Bitesize InsurTech: Groundspeed Analytics
April 5, 2019 Chris Sandilands
Groundspeed Analytics helps insurers and brokers generate greater insight from unstructured commercial insurance submissions.
The business was founded in 2016 and raised $30m in July 2018 (according to the company, the largest Supplier InsurTech fundraise last year). Its co-CEO since then, Andrew Robinson, was previously president of specialty insurance at the Hanover (owner until recently of Lloyd’s managing agent Chaucer).
The company’s core belief is that 80% of information presented in submissions is not used. This includes loss and exposure schedules, sublimits and so on. The objective is to structure this information and allow insurers and brokers to incorporate it into their underwriting and pricing process.
The process currently has three main steps. First, data is ingested via API or via a Groundspeed portal. Files are then classified and data extracted, labelled, cleaned and normalised. Depending on the client use case, predictions are made (e.g. identifying potential clashes). Structured data is then fed back into insurers’ pricing models. This frees up underwriter time, allowing staff to focus on value-adding risk analysis and negotiation activities.
For brokers, use cases are often around generating insight from client policies to enhance their proposition to the market – for example, understanding where proprietary products could be created.
This is a complex problem. Andrew notes that the company has seen risk information presented in 250,000 different ways. Algorithms must understand this heterogeneity and interpret data at speed.
Groundspeed currently has “just over” 10 clients, all major carriers or brokers. Through these global relationships they are active in Europe. They have 70 staff, the majority of whom are engineers and data scientists.
The Oxbow Partners view
We’ve noted before that commercial insurance data InsurTechs are all the rage. Broadly speaking propositions fall into two categories:
- Data cleaners: These InsurTechs take the data you already have and tidy it up. Groundspeed is an example and Concirrus (see 2019 Impact 25), Risk Genius and Eigen Technologies are others.
- Data augmenters: These InsurTechs source new data for companies. The promise is that their data is more complete, more predictive or less onerous to collect than traditional sources. Cytora, Insurdata and Carpe Data are examples.
The operational and underwriting benefits of streamlining the ingestion of data and enhancing insight are clear.
Implementation – or transformation?
Insurers can engage with companies like Groundspeed on a spectrum from implementation to transformation.
Implementation is a narrow approach. Insurers might use Groundspeed to automate a part of the underwriting process. This would undoubtedly see some benefit, certainly in operational efficiency and potentially in underwriting performance if the actuarial/pricing teams can generate insight from the additional data.
However, the bigger opportunity is to use an InsurTech such as Groundspeed as the catalyst for an underwriting transformation. Groundspeed does not just automate the submission process, but it changes the capabilities required from underwriters. No longer do humans leaf through a submission to get a sense of a risk (something where experience can be helpful), but Groundspeed exposes underwriters to structured information and requires them to make data-driven decisions. This has implications for the whole target operating model – the people you employ, the processes you run and the technology you use.
If you are thinking about enhancing your underwriting processes, drop us a line.