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Right now, insurers are scrambling to understand the lashing Hurricane Laura has reaped on their portfolios. For some carriers, it can be an all-data-hands-on-deck, 24/7 effort to continuously process the latest datasets from multiple providers (e.g. NOAA, KatRisk, Kinetic), and get them into formats that are useable. Operationalizing even one dataset can take up to four hours for insurers who choose to undertake the data processing themselves. Not only does this put a strain on key personnel, it can delay risk mitigation and claims response efforts, resulting in higher cost of claims.

If, however, those insurers were using Insurity’s SpatialKey Event Response solution, it would not take hours to process each dataset and intersect it with a current snapshot of their portfolio data. They would instantly and automatically understand which locations are in harm’s way, along with the relevant financial impact to their portfolios. No longer is it cost effective to undertake these types of operations in-house, especially as catastrophes increase in frequency and severity. You may have the data in-hand, but can you effectively make use of it? In this way, data and analytics go hand-in-hand. Data is nothing without context, and context is not possible without analytics.

Hurricane Laura

Shown above is a view of Kinetic’s surge extent forecast visualized within the SpatialKey Event Response solution for Hurricane Laura with severity bands, impacted locations, total insured value (TIV), and actual (gross) financial exposure. Other data currently available for this event includes flood, surge, and wind forecasts from KatRisk, NOAA, and Kinetic, as well as forthcoming NOAA aerial imagery.


Giving insurers data in the context that they need it is critical to decision making

Bringing together the best data assets in the marketplace to drive more insight at the point of decision is a key focus for us at Insurity. With the company’s acquisition of SpatialKey, it instantly gained 25 third-party data relationships, enabling not only out-of-the-box content, but purpose-built analytics to help insurers contextualize risk within the underwriting, portfolio management, and claims workflows. “Vendors are aware that data is a key component of the core system; being able to integrate with and pull in third-party data out of the box is part of this,” writes Jeff Goldberg of Novarica. The key statement here is “part of this.” Building out an ecosystem of on-demand third-party data is essential—and it’s something every core systems provider understands the value of. But it’s one thing to have data and it’s another to make that data useable—to be able to instantly provide context that drives insight.

Collectively, Insurity’s data analytics acquisitions have brought 50 third-party data assets to the table plus a $100 billion data consortium. That’s a lot of data for any underwriter, portfolio analyst, or claims professional to have at his/her fingertips. But perhaps more importantly, it’s all delivered through a cloud-based data analytics platform and natively integrated within the workflows where risk professionals need to make decisions; thus, giving them data in the context that they need to make more informed decisions.

Beyond catastrophe risk, another area where context is greatly needed is with COVID-19. We’ve brought our SpatialKey geospatial analytics platform together with our Valen Data Consortium to help insurers understand the impacts of COVID-19 on their businesses—from potential claims, to premium at risk, and even new business growth opportunities.


In the above screenshot, your attention is drawn to areas where an insurer may want to avoid marketing and growth activities while COVID-19 is still a concern. The areas in red represent areas where there is a high number of COVID confirmed cases and where an insurer has higher market penetration. These are just a few of the metrics that could be relevant when considering growth strategies amid the constraints of COVID. A host of other variables, such as industry, can also be taken into consideration based on an insurer’s business needs and objectives. Click here to read the full article on our blog.

The impacts of COVID-19 will create a race for premium in the months to come with pricing and underwriting excellence being the differentiating factors in winning market share. As McKinsey stated in a recent report, “Because pricing will be a primary differentiator for long-term value generation in P&C, it should be an integral part of every insurance carrier’s COVID-19 response strategy.” Our Valen predictive models can be deployed within weeks, helping insurers more effectively price risk in what’s sure to be a hyper-competitive market. Alongside pricing accuracy, our predictive analytics solutions create efficiency by accelerating an insurer’s ability to adopt straight-through processing (STP), helping them not only make better decisions at the point of quote but also monitor the performance of those decisions over time and adjust accordingly.

These are just a few of the relevant and timely solutions we’re working on as we continue building a data analytics platform that will help insurers make better decisions. The exciting possibilities of convolving all this data together with analytics that deliver richer insights to insurers is what drives us—and as we evolve with technologies like AI and machine learning, the possibilities are truly endless. We’re excited to streamline the delivery of insight as readily as we do data.


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