In early collections, most customers will pay within a couple of days when nudged by a friendly reminder, such as text messaging. On the other hand, customers under financial stress should be spoken to sooner rather than later, so that there is sufficient time to resolve the problem and prevent accounts from rolling to later stages of delinquency. Ideally, minimal operational effort is spent on customers that are likely going to pay, so that expensive debt collection resources can be focused on those customers where agent intervention makes a difference. This is a perfect opportunity for digital debt collection.
With digital debt collection, this goal is much easier to achieve. Digital channels not only scale better than call centres, they can also be available outside standard business hours and switch to a preferred channel within the same dialogue. Specifically in debt collection, customers seem to appreciate a self-service option, as it’s seen as less invasive and non-judging.
Self-service options have proven to deliver great results both in early collections and even post charge-off recovery. This frees up human collectors to spend more time with customers in forbearance situations that require empathy and consultation.
In a recent McKinsey paper, the authors stress that digital debt collection helps to both substantially reduce operational costs and dramatically increase resolution rates. It is not surprising that several leading lenders, telcos, utilities and debt collection agencies are defining digital communications as their new normal. With the increasing capabilities of speech recognition and AI-driven dialogue management, it is likely that that digital customer engagement will take over more and more of the debt collection life cycle.
Risk-Based Segmentation and Digital Debt Collection
A good contact strategy for early collections typically separates out special cases which require a specific treatment, identified by one or few data attributes. Such cases might include employees, deceased customers, fraud, first-payment defaulters or customers without valid contact data. The bulk of the remaining accounts should be segmented by arrears bucket (days past due), balance and a risk indicator, ideally propensity to roll. The segmentation tree can be evaluated daily, or alternatively at cycle date, when the account balance changes, and eventually when payment agreements are made or broken.
Mini Workflows Define the Customer Experience
The resulting segments can then be subject to simple mini-workflows appropriate to their risk, with a variation in communication timing, channel, and tonality, e.g., a text message on day 2 followed by a call on day 7 followed by a letter on day 15. Using champion/challenger testing, the appropriate treatment for each segment can be determined, balancing customer experience, segment performance and operational effort. In a more advanced approach, decision optimisation can be used to analytically derive the optimal treatment for each customer, minimizing a business objective like balance roll rate whilst honouring capacity constraints and alternative business targets.
Treatments paths should remain simple and not contain unnecessary conditional logic. This allows you to keep these workflows in existing case management systems, like legacy collection systems or CRM solutions.
Agility Is King in Digital Debt Collection
As the above-mentioned McKinsey paper stresses, important prerequisites for the successful deployment of digital communication strategies are cross-functional teams and an agile development approach. Effective communication strategies cannot be designed on a whiteboard and implemented in a waterfall approach — they need to be tested and gradually tailored to customer preferences and behaviour.
In consequence, the underlying decision services need to allow for flexible strategy management and configuration, and strategy performance needs to be continuously reviewed, discussed, and improved. Good decision platforms will support strategy version management, business outcome simulation, strategy staging from development to test and production, and champion/challenger testing.
In an agile environment, the strategy lifecycle involves continuous monitoring and measurement of strategy results, typically undertaken by the strategy management team. In joint meetings with business stakeholders, strategy results are periodically reviewed, and lead to the design and configuration of strategy changes. These changes are configured by the strategy management team and typically implemented as challengers to the existing baseline (“champion”) strategy, so that the impact of the change can be quantified. Before deployment, the modified strategy undergoes appropriate quality assurance measures before release into production. With the exception of the last step, all parts of the strategy lifecycle are managed between the strategy management team and business stakeholders and should not require any involvement of IT resources.
FICO Platform Puts You in the Driver’s Seat
FICO Platform brings all these components together. Analytics, segmentation, strategy management, strategy execution and customer engagement are all supported by the platform, and can be integrated with existing system stacks or legacy debt collection solutions.
Of course, digital collections does not stop with early collections. Once the infrastructure of FICO Platform is in place, it can be used for multiple collections areas, such as pre-delinquency treatments or even forbearance treatments.
In conventional environments (top row), the application of forbearance measures can be labour-intense. When customers indicate hardship, an understanding of the nature of the issue and an evaluation of the financial capabilities of the customer is required. The related discussions with the customer tend to require high operational efforts.
When the communication is swapped to a digital channel (bottom row), the assessment of the financial situation can be automated in the same channel in which the customers indicate their hardship, or, given customer consent, can even be retrieved through an Open Banking interface. Using advanced analytics, an appropriate temporary or permanent modification of the payment plan can be offered where expected customer behaviour allows. The offer is communicated and agreed in the same digital channel where the discussion started.
No doubt, the combined power of data analytics, decisioning and digitalisation is going to change the debt collection industry. With the right tools in place and an agile approach, you’ll be in the driver’s seat.