Mark Twain once said, “In the spring, I counted 136 different types of weather in 24 hours”. He also said, “climate is what we expect, weather is what we get”.
The weather impacts the financial performance for as many as 70% of all businesses.
Whether it is warmer or colder, wetter or drier than expected, these are the minor variations in weather that everyone experiences daily and that Twain refers to in his quote above. When we talk about the impact of weather on businesses and the economy, we usually think of storms, hurricanes and flooding. But it is the minor daily variations in the climate that have the biggest impact.
This is because they impact the fundamentals of supply and demand. How often have we listened to the CEO of a major corporate blame the impact of a warmer winter or a wetter summer for it’s poor sales performance? The impact to business is measured in units of volume and usage of products and services rather than pricing. For example, a warmer, drier winter means a retailer has more umbrellas and coats in stock than they could shift, or a wetter, colder winter could mean that they didn’t have enough. In either case, the business can underperform and it’s all the fault of the weather!
And it’s not just businesses that are impacted, as national economies ultimately feel the financial cost.
A study from Allianz, “The Weather Business”, reports that 30% of US GDP is impacted by the weather at a value of $534bn per annum.
In 2011, there were 11 major weather events that each cost the US economy $1bn or more, and yet the government’s weather relief budget was closer to $100bn.
So, what can be done?
Protecting against the fall-out from Mother Nature led to the introduction of weather derivatives in the mid-1990s. Led by the energy industry, many businesses now manage their risk to weather sensitivity by trading swaps against indexes that track average changes to temperature, such as HDD (“Heating Degree Day”) in winter months, and CDD (“Cooling Degree Day”) in summer months. However, the limitation of using these financial instruments is that they are not directly linked to the impact of a specific business’ P&L. They are generalized protection instruments, and therefore, limited.
Of course, Catastrophe Insurance has been around a lot longer than weather derivatives to provide financial protection against natural weather disasters such as earthquakes, floods and hurricanes. The sheer scale and complexity of assessing and managing risk and claims of catastrophic events has led to a whole industry of specialized insurance, reinsurance and retrocession.
However, we are now seeing the emergence of Weather Risk Management in the insurance sector. This fills the gap between the infrequent but high impact major catastrophes and the generic instrument of derivatives indices. Whilst the economic impact of a major event grabs the headlines, it is the more subtle effects of minor changes in weather that can have a dramatic impact on company profits and revenues.
And as a growing number of businesses are now turning to massive data driven solutions to model the impact of predictable variances in weather, this week, I look at one of the new InsuranceTech players in this emerging sector;
Meteo Protect are an insurance and reinsurance broker who offer financial products that protect companies and institutions when weather conditions adversely impact their business, profits and costs.
Earlier this week I skyped with Jean-Louis Bertrand, Development Director and Laura Hersey, Business Development Director from their offices in Paris. They explained the origins of the business in the weather risk management industry where they started by calculating the relationship between minor variances in weather to the sales data of individual businesses.
Jean-Louis told me about how they first got into the idea for this business back in 2007 when they looked at a ski resort that went bust after a warm winter. The team of 4 modeled the cash-flow of the resort directly to the impact of minor changes in temperature from the warmer weather which led to its failure as a result of the lack of snow.
This led the team to look at providing protection insurance based on using real time weather information matched against historical weather data. However, the team quickly found a fundamental flaw in this approach. The cost of buying the data that they needed each and every time they had to calculate a premium that was prohibitive. Simply, the margins in the insurance premium could not sustain the cost of data needed to calculate the premium!
So the team tackled the problem head on, and after a massive investment in IT, Meteo Protect built its own database of 30 years of global weather history. They also connected with base stations and weather satellites that provide real-time feeds across the globe. Their goal is not to predict the weather (goals must be achievable, after all!), but their objective is to “provide the best representation of the risk the customer wants to cover”.
Using historical data mapped to the company’s past financial results, Meteo Protect can understand what is “normal weather” for their specific business, the degrees to which weather variation has an impact on their business and, most importantly, price the risk of weather variation.
Jean-Louis explained that this “Weather Sensitivity Analysis” provides a transparent model that a business can use to test how weather variations will impact it’s cash-flow and P&L. Ultimately, this enables a business to buy insurance protection against financial performance in the knowledge that the risk has been assessed using massive amounts of data directly correlated to it’s own sales performance.
And none of this has been possible until now and as a result of the advances and availability of massive computing capacity.
The sheer scale of the technology deployed by Metro Protect is staggering. Meteo Protect now has over 80 billion weather data observations available and quality controlled.
This weather data is for a period spanning over thirty years. Using in-house algorithms, software, data, processes and expertise, they have produced over 50,000 models for 320 industry sectors.
The underlying tech is interesting too, combining the new and the traditional! It is mainly based on the R language for modeling and pricing with all the software development being done in-house in a Linux environment. This is a big data business and it’s approach to data management combines a mix of traditional open-source databases (mainly MySQL) with the massive capability provided by SAP’s HANA bigdata architecture.
Meteo Protect have been in business longer than most start-ups, but it is this latest development in technology over the past couple of years that caught my eye. They have bootstrapped the new business themselves and with support from some heavy weight carriers and from SAP, who will provide Meteo Protect on the HANA platform and as part of its FICO software. As we speak, Meteo Protect are in Proof of Concept stage in several sectors and are now looking to raise serious investment as they look to take this capability global.
Meteo Protect are proof, if ever it was needed, of the significance of being able to handle massive amounts of data to drive insurance business. I’m not sure if weather risk management the way that Meteo Protect are addressing it, could have been possible on a commercial scale ten years ago, let alone 5.