BE1027498B1 - Advanced system to make financial forecasts based on energy consumption data - Google Patents

Abstract

The present invention relates to a method that is integrated into computers for the purpose of enabling energy suppliers to make predictions about (i) future energy use and consumption of their customers, (ii) future retention of customers, (iii) future cash flows, and (iii) the impact that customers - whether or not on an individual basis - have on the operational costs of an energy supplier.

Description

-1- Title: Advanced system for making financial predictions on the basis of energy consumption data Technical field of the invention The present invention relates to the field of data processing, and in particular the processing and analysis of energy consumption data, the development of future consumption models and the facilitation of (financial) reporting in this regard.

Background Taking into account recent evolutions in the electricity and gas markets, and in particular supply and distribution on the one hand, and high competition on the other, suppliers of such energies are more and more confronted with uncertainties. This compels them to take measures that on the one hand make them more resistant to future evolutions, and on the other hand offer the possibility to develop products and services or to adapt existing products and services in function of future market evolutions and customer needs.

The large amounts of data available to such suppliers (whether or not supplied by third parties) provide an excellent basis for an in-depth analysis, especially in areas such as (i} controlling, accounting and financial reporting, (ii) operational aspects and obtaining guarantees in terms of revenues and cash flows, and (iii) market dynamics and customer management.

Description of the invention

-2- The method described herein allows energy suppliers and other intermediaries who develop activities in the energy market to obtain additional insights about a business based on the customer data they have, whether or not originating from third parties, such as distribution network operators and regulatory authorities. large number of processes that are essential for an energy supplier, such as:

1. “Imbalance Accounting”: The purpose of the processes behind Imbalance Accounting is to calculate a monthly commission for on the one hand the invoices to be drawn up and on the other hand the invoices to be received, including the underlying aging overview and matching this to the consumption view. Two approaches are used to calculate these provisions, namely follow-up from the balance sheet positions (invoices to be prepared and invoices to be received), and from the income statement (profitability, full current result + adjustment of the last 3 financial years), difference between current and future sales and profit, taking into account the results already recognized in the accounting records during the previous periodic close);

2. “Energy balance”: The purpose of the energy balance is to provide a progressive insight into the different energy flows that are relevant to the gross margin. More measurements and rectifications, more insight into costs and all additional market data ensure that the energy supplier can adjust its view of the past, which is a process that lasts up to 38 months after consumption month. This means that the results of previous consumption months can be influenced up to a few years after the date.

The energy balance provides an aggregated insight per consumption month into the volumes, and the associated euros, of the entire customer portfolio based on metering type.

3.

5. This is especially important for annual customers. The meter reading | {| This is done manually here by the distribution network operator. These "meter readings are spread over the year, approximately 1/12 per calendar month, which means that not all meter readings have been taken at year-end. Approximately 50% of the turnover is therefore based on" estimates. Only after X number of years and after final reconciliation at market level is a complete picture formed of the measured volumes. == N Sa Within the various energy flows, a distinction is made for volumes between measured loops (Billed / Settled) and divided {Unbilled / Unsettled} volumes. Here the principle is used that the volumes on the turnover side are leading, whereby the market information with regard to energy balance is used as a stepping stone, {| In addition, this method makes it possible to provide customers with insights into their income (amounts and volumes invoiced per energy flow and per consumption period), taking into account, among other things, the consumption profile of the (categories) of customers and the temperature.

The method can also display an estimate of the expected revenues for periods that have not yet been billed based on the active connections. A certain sequence is used. In concrete terms, we first look at the measured consumption that is available at contract level. If no measured consumption is available, it is switched to the individual estimated consumption of the distribution network operator. If both sources do not contain data for a particular connection point, the consumption that occurs in the snapshots that are sent monthly from the distribution network operators is examined. If this also does not produce a result, one falls back to the average consumption per type.

