The Problem
Adverse weather has a calamitous effect on companies. With climate change, droughts, floods, storms, and temperature swings pose greater risks than ever; frequency and intensity of weather abnormalities have doubled over the last 15 years. Farmers are the most obvious constituency imperiled. Food-processing companies are vulnerable as their costs of goods skyrocket when unfavorable weather strikes their key sources. Wind energy providers face disaster when the wind stops. To minimize their financial exposure in the face of weather-related adversity, they turn to the insurance industry for protection. But the insurance options available are inadequate. The French government e.g. has subsidized crop insurance but the base contract only covers the costs of production if the yield loss is >30% + a 25% deductible. Insurance against bad weather is available with only a few options, whereas the needs are highly nuanced, calling for policies matching the types of protection they require.
The Solution
Meteo Protect’s vision was to provide clients with insurance policies and customized price quotes based on a set of individual parameters. It developed a platform called Vivaldi for providing completely customized insurance for any weather-related risk. A key component of Vivaldi is a Web-based app that determines the right price for any particular insurance scenario a person wants. In the initial implementation using conventional computing technology, this process was impractically slow. Meteo Protect wanted it to be so fast that end users could adjust insurance parameters, immediately see the price impact, and then iterate perhaps dozens of times before committing to a particular plan. It created an app that lets customers state their policy specifications and then uses the SAP HANA® platform to aggregate huge volumes of weather-related data from multiple sources, analyze risks, and present price quotes - all in real-time.
The results
When clients ask for simulations - "what if I wanted to hedge against this, and what if I wanted to change this et cetera et cetera" – every time a replay of weather history for this client and for these parameters is necessary. And imagine you are in front of your computer and you need 25 price simulations before making your decision. If you wait one second between each, or if you wait eight seconds between each makes a huge difference.
The solution connects into many data sources including a 40-year climate history; current readings from satellites, sensors, gauges, and other global weather data sources; and other types of data such as commodity prices and crop yields. Within a second, SAP HANA analyzes more than 80 billion quality-controlled weather data observations to determine risk and provide customers with the most cost-effective financial cover. Meteo Protect dedicates one server to the SAP HANA database, configures two others as Web servers, and uses a fourth for calculating algorithms. Data upload includes over 35 million rows. The firm has already produced over 50,000 models for 320 industry sectors.
Metrics
• 8x Faster scenario pricing
• 12x Faster data upload (more than 35 mil. rows)
• Almost 7:1 data compression
• Complex query execution (data analytics) is faster by 1.982 times on average, up to 5 times
For their clients (farmers): They can test adaptive measures to climate changes (eg. modifying sowing and harvesting times, crop types, labor management practices), invest in new agrotechnologies (such as purchasing heat-tolerant crop varieties, and installing post-harvest storage facilities for a warmer climate). They can increase their investments and know they’ll be able to cover their staff salaries and fixed costs even in the face of prolonged unfavorable weather.
The Technology
There are 20877 users for the live system. The DB server has a Intel Xeon E5-2670 v2 processor in high frequency, with 8 CPU, 61 GB RAM and 160 GB of storage using discs SSD. For each web server, there is 1 CPU (Intel Xeon processor at high frequency), with 1 GB RAM. The server for calculating algorithms has 4 CPU Intel Xeon processors E5-2670 v2 (Ivy Bridge) at high frequency, with 15 GB RAM and 80 GB of storage in ssd.
Disruptive Factor
As Meteo Protect grows, so does the breadth of its service portfolio and customer base. Whenever a new client is signed up, it's usually much bigger than they are and often in a different geographic area or a new industry. With SAP HANA, whenever they need to initiate a new service or create a new policy or insurance program, the commissioning is extremely fast and reliable. Meteo Protect have dramatically cut their client waiting time because processing is extremely short; this also has changed the interaction between their clients and their under writing platform. For a young company trying to grow scalability is very important: They were was able to add new countries and clients easily, deploy their services and inject all known weather history into the system in order to produce prices rapidly and in a secure fashion. The company also benefits from the system’s security and reliability because they sell services to insurance and reinsurance companies and creating a new insurance product can potentially pose a big risk. Every time Meteo Protect price an insurance policy, they say the price to transfer risk from one company to another.
Meteo Protect aims to service insurance clients and insurance companies globally, to add more complexity in their calculation and to be able to rapidly create new products. They are looking to leverage more analytical and IoT applications and to make relevant information and processes available on mobile devices.
Shining Moment
* Finalist for the Hana Innovation Award in the Digital Trailblazer category in 2016.
* Entreprise Innovante des Pôles (awarded to technology SMEs with strong growth potential)
* MeetInnov Prize (awarded by a jury of venture capitalists and Business Angels at the
MeetInvest meetings)
