If you look at a chart of the UK’s GDP over the past 15 years, it’s pretty alarming. You can see when the last financial crisis hit. There’s a small but noticeable dip of about 6% between February 2008 and March 2009, followed by a slow and steady recovery. By contrast, when you get to 2020, GDP falls off a cliff – dropping by more than 25% between February and April. You can’t expect the economy to weather that kind of shock without lasting consequences.
Even if the economy recovers quickly, banks and other lenders are going to be feeling the repercussions for years to come. The UK is a highly leveraged society, and with millions of people now facing job losses, business closures and reduced incomes, it’s inevitable that many will find it difficult to repay or even service their debts.
How can collections teams cope?
To handle this huge increase in delinquency, collections teams will need to find ways to work smarter by harnessing new technologies. This doesn’t necessarily mean ripping and replacing existing collections systems. Instead, you can take a more pragmatic approach by building on what you already have and augmenting it with new capabilities.
As I explained in a previous article in this series, improving segmentation with predictive analytics is a good place to start. It’s relatively easy to replace existing crude segmentation techniques with a more advanced approach, and it gives you the ability to treat your customers as individuals, which improves the customer relationship and increases yield. But once you’ve brought your segmentation strategy up to standard, what should your next move be?
Orchestrating omnichannel collections journeys
From an operational perspective, there are four key questions that collections teams always need to answer:
- Which customers should we contact?
- How should we contact those customers?
- When should we contact those customers?
- What should we say to those customers?
Segmentation can be very helpful in deciding who to contact, choosing a contact strategy and designing appropriate treatments for each customer. But it doesn’t actually help your teams put their plans into action. To run an effective collections operation, you also need tools to help orchestrate customer journeys across all channels, and dynamically adapt those journeys as new information becomes available.
For example, if you can monitor how each customer is engaging with you at each contact point, you can personalise each customer journey based on how well your different contact strategies and treatment approaches are working. Intelligent decisioning using predictive models can automatically move individual customers to more effective contact channels or gradually escalate to use more robust measures while avoiding the use of heavy-handed or intrusive treatments until they are absolutely necessary.
How SAS can help
At SAS, we optimise and automate collections operations to improve customer-centricity whilst collecting more payments faster. Advanced analytics and journey optimisation capabilities make it easy to plan sophisticated, personalised collections campaigns and execute them at scale through smart automation.
Our solutions orchestrate hyperpersonalised contact strategies across digital and offline channels and optimise the sequence of activities at an individual customer level. By providing a seamless customer journey – optimised by customer channel preference and engagement across mobile push and pop-up messages, email, SMS, call centre interactions and direct mail – collections teams can ensure that each customer receives the right level of intervention for their individual case.
When calling customers is the smartest option, our solution can optimise dialler campaigns by automatically generating call schedules that help collections teams initiate phone calls to customers at the right times, boosting right party contact (RPC) rates.
We can also derive optimal messaging for each individual customer, helping you build tailored communications to address different types of customer needs, and using analytics on historical cases to suggest appropriate settlement amounts for each customer.
Building a foundation for smarter collections
Smarter segmentation and automated omnichannel orchestration can make a significant difference to the effectiveness of collections operations – and provide a solid foundation for the use of AI techniques such as deep learning and reinforcement learning, which is the topic I’ll be exploring next in the final article in this series.
In the meantime, if you’d like to learn more about how to get started, please check out our e-book The AI Enabled Collections Model.