-4- consumption profiles and per distribution network operator. Allocation and reconciliation are taken as the reference volume. In addition, the method offers the possibility of an aggregated and detailed view of the various corrections that must be made so that the total turnover will be in line with the market data. After a “bottom up” calculation, a “top dowm” settlement is made here again of the volume differences per tariff and the corrections are calculated on the basis of the detailed not yet invoiced unit prices. make data predictions regarding:

1. customers who may cancel their agreement with the energy supplier in the future;

2.predict payment behavior of individual customers, in particular in case there were (large) differences between the sum of the periodic advances paid by customers and the final settlement they receive, as well as the impact of such payment behavior on the cash flow position of the energy supplier; and

3. the impact that individual customers have on the processing and operating costs of the energy supplier.

As far as the first component of the method is concerned, the analysis enables an energy supplier - taking into account its position in the market - either to develop specific offers, whereby several energies may or may not be combined (e.g. electricity + gas) , or not to make further efforts to retain a particular Client. As far as the second component of the method is concerned, insights can be obtained about the pricing of certain products or combinations thereof, how these can best be adapted for the defined

5 customers and customer segments, and how within this (intended) pricing the profitability (net margin) of the company is affected. Of such. Insights make it possible to predict probable price evolutions and the impact on turnover and profitability well in advance, so that suppliers can respond to these simulated or expected evolutions. Subsequently, taking into account the above calculations and generated outputs, energy suppliers can make informed decisions about their product and service offering.

Such analyzes can be performed on a regular basis on the basis of the method described herein, in order to verify and / or obtain confirmation that the current strategy is in line with the previously generated analysis results, or the strategy for the short, medium and / or or long-term adjustment.

Background Art The system described herein has a number of differences from the prior art. | Existing “business intelligence” applications enable companies to gain an up-to-date picture of their financial situation based on existing data, but lack the necessary parameters to make effective predictions for the future.

The parameters that the method described herein takes into account include the following in: - models to predict future energy prices;

-6- - models to predict future profitability of the company, taking into account, among other things, developments in the above future energy prices; - creation of models to absorb energy portfolio risks, to be factored into price models and pricing of energy products and 19 combinations of energy products; - parameters to predict and allocate market risks and costs; - current and future costs incurred to win, serve and retain customers; | - etc.

| Unlike prior art tools, the outputs generated by the method described herein enable the user to take various actions: - adapting the current product and service offering; - creation of new products or services; - make automated comparisons, periodically, of the predicted evolution with the current state of affairs, so that, if necessary, the chosen and applied strategy can be adjusted and adjusted.

or can be filled in completely differently; - processes and management practices can be adapted; - etc.

Claims (4)

-7- Conclusions A computer-implemented method that allows a user (A) to simplify the periodic financial close process, determine invoiced and unbilled revenue, and calculate current energy balance based on current energy consumption data (1). , as well as (2) make predictions about (i) future customer behavior, (ii) future price evolutions in the energy markets, and {iii} costs (more specifically the costs of winning, serving and retaining customers) and margins that can be expected by the energy supplier, taking into account the predictions generated by the method in steps {i} and (ii), The method described in claim 1, which, on the basis of the predictions and on the basis of the parameters set by user (A), automatically proceeds to (1) a segmentation of the various current customers, (ii} calculating the expected financial margin of the energy supplier, and (iii) indicating which customers may change their behavior in the future or terminate their energy supply agreement, in order to enable user (A) to gain insight generate reports on the realized and future estimated profitability (net margin) of his or her company, the predefined customer segments and individual customers. The method described in claim 1, wherein the method automatically sketches profiles of customers on the basis of energy consumption data in the past, in order to enable energy suppliers and / or intermediaries to - develop and offer specific energy products. to the -8- market, taking into account, among other things, their cost structure, expected price evolutions, etc., The method stated in claim 1, which is applied either within an environment designated by user (A), or by a third party (the patent holder or a third party designated by the patent holder) acting directly in the name and / or on behalf of user ( A).