Many small business prospects are new or immature market ventures without any prior loss history.

To deal with this, insurity company Valen Analytics has unveiled a new ‘Unavailable Loss History Model’ for workers’ compensation – a predictive model that can accurately price and assess risk when there is no loss history available.

The model uses a combination of third-party and synthetic variables derived from Valen’s extensive workers’ compensation data consortium – a granular data set of approximately 650,000 policies presenting $7.6 billion in premium – to indicate risk quality based on how similar policies have performed in the past.

“Being able to deliver valuable insights despite the absence of a key piece of information like loss history is a true testament to the power of partnering around data,” said Kirstin Marr, president of Valen Analytics.

“We think our new Unavailable Loss History Model will help our carrier partners get into the small commercial market. The reality is, there’s no easy way to get into this market and to spend an enormous amount of time manually evaluating a policy like they would for medium- or large-sized accounts – they simply can’t make money as a business doing that. So, they have to invest in more advanced, automated data solutions that enable them to assess the risk, validate the business, price it accurately, and feel confident that they’re managing the risks of their own growing portfolios.”

Typically, carriers looking to price policies for accounts without prior loss history would run the account through a loss history model and then make an educated guess based on the results of the model.

“We’ve been able to amass a number of policies, which, at the time they were written didn’t have a loss history, but because we’ve had our data consortium maturing for so long, those policies now have a loss history,” explained Marr.