As debt collection moves into the digital age, it’s valuable to take a holistic view of which elements can be leveraged to maximise results. There are plenty of areas to focus on of course, but four under-exploited factors have the potential to take digital to another level in terms of participation, efficiency and effectiveness. If these key areas work harmoniously, digital collections will work for more customers more efficiently and with better, measurable outcomes.
Let’s look at the four areas:
1. Customer demand
“If you want people to engage with you in collections, you’ve got to be realistic that people are less likely to pick up the phone and call you back or even answer the phone”
Today, as contactless payments are overtaking chip and pin for the first time and smartphone ownership rising in all age groups, there is a discernible ‘rush to digital’ in collections driven by customer demand. The biggest single factor is the spectacular decline of the voice call but whereas some see digital as the end game of this trend, in reality, it’s just the starting point.
Customers expect digital systems that respond to their input and react intelligently; this is what they’re used to across their online interactions. What frustrates them is a limited experience, a lack of information or an unresponsive tool that doesn’t offer enough personalisation. Is it going to be enough to lift the collections process as it stands and drop it into a digital environment?
Collections has moved away from the concept of customers as stagnant, average entities and is building engagements that better reflect the diverse, fluctuating nature of human lives rather than being ‘designed for the ideal’. There is a particular need for this when debt so often overlaps with complex circumstances like mental health challenges or big life changes. It’s unlikely that box-ticking is going to be enough to meet increasing regulation or satisfy customer demand.
2. User Experience Design
“A quick, painless experience to set up a plan or pay what you owe and you can get on with the rest of your life”
As debt collection software hasn’t previously been customer-facing, user experience design (UXD) has not been a high priority, until now. With the customer in control, the journey has to be seamless and obvious but not blunt and without flexibility. It is important that a digital system doesn’t increase detriment by overlooking non-average customers or failing to provide reasonable adjustments to increase accessibility. Customers’ tolerance of frustrating design is low and high drop-out rates only load the cost back onto contact centres.
For customers, plain English and lack of jargon help as do clear instructions and simple, intuitively presented options. But UXD also has a key role in presenting a collaborative approach and connecting with customers through an empathetic and encouraging journey.
In later stage collections, bringing in the time-saving option to authorise Open Banking to make income and expenditure a quicker, more accurate procedure may prove to be surprisingly popular. It’s a difficult one to predict but underestimating the public’s appetite for change can leave organisations playing catch up. Debt advice bodies are getting behind Open Banking as a force for good and promoting the mutually beneficial exchange of information in return for improved understanding and personalised service.
UXD is not only about neat-looking interfaces; it can be measured in terms of increased participation, lower cost to serve and more positive outcomes.
3. Machine Learning
“We want things to be easy to use and to be organised around what’s known about us”
After some initial scepticism, every progressive business is now looking at ways to leverage machine learning to improve customer service and profitability. This is a rapidly developing technology and there are exciting opportunities to integrate a previously unimagined degree of intelligence into customer-facing systems. The information received can then be presented to aid decision-making, putting departments in control of how they respond, based on their own specific policies and requirements.
The most useful application of machine learning early in the collections process is to identify the propensity to pay and ensuring those customers are directed promptly to the most appropriate treatment. With 22% of customers in arrears waiting for the first contact before they pay, the potential is significant.
“Collections hasn’t always been something to invest hard earned money in because where’s the return?”
If we think about the acquisition and management of data as a cost then the opportunity to make it pay by improving efficiency is an attractive proposition. Machine learning is one way to do this, another is to fully utilise transactional data and usage information via web analytics to inform decisions and continually feed this insight back into updates and improvements. The value of this data is that it comes directly from the experiences of customers and agents within the organisation, it’s always up to date and it isn’t based on assumptions from outside sources or general data cohorts.
Armed with this knowledge, the agile nature of digital technology makes it infinitely easier to quickly test and implement changes according to what is known about the customer journey and what works in any one organisation. This is a sea change from the days of investing in legacy software that couldn’t be replaced until the next major IT spending round.
If we can achieve a balance and a synergy between the most leverageable aspects of digital collections it can reap definable and measurable benefits to both customer and creditor. Moving to digital without fully realising the possibilities would be a missed opportunity and in just a brief period of time, the shortfall would be painfully obvious. As digital technology has the ability to continually improve and update as a matter of course, these benefits can be incremental, adjusted, personalised and expanded without fuss.
Quotes taken from the Flexys Refreshing Collections podcast- listen here