Last week saw the return of the in-person RIMS (Risk and Insurance Management Society) conference, this time held in San Francisco. There was no better place than Silicon Valley for us to hold a meeting of InsurTech minds.
Sixteen insurers, InsurTechs, and hangers-on like me, got together to talk about what insurers can do to make best use of all the data we are creating in the world. I don't need to pull out another statistic about the amount of data we create each year versus all of human history - the truth is we all know it's something incomprehensively large.
The group needed very little encouragement to get talking about data - an hour really wasn't enough time. What did we talk about? For me, three keystone issues stood out.
- We need to work more collaboratively across the InsurTech ecosystem.
- We need to get better at using data and our learnings from it to improve pricing models.
- We should extract more insights from our data and move this up the value chain.
We need to work more collaboratively across the InsurTech ecosystem
Start-ups can and should work with incumbents to get full value - don't just throw data over, add insight, and create actionable information from it. For their part, incumbents need to agree data standards. Lloyd’s Core Data Record (CDR), which provides the critical transactional data that needs to be collected by the point of bind to drive downstream processes, is a good starting point. But we need more.
We need to get better at using data and our learnings from it for better pricing models
The feedback loop between claims and pricing is often missing or poor. We can get better at pricing insurance for the specific risk rather than the generic category it happens to fit under; maybe even start pricing at the transactional level. Good actors will share more data to help their insurers with this - so they'll get a better price. If they don't get a better price, it will be because their risk is higher, and we can tell them why, with specifics, so they can work to improve.
The industry can also get better at using data to challenge underwriting assumptions and traditional biases. For example, one underwriter explained how his firm had analysed the point at which holidaymakers chose to purchase their travel insurance. The results overturned the conventional assumption that holidaymakers who chose to purchase insurance at the last minute are more likely to make a claim.
We should extract more insights from our data and move up the value chain
Data is a tool we can use to improve regulation – underwriters should use these insights to help policymakers understand new and emerging sectors, like the sharing economy. We should empower clients – and we should help them to understand their risks and how the data can mitigate losses, thereby building trust and lasting partnerships. Ultimately, we need to incentivise players to share good quality data – and we can do this by giving back value and by helping customers manage their risks proactively.
Finally – everyone has a role to play
Underwriters, brokers, customers and service providers all have an important role to play in this. Brokers, for example, need to identify whether they already hold the right data. If not, perhaps they could consider what they need to do to capture it systematically? Insurers should consider how they can leverage data in their pricing models more effectively, or to help launch new products and services. Service providers should perhaps consider how they can provide products and services that enable the collection and analysis of data, and how they can support clients with all these challenges.
Thanks again to everyone who participated in the roundtable at RIMS.