Concirrus and Meteomatics Partner to Provide Insights into the Impact of Weather on Insurance Claims
Concirrus announces new partnership with Meteomatics to deliver integrated benefits of their high-quality weather models to Concirrus Quest customers.
London: Leading InsurTech, Concirrus is delighted to announce a new partnership with Meteomatics, the innovative weather data provider, to deliver the integrated benefits of their high-quality weather models and wealth of expertise to Concirrus Quest customers.
With an increased frequency and severity of extreme weather events, it’s unsurprising that there’s a knock-on effect to the volume and scale of global insurance claims.
Concirrus Director of Alliances, Graham Libaert comments: “At Concirrus, we set high expectations for our data partners and employ robust methodologies for assessing their technical capabilities and quality; Meteomatics not only met our requirements, but continued to provide frictionless support to our validation and integration processes.”
Meteomatics COO, Sam Nixson's said: “Meteomatics loves to work with innovative, forward-thinking organisations, creating new, data-led business insights and opportunities; by integrating our Weather API, Quest customers will have the ability to harness new, external data sets to bring context to their existing data, providing a new powerful predictive capability.”
Concirrus has made significant steps to quantify the impact of weather conditions on global maritime casualty claims, by analysing the behaviours and scenarios which display propensity to suffering an incident. This will soon be ready for adoption by Quest customers.
Here are a few of the lessons we have learned along the way…
- No two data-sets are the same.
Particularly when exploring ‘big’ data, it’s essential to perform a 4V assessment (Volume, Velocity, Variety & Veracity) from the outset so that you fully understand the dimensions of the data and can establish quality metrics which provide a baseline measurement.
- Have a clear value outcome in mind.
It is easy to become distracted during the discovery process - as new findings arise the more you explore. By all means take these new findings into account and be open to change but ask yourself whether they impact the value you set out to achieve. Then, you can decide whether to dig deeper or resolve into backlogs for investigation at a later time.
- You need a powerful machine.
Mining and attaching billions of data points on a global basis requires significant computing horse power AND a well-designed data science environment. This helps to establish relationships between the data-sets quickly and produces results which are statistically quantifiable and unbiased.
- No two partners are the same.
Concirrus invests significant effort up-front to research and select preferred partners to collaborate with. We want to establish long term relationships with our partners based on a common set of goals and ‘mission compatibility’ is essential for continued delivery of ongoing benefits to the market.
“As an organisation, working closely with our customers and the wider insurance community, we continually assess and validate new sources of quality data to add increasing value to our offerings. A tsunami of information heads towards the insurance market each day and a significant part of the value we provide to our clients is in the heavy lifting of validating and extracting simple, useful insights from big data in a consumable manner." Concludes Libaert.
Concirrus is the creator of Quest, an insurance software platform developed with, used and trusted by insureds, insurers, reinsurers and brokers around the world. Quest allows existing and new data to be ingested, understood and presented in a way that provides valuable insights to help improve loss ratios.
Meteomatics is a global commercial weather service provider whose Weather API delivers quality weather and environmental data for any location and time series, worldwide. Meteomatics has also designed, developed manufactures and operates its unique Meteodrones to gather environmental data at all layers of the lower atmosphere to improve numerical weather forecasting for all sectors that are impacted by weather.