In this decision, the European Patent Office did not grant a patent on the concept of improving a weather forecast based on specific weather measures, e.g. temperature, precipitation or wind speed. Here are the practical takeaways of the decision T 1798/13 (Forecasting the value of a structured financial product/SWISS REINSURANCE COMPANY LTD) of 25.5.2020 of Technical Board of Appeal 3.5.01:
The “weather” is not a technical system that the skilled person can improve, or even simulate with the purpose of trying to improve it. It is a physical system that can be modelled in the sense of showing how it works. This kind of modelling is rather a discovery or a scientific theory, which are excluded under Article 52(2)(a) EPC and thus do not contribute to the technical character of the invention (see point 2.10ff.).
This European patent application generally relates to forecasting the value of weather-based structured financial products. The values of these products are based on specific weather measures, e.g. temperature, precipitation, hours of sunshine, heating degree days, cooling degree days or wind speed.
In Fig. 2, the forecast value of the product S13 is based on forecasted weather data S11 for a defined time period and a defined geographical area relevant to the financial product S12. A quality indicator S34 is calculated, based on the accuracy of the forecasted weather data S31 compared to reference weather data S32, S21. This is said to “enable both investors and providers of the financial product to make better-informed decisions concerning the value of the financial product” (page 2, last paragraph). The quality indicator is used S4 to calculate the final value of the financial product S41.
Here is how the invention is defined in claim 1:
Claim 1 (sole request)A method for forecasting a value of a weather-based structured financial product for steering of an optimal weather derivative portfolio based on specified weather measures comprising temperature and/or precipitation and/or hours of sunshine and/or heating degree days and/or cooling degree days and/or wind speed retrieved from a weather data measuring and monitoring system comprising:
calculating reference weather data at least including temperature data from historical weather data at least including temperature data stored in a database (16) or retrieved from an external weather-data measuring system (5) by means of a weather reference module (11) for a defined time period and a defined geographical area, wherein the historical weather data covering a plurality of years as a time series, is decomposed in portions with deterministic data and a portion with stochastic data, wherein the deterministic portions include historical trend data and seasonal pattern data, and wherein the reference weather data is determined for the defined time period and the defined geographical area defined in correspondence with the parameters of the structured financial product to be forecasted by establishing the reference weather data from the deterministic data, applicable to the defined time period, through auto regression, and from stochastic data determined for the time period;
establishing forecasted weather data by means of a weather forecast module (12) based on multi-year historical weather data and long-term weather forecast data covering one or more months and storing the forecasted weather data as multiple sets of forecasted weather data for subsequent time periods in database (16) assigned to their respective time period;
calculating weighted forecasted weather data by means of a weighting module (121) from the multiple sets of forecasted weather data stored in the database (16), wherein each set of forecasted weather data is weighted by a weighting factor having a value that increases from one time period to the next subsequent time period;
calculating a forecasted weather index at least including an average temperature, a cumulative temperature a number of heating degree days or a number of cooling degree days for the defined time period and the defined geographic area from the forecasted weather data, wherein the type of index is defined by a respective parameter of the financial product to be forecasted, and calculating a forecast value of the structured financial product based on forecasted weather data for a defined time period and a defined geographical area, wherein the forecast value is calculated by applying structural parameters of the financial product to the forecasted weather index determined from the forecasted weather data;
calculating a reference weather index at least including an average temperature, a cumulative temperature a number of heating degree days or a number of cooling degree days for the defined time period and the defined geographic area from the reference weather data by means of a reference module (13), wherein the type of index is defined by a respective parameter of the financial product to be forecasted, and calculating a reference value of the structured financial product based on the reference weather data, wherein the reference value is calculated by applying the structural parameters of the financial product to the reference weather index determined from the reference weather data;
calculating a ranked probability score for the reference weather data by integrating a cumulative distribution function of the forecasted weather data representing the actual relevant weather situation, and calculating a ranked probability score for the forecasted weather data, by integrating a cumulative distribution function of the forecasted weather data representing the actual relevant weather situation,
calculating a quality indicator by means of a quality indicator module (15), indicative of a forecasting quality associated with the forecasted weather data, based on the forecasted weather data and the reference weather data, wherein the quality indicator is calculated as a ranked probability skill score from the ranked probability score for the forecasted weather data and the ranked probability score for the reference weather data, the ranked probability skill score indicating the accuracy of the forecast of the weather data compared to the reference weather data according to the percentage of improvement in accuracy of the forecast weather data over the reference weather data; and
calculating the value of the financial product by means of a value forecasting module from the reference value and from the forecast value weighted by the quality indicator, wherein the influence of the forecasted value on the calculated value of the financial product is adjusted.
Is it technical?
The first-instance examining division had refused the patent application for lack of inventive step, “because no technical problem was overcome”. More precisely, the division considered that the invention had two aspects: a) defining and calculating a weather forecast, and b) defining and calculating the influence of the weather forecast on a particular financial product. The division could not find a technical problem solved by the implementation of either of these aspects.
