Unstructured Unlocked by Indico Data

There are a handful of genuinely useful observations - particularly around data not being recycled downstream after triage and the idea of 'pricing for the future' by underwriting today - but most of the episode is consumed by high-level generalities about legacy systems, silos, and 'consistency of data.' The promised 'top three recommendations' list yielded only one point before the show ended, which illustrates the padding problem.

“Take triaging for example. Sovs are sent in by a broker and there's a data enrichment to prioritize risk based on appetite. But once that happens, is the data then also reused for risk analysis, pricing, accumulation, management, portfolio steering risk? Rarely.”

“to continue, for example, just increasing rates 50% every year, it's not going to help everyone. So how do we price for the future? By underwriting today and making sure there's a softer land on that five year premium if somebody buys a policy today.”

The 'pricing for future risk while underwriting today' framing and the argument that granular property-level data could re-open markets that carriers have bluntly exited are the freshest angles, but the bulk of the content - legacy anchors, AI-as-enabler, silos, start-with-a-pilot - is thoroughly recycled B2B tech-in-insurance discourse.

“I also think, um, there's an issue around trying to adopt AI for AI sake. It's a buzzword, it's everywhere.”

“really I think um, it's an adoption point of view operationally, but really finding the right use cases. And I honestly don't think we're all there yet in understanding the true value of AI”

Andrew Holdway is a legitimate Swiss Re practitioner with real carrier-side history and credible examples from named programs (Flood RE, Canadian provinces, Bellwether), but his role is Head of Partnerships - a commercial/BD function - rather than a chief underwriter, CTO, or risk modelling lead, which limits the depth of technical and operational insight he can offer.

“I came from a carrier before I joined Swiss Fri, and carriers do spend a lot of time trying to educate their business partners about what their preferred risk appetite is”

“I even used to try and influence their prioritisation with donuts and cookies so they would work on my broker business first”

There are some genuinely specific data points - wildfire risk modelled at 10-to-20-yard resolution, the Bellwether partnership with Google X for 1- and 5-year wildfire views, Flood RE in the UK, Canadian provinces using flood data - but no hard ROI figures, no named carrier case studies, and no revenue or loss-ratio metrics anywhere in the episode.

“we looked in quite granular detail on the maps of locations within 10 to 20 yards of each other”

“We do partner with uh, Google X one of their business units called Bellwether, where we look at our wildfire risk, where we look at a one year and a five year view of how that wildfire risk could spread”

The hosts occasionally redirect productively - the wildfire/precision-underwriting angle is a good pivot - but most questions are leading and soft ('What is the ROI or operational efficiency you gain?'), there is zero pushback on vague answers, and the session was so poorly time-managed that the structured 'top three' segment was abandoned after one point.

“Maybe as a tangent to build on that. Um, but also, um, switching gears slightly”

“Well Parul, we can't let Andrew escape without talking uh, about AI and the impact on uh, Swiss uh, RE's uh risk data solutions”