Reinsurance Group of America

Winners of the Reinsurance Group of America ‘Big ideas’ competition that run through EMEA. Our award winning Clothing-To-Health Risk analytics software allows insurance companies and employers to assess companies’ obesity related health risk.

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The Challenge

While in Silicon Valley on ABC accelerator program, we created a spin off product from our virtual workwear app to tackle the US health insurance market. The rise of obesity in the US is the main driver of the healthcare crisis, with costs spiralling out of control.
There was simply no tool for corporations to quantify & price their obesity health risk. We realised that instead of using body data to calculate uniform size, we used uniform size to calculate body data. This was a breakthrough!

The Solution

We reserved engineered our algorithm to produce an aggregated and anonymized obesity insurance score with 70% accuracy. The predictive power of our data was second only to previous medical claims.

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The innovative part was the non invasive & cost efficient manner of our data collection method. We just needed to download an existing uniform order sheet with the attached sizing chart, our machine learning algorithm and dashboard did the rest!

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This really excited the health insurance industry and the Reinsurance Group of America innovation team pushed out the product to 26 of their global markets. Unfortunately the workwear wearing market size, 20% of the corporate workforce, was insufficient to adopt a new data source to a very traditional underwriting practices.

Feel & Look

The visual geographic and traffic light colour scheme complimented the general ease of our data collection method. The aim was that insurance companies can understand their risk with a glance that become a major selling point.

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The team were professional, dynamic and energetic. I thought the idea was innovative and novel yet very practical... Immediately winning over the judges with their slick, cutting edge technology. The technology had an approachable front end and clever risk modelling at the backend.’