Moving collection to resolution

23rd March 2022

Can combining data and a human approach hold the key to smarter management of local authority debt?

In Helping councils address tax arrears in a sustainable way, we examined how the pandemic has created new types of council tax and business rates customer who are in debt, and we explained why data can support personalized and effective debt recovery. This follow-up post takes a deeper look at how smart use of data can underpin the move towards a debt resolution approach that’s appropriate for local authority finances as we start to recover from the pandemic.

Two trends are driving the need for a smarter approach to debt resolution. The first is helping people who find themselves in financial distress after a lifetime of reliable payment because of COVID-19. Traditional enforcement approaches may be neither appropriate nor effective for this group. Secondly, the financial pressure on local authorities makes it more important than ever to resolve debt (even if that means writing it off) and to minimise the number of recurring debtors.

Deeper understanding

The key to this smarter approach is to build a deeper understanding of individual customers. The more a local authority knows about its customers who are in debt, the better equipped it is to segment customers who have debts and apply tailored approaches. For example, if a council knows it is dealing with a customer who owes the authority money for the first time, with no history of missed payments, collections teams can take a compassionate approach to resolution that lets the individual know they are going to be helped rather than penalised.

Segmentation by age and demographics is also valuable. Despite the drive to digital, older individuals or low-income families may not have the skills or access to use services online, and face-to-face interaction may still be the preferred route. Younger, ‘digital natives’, on the other hand, may be happier to self-serve using apps or web chat.

So, how can local authorities move towards segmenting customers owing money to improve collection? We’ve identified three key steps:

1. Data collection and interpretation.

This starts with data that’s already held internally about the specific debt (e.g. name and address information and council tax payment history). It can extend to other internal data that the council holds about an individual, for example outstanding penalty charge notices, former tenant arrears or housing benefits overpayments. Together this data will begin to build an insight into their financial status and ability to pay. Then, using data from government departments such as the DWP or HMRC (as made possible by the Digital Economy Act), and credit referencing agencies who provide propensity to pay or open banking data, local authorities can further refine the picture of an individual’s financial position. CivicaCollect, for example, brings together all of an individual’s debts, and pools information from other council systems, creating a single view of debt and making collection more informed and efficient.

2. Data cleansing and enrichment.

To be of genuine value, data needs to be as correct and complete as possible. Something as simple as having the right address can significantly improve the likelihood of repayment. It’s therefore crucial to validate the accuracy of data and where possible, to enrich records with extra details (for example telephone numbers or email addresses) if these are not present.

Similarly, a customer’s date of birth can be the difference between tracing them to a new address or not, as it’s often the unique identifier that confirms identity.

3. Predictive data analysis.

Once a clean and comprehensive dataset is available, modern analysis tools can start to reveal the patterns and trends that effective collection strategies can be built on. For example, historic payment data is the most reliable indicator of how an individual will respond to support or enforcement actions. Analysing this data can predict the type of resolution strategy that would be most effective, so revenues managers can spend more time working directly with the people who most need their help. Findings can also be refined further using data analysis insights on an individual’s geodemographic details.

Personalised approach to resolution

Southwark Council's Income Operations Team has proven this approach works. The Council uses CivicaCollect to take a personalised, customer-centric approach to collections. With all the information in one system, the team profile customers with problem debt. Instead of going down the enforcement route, the Council offers an affordable, personalised payment plan covering all of debts handled by the team. Southwark now makes collections with fewer enforcement visits, saving costs for the authority and its customers.

Using this three-step process can ultimately help shape future service provision. By segmenting customers, it helps local authorities to refine their collections process to improve the chances of long-term resolution of debt problems. It becomes possible to match customers with their preferred communication channel and to apply a recovery path that’s most appropriate to an individual and therefore likely to succeed. And by providing insights into the likelihood of collection, it provides a more accurate and holistic view of a local authority’s overall financial position, helping organisations plan services better for the future.