According to PPC data, the leading power generation and supply company in Greece (with a 64.5% market share), before the energy crisis, Greek households were paying € 0.11/kWh which included the price adjustment clause. Between October and December 2021, the price per kWh rose from € 0.19 to € 0.29 before falling to € 0.13 after a power subsidy offered by the Greek government.
Even despite the state’s power subsidies, which in any case cannot last for long, the rise in energy prices is high, meaning that the risk of consumers delaying payment and/or being completely unable to pay their energy bills is equally high.
WEMETRIX conducted a survey which showed that debts to energy providers for the 3-month period from October to December 2021, more than doubled compared to the same period the previous year, both in terms of money owed and the number of indebted households and enterprises.
In the same survey, WEMETRIX captured consumers’ ability and willingness to pay. Interestingly, the survey shows that 51% of households are or will probably be unable to pay their bills in full in good time. The respective percentages for small and medium-sized enterprises (SMEs) are even more worrying. A huge 64% of energy-intensive SMEs, such as bakeries, car body shops and print shops indicated that they will be unable to pay the bills issued within the last three months of 2021 in full in time.
Energy providers have already begun putting in place debt repayment schemes for both households and enterprises. However, this does not solve the problem. It’s often the case that after the first or second instalment is paid, customers cannot keep up with the debt repayment plans; several customers also ask for new repayment plans. It seems that energy providers are following the same ill-fated approach taken by banks when they were faced with non-performing loans, where across-the-board schemes were put in place that only took into account the size of the debt, regardless of the debtor’s profile. It’s also illustrative that the idea of “the more you owe the more instalments you get” favours non-payers and results in losses for energy providers. It’s also interesting that electricity bills contain a charge (what you might call a hidden charge, listed under ΛΠ1) the majority of which is used to cover uncollectible amounts and power theft.
According to WEMETRIX survey, four out of five energy consumers are absolutely or probably in favour of entering into a debt repayment plan with their energy provider even if the deadline for paying their bill has not expired or even if their bill has not yet been issued. This is an international best practice known as reaching an amicable solution or amicable settlement. Reaching an amicable solution requires energy providers to offer a viable repayment plan based on the consumer’s own profile. By “profile”, we mean the way the consumer pays their bills over time, the seasonality in their consumption, but most importantly their means of subsistence, such as their occupation, income, how they prioritize their debts, their marital status, and so on.
Neither banks in the past nor energy providers nowadays have adopted this approach, as they have several thousand customers, they do not have much of the raw data needed and they do not have adequate amounts of historical data for comparative purposes.
So, what can be done given that it appears that the energy crisis will last for the next two years? How can we bridge the gap given the evident willingness of most consumers to pay their bills according to their means?
Technology holds the answer to these questions. Artificial intelligence and machine learning algorithms can very rapidly process large datasets and make timely (3 months earlier), valid (88% accurate) predictions about the possibility of any given consumer needing to enter into a debt repayment plan and therefore allow the energy provider to offer a customized repayment plan as a solution. Algorithms keep track of consumption and payment behaviours through the energy providers’ systems, integrate profile characteristics provided by the consumers themselves and compare aggregated data attributes from 20,000 micro-regions inside Greece in order to classify consumers into appropriate profiles. Significantly, there are 74 profiles in Greece, with identical or similar (very slightly different) electricity and natural gas consumption behaviors.
At the same time, special applications can offer interactivity, allowing consumers to constantly update the algorithm as their life circumstances change (e.g., unemployment, divorce, illness etc.).
The use of such applications allows energy providers to achieve their main goal which is constant communication with their customers in order to avoid a hostile atmosphere on both sides, which was what happened in the banking sector. Moreover, continuous cash flows are bolstered. As shown by WEMETRIX’s survey results customers want to pay, but want to do so based on their own profile and circumstances. Actually, such applications are now collectively known as Customer Value Management (CVM) tools, since all communications between energy providers and customers are now related to “empathy”. Customer Value is confirmed by matching purchases to payments. CVM solutions for debt repayments often lead to important cost decreases for energy providers, since they no longer need to involve debt collection agencies and law firms. They also increase the cross-selling (X-Sell) of other services and products (such as green appliances) to consumers who need to lower the cost of the energy they consume.
