ideal world, you want this figure to be as high as possible—this means that you are seeing the greatest return on investment (ROI) from your efforts.
Enterprise collections management software provides you with the features your agents need to stay on top of these key KPIs, and to optimise your performance more generally. Let us examine a few of these features in closer detail.
With collections management software, you can easily track if the emails you send out are successfully delivered. That is, you can see if the emails are opened, or if the recipients actually clicked on the link and visited your repayment landing page.
This means that if agents do need to pick up the phone and give customers a call, they know in advance whether the customer has read the email or seen the repayment landing page. They can therefore tailor their communication appropriately according to a customer’s behaviour and will not simply assume they have all received your messages.
Self-service functionality puts control back in past-due customers’ hands. Customers can take ownership of the payment process without an agent needing to step in. They can repay what they owe when they want and on whichever channel they prefer. Or, they can set up an instalment plan that suits their particular context and financial situation without needing to enlist the help of an agent at any step throughout the process.
This frees up agents’ time and energy to focus on other matters (like dealing with particularly high-value or tricky cases). It will also reduce the number of outbound calls that your agents need to make, slashing your phone/electricity bill. Besides, it is an easy and effortless way to increase your account per collections employee KPI.
Artificial intelligence (AI) and machine learning (ML) are proving to be two incredibly potent weapons for modern collections departments. But why are they so useful? Essentially, AI and ML algorithms can analyse the performance of your messaging/email strategies before discerning which are most effective for which particular customer segment.
This means that you can fine-tune your outreach strategy going forward, choosing messaging strategies that resonate with each segment. In fact, ML can even identify the best times to send your outreach messages. In other words, agents can automatically use the most effective messaging strategies at the most effective times, thereby increasing collections success tremendously.
Enterprise collections management software is entirely digitised, meaning it provides agents with a wealth of data on all aspects of their collections operations. Agents can use this data to verify the phone number and email address, to segment customers according to their demographic details, or to create a customised strategy that is optimised for each particular persona’s preferences.
Furthermore, data can indicate which customers need more support and care (for instance, by analysing payment attempt/disruption rates). If it seems that past-due customers keep on trying to repay what they owe but are not successful, perhaps they need an agent to walk them through how your repayment landing page works. Or, this might even be an indication that there is something wrong with your landing page—helping you identify, and quickly rectify, the problem before it gets even worse.
View everything you need to know about past-due customers in one single place—in other words, in an all-in-one case management system. See their contact information, verify their contact details, check out how much they owe, assess their financial history, and see their current payment agreement.
Agents will no longer have to switch back and forth between different systems when dealing with a single past-due customer. Instead, they have all need-to-know information in a clean, clear, easy-to-view portal. This will increase their productivity and efficiency, making their jobs so much easier than before.
Enterprise collections management software is the single best tool for optimising your agents’ performance. It goes without saying that all collections departments/teams need to focus on improving their accounts per collections employee, amount collected per employee, percentage of inbound/outbound promises to pay kept, and profit per account.
By leveraging a data-driven modern collections management system that boasts tracking, self-service, AI/ML, and case management capabilities, you will optimise these crucial KPIs—keeping your agents as successful and productive as possible.
Cars have transformed society since they were first introduced back in the early 1900s. They’re synonymous with personal freedom, allowing people to get from A to B more quickly, easily, and indepen...
Financial institutions use big data to gain a deeper understanding of their customers: their financial history, preferences, and behaviour. In a digital-first world, data acts as the footprints in the...