On the one hand, the appellant agreed that the use of the weather forecast to define a financial product had no technical character. But on the other hand, according to the appellant, the invention improved the reliability and predictability of weather forecast data in general, which was a technical problem.
The appellant provided three main arguments. The first argument was that the forecasting was based on specified weather measures, such as temperature, precipitation, hours of sunshine, heating degree days, cooling degree days or wind speed, which represented physical, hence technical data. Here is what the board said:
Regarding the first argument, the Board agrees that a system for weather forecasting, for example, comprising sensors for measuring specific weather data, has technical character. The invention, however, relies on the use of already measured weather data. It could be argued that this (raw) weather data represents measurements about the physical world and is therefore also technical. The situation would thus be similar to that in T 2079/10 (Steuerung von zellulär aufgebauten Alarm-systemen / SWISSRE), reasons 4.2 and 4.3, which considered that physical parameters represent technical data and the choice of which physical parameters are to be measured are competences of the technical skilled person.
In T 2079/10, however, the invention was seen to lie in the improvement of the measurement technique itself, which involved technical considerations about the sensors and their positions. In the present case, the measurements themselves do not play a role, the improvement is in the processing of data to provide a better weather forecast.
Secondly, the appellant argued that the invention did not only retrieve and use the measurement data, but specifically calculated and further processed reference weather data and forecasted weather data. These steps operated on physical data and achieved the technical effect of improving this data. The boards reaction was as follows:
The applicant’s second argument is essentially that also an improvement in the weather data by calculating and further processing it is also technical. In the Board’s view this leads to the key issue in this case, namely whether improving the accuracy of given data of a weather forecast is technical. If it is not, then the details of the algorithm, the “mathematics” as the division put it, does not help.
The Board judges that it is not. The “weather” is not a technical system that the skilled person can improve, or even simulate with the purpose of trying to improve it. It is a physical system that can be modelled in the sense of showing how it works. In the Board’s view, this kind of modelling is rather a discovery or a scientific theory, which are excluded under Article 52(2)(a) EPC.
As Mellulis puts it (see Benkard, EPC, 3rd ed. (2019) on Art. 52, paragraph 232, translation from German by the Board): like the discovery, scientific theories also contain instructions for (technical) action. They are an attempt at a rational explanation of observed or expected processes based on natural laws or logical considerations. They are frequently based on a knowledge, expectation or presumption of laws, which can also be based on empirically gained knowledge. In terms of content, they resemble discoveries; there is some overlap here. They are not patentable even if they provide an explanation for activities that are in use.
This applies in the Board’s view to the understanding of “weather” in the present application. The modelling of weather in terms of historic or calculated reference data, predictions or established forecast data, trends and seasonal patterns etc. aim at a better understanding of “weather”, of the causal relationships and correlations between different kinds of weather data, thereby enabling better use of previous experiences. Thus, in the Board’s view, the improvement of the data in this case is rather an improvement of a model utilising a scientific theory and thus does not contribute to the technical character of the application.
Furthermore, the parametrisation of these models is ultimately influenced by the business requirements. The application explains at page 1, lines 9 to 26, that weather-based financial instruments have a start date, maturity date, are defined for a specific geographical region and at least one weather condition, such as temperature, precipitation, hours of sunshine, heating degree days, cooling degree days or wind speed. It is also the business person who, as an expert in weather-based financial derivates, has not only expertise about finance, but also about mathematical models and methods and weather-based parameters which are required to define these financial instruments.
The third argument of the appellant was that the calculated quality indicator gave the percentage of improvement in accuracy of the forecast over the reference simulation, and this was a novel and inventive approach because conventional solutions to improve predicability of weather forecasts would have been to provide more sensors and to make more measurements. But also this argument did not succeed in front of teh board:
The appellant’s third argument is that the quality indicator is technical because it improves the data in a way that would conventionally have been done by technical means. In the Board’s view this also fails for the reasons given in the previous paragraph.
The situation in this case is comparable to T 2331/10 (Operating wind turbines / GENERAL ELECTRIC COMPANY), which concerned forecasting electric power production based on weather forecasts and wind turbine parameters. The Board considered that the improvement lay in the area of modelling and algorithms which by themselves did not achieve a technical effect (reasons 5.2). The Board also found that the predicted forecast data signal was not a physical variable of an underlying technical system and was not linked to its functioning, but it had a business purpose, namely to make sales of electric power generation with increased confidence (reasons 5.4 to 5.5). In the present case, the weather forecast and the quality indicator do not serve a technical purpose, such as improving the measurement system, the collection of measurement data, the arrangement of sensors, or the like, but are (mathematical) values with a business purpose, namely determining the value of the financial product.
The board therefore concluded that the sole technical elements in claim 1 were the storage of data in a database and a computer-implementation. The objective technical problem thus was how to implement the non-technical method of forecasting the value of weather-based financial products on a notoriously-known general purpose computer system. Following the COMVIK approach, claim 1 was found to lack an inventive step, and the appeal was dismissed.
You can read the whole decision here: T 1798/13 (Forecasting the value of a structured financial product/SWISS REINSURANCE COMPANY LTD) of 25.5.2020