3 ways open ecosystems help P&C insurers thrive

Insurers are awash in data but only benefit from it with improved access and analytics.

In this digital insurance era, organizations should no longer be constrained in their access to data and analytics. (Shutterstock)

The value of third-party data is clearly understood in the P&C industry. From hazard data to property data, IoT, and more, insurers are awash in data.

As the sea of data assets expands, insurers must assess their ability to access data quickly and efficiently to drive immediate insights. But access is not enough. Data itself is sorely lacking without context — without the ability to use analytics to uncover the hidden value within. Workflows can be cumbersome and inefficient, with risk professionals often accessing multiple disparate systems to make informed decisions. Likewise, certain software and data can be proprietary — limiting the flexibility in how data can be used and visualized to drive insights. This delays decisioning and leads to potentially missed opportunities and extraneous costs.

The good news is that the industry is well-aware of these operational constraints — and is thirsty for change. As noted in Insurity’s Valen Analytics Outlook report released earlier this year, we’ve observed a shift in the industry. Insurers are more readily embracing the idea of working with partners as a means to solve the challenge of maintaining connections to multiple data providers and as a means to test and scale new products. Connecting to partners through software solutions and/or API technology also takes the load off of in-house IT, freeing up resources for other initiatives.

Purposefully building out partner connections through APIs and digital solutions enables insurers to streamline operations, reduce costs, and develop customized products with more agility than ever before. However, when building their networks, insurers must look to partners that enable “open ecosystems” — meaning partners that do not put limitations on access to data, analytics, or software. Insurers should have the flexibility to incorporate inputs in any way that helps them meet their business objectives. Put simply, open ecosystems enable choice. Choice in data providers that can collectively drive better and faster decisions, and the choice in technology partners that best aligns with an insurer’s claims experience, product lines, practices, and view of risk.

Here are three key ways open ecosystems can help P&C insurers thrive with improved access to data and analytics:

No. 1: Improving catastrophe risk management and strategy

Hazards such as floods, wildfires, and hurricanes can be one of the leading claims expenses on an insurer’s book of business. In fact, since 1989, nearly 20% of the global insured losses from natural catastrophe events occurred in the years 2017 and 2018 — the highest ever for a two-year period at $219 billion — with a large percentage of those losses in North America.

That’s staggering to think about. It also underscores the need for insurers to implement effective and proactive catastrophe management solutions.

Data plays a pivotal role in hazard analysis. But, while data choice is abundant, insurers may still be hopping between platforms to access and visualize hazard data and models in the context of their exposure data. A key reason for this is the proprietary nature of some trusted industry catastrophe modeling companies that don’t support the industry call for more open ecosystems. They can drive inefficiencies by limiting where and how data can be visualized. This leads to the necessity of piecing together multiple disparate solutions to fully understand risk. Without the ability to quickly and efficiently calibrate views of risk, insurers can be left with more questions than answers.

Insurers should have the flexibility to pick and choose the data they need — whether to underwrite risk or respond to catastrophes — and seamlessly integrate this data into critical workflows, making it instantly actionable. While access to a variety of trusted hazard and event data is paramount, so too are the analytic tools to derive meaningful insights from that data. Case in point, we’re now in the throes of an above-average hurricane season and insurers must rely on catastrophe event data and analytics to fill the gap as social distancing limits insurers’ abilities to get boots on the ground and people in the field to respond to claims. The ability to incorporate “ground truth” data such as aerial imagery, public event footprints (e.g. NOAA, FEMA), or the latest event footprints from providers like KatRisk, JBA Risk Management, Kinetic Analysis Corp, and Impact Forecasting will be critical to helping insurers quickly quantify their potential exposure and formulate their claims response and investigative efforts.

No. 2: Accelerating business growth in new areas

At one point in time, leveraging predictive models for underwriting made the difference between the carriers that would succeed and those that would be more susceptible to adverse selection. Most P&C insurance carriers now leverage predictive