By Colette Land (Data & Analytics Leader at Experian)
The challenge of data quality and speed of data correction
Imagine you’re a small food retailer who is told that, from tomorrow, you’re to deliver thousands of food parcels every month to new customers and collect payment. There’s no option to stop any deliveries. However, there’s a catch; you have addresses but you don’t know the names of many customers you are delivering to and you know in advance that some customers (but not which ones) have already moved to a different address and some properties are vacant (but you don’t know which ones). You then need to bill and collect the money for the orders whilst also ensuring that if any customers are in vulnerable circumstances, you offer appropriate support.
It’s easy to see that the challenge quickly becomes one of data quality and speed of data correction. Although a little crude this is analogous to the situation faced by energy suppliers appointed under Ofgem’s Supplier of Last Resort (SOLR) and, to some extent, by energy suppliers as consumers move in and out of properties and consume energy.
Here’s some practical advice on how suppliers can easily use data basics to minimise future bad debt losses and address the challenge of missing customer details. This guidance is especially pertinent for suppliers appointed under Ofgem’s Supplier of Last Resort (SOLR).
What were the arrears trends facing domestic energy suppliers in 2021?
In 2020, late payment of utility (energy and water) bills increased substantially, which then flowed through into a swell of later stage arrears (bills unpaid after 6 months). This has reduced substantially, and the annual arrears spike in 2021 was not as high as last. This is good news but it’s an incomplete picture. When customers amass a significant deficit on their utilities balance they can spread the debt on a payment plan and repay the debt alongside their ongoing consumption. If the debt cannot be repaid in a short period then the payment plan is classed as an ‘arrangement’ with a credit reference agency.
Experian’s insights reveal a substantial increase in utilities arrangements over the past year, with energy driving the majority of the increase. Therefore, what we’re now seeing is customers amassing energy debt and repaying this over longer periods in addition to their continuing consumption. Ofgem’s data is consistent with the above, though the increase is not as pronounced. According to Ofgem’s data portal, over the last 12 months, there’s been an 11% increase in the volume of electricity accounts with a debt arrangement. Interestingly consumers in arrears without a debt plan in place have seen their debts increase by an average of 27% over the last year.
Will the increase in arrangements to repay debt result in additional losses for suppliers?
The ‘perfect storm’ phrase is being used a lot. The cut to universal credit that was expected to affect 1.5m people, the increase in National Insurance in April, the considerable and multiple increases in the price cap all occur in quick succession. Add into this mixing pot the c4m customers, and counting, whose energy supplier has ceased to trade and it’s likely that their monthly payment (just to cover energy) will increase, and any debt will now likely come under the jurisdiction of the administrators and face collections accordingly. So yes, I think the increasing number of customers repaying energy debts over extended periods combined with increasing energy costs is a growing problem. Although arrears trends aren’t particularly elevated at the moment and bad debt may be within expected levels there is an undercurrent in credit risk data that customers are starting to struggle with energy debt. Given the current climate, it’s likely that an increasing segment of consumers are likely to be in difficulty this winter. For suppliers, this is likely to turn into an increase in aged debts, collections costs and bad debts over the next couple of years.
What can suppliers do quickly and easily to minimise future credit losses?
The situation facing suppliers is challenging. Rising wholesale prices, more customers needing help and support, regulatory pressures layered on top of the pandemic and reduced profits mean suppliers need to focus efforts on leveraging data quickly and efficiently and reducing bad debts. The problem facing suppliers appointed under SOLR accentuates this. On the one hand, it’s an opportunity to gain an influx of customers, economies of scale and generate profits. On the other, there’s a potential that you open many accounts that will result in high write-offs and credit losses. To limit future bad debts it’s crucial that suppliers do a data quality check and ‘filling the gaps’ exercise on their (newly allocated) accounts.
Four ways energy suppliers can use ‘data basics’ better to limit credit losses, especially when appointed under SOLR?
1. Occupiers (unnamed occupancy sites) need to be ‘named’ as quickly as possible.
This applies to all suppliers but especially those appointed under Ofgem’s SOLR. In the SOLR most suppliers will not become responsible for the collection of debt owed to the previous supplier (unless they choose to take this on). They will become responsible for all energy billed to the acquired supply points. For any credit risk manager, this will be daunting as the new portfolio will include a portion of ‘occupier’ or unnamed accounts. To limit ageing debts that are difficult to collect and often end up being written off, it’s imperative to accurately allocate a name to occupier properties as quickly as possible. Experian can help with this process using our vast data amassed through credit reporting by banks, building societies, telecommunications providers, car loan providers and utilities. Utilities suppliers can provide a list of occupiers, or ‘void’, addresses and associated time periods and we can check for evidence of occupancy within the period provided. The returned data includes summary information, evidence of occupancy and details of occupants.
2. Data cleanse – get the basic customer details right.
This applies to all suppliers but is particularly important for those appointed as SOLR. The quality of energy suppliers’ customer data varies considerably. Often customers that are believed to live at an address have moved on, carrying a debt that should be finalised and the name held against that address is incorrect and needs updating. Incorrect details or missing name details, titles or dates of birth, limit the supplier’s ability to understand consumers’ eligibility for various schemes, limit the effectiveness of communications and, should the account progress through arrears to debt collection, often hinders collection efforts, particularly when debts are pursued through the courts. A simple and easy step suppliers can take is to request a data quality assessment of customer data (or on a newly acquired base under SOLR) from Experian to get to grips with the size of the problem and potential for improvement.
3. Understanding duplicate customers on your base, better known as ’Single Customer View’.
The above data quality exercise can be also used to understand the extent of duplicate accounts on a suppliers’ customer base. This can apply to all suppliers but in particular, those appointed under Ofgem’s SOLR. In this situation, the newly appointed supplier can undertake a duplication exercise against their existing ‘final’ debt book to match this to their newly acquired customer base. This can identify several duplicate accounts where efficiencies and improvements could be made in debt collection across multiple accounts where they belong to the same person. Experian can help understand the scale of duplication in a suppliers’ base (or newly acquired base).
4. Quickly identify customers who are financially struggling and understand customers’ ability to pay
Experian’s data can be used very simply by energy suppliers to identify which of their customers:
- are already in financial difficulty and have fallen into early arrears on their credit obligations,
- can afford their current energy bill and /or their debt repayment plan (R/A/G flag provided to show it is unaffordable).
The above is imperative to support Ability to Pay assessments, to limit debt build-up and inevitable bad debts. Using data in this way makes sense for customers too as it helps suppliers signpost additional support and prevent further stress for customers who simply haven’t got the means to pay.
Conversely, Experian’s data can also be used to understand which customers could afford to repay debts quicker.
The data exercises described above are very quick and easy to perform on a one-off batch basis or initial trial to understand the potential value for suppliers.
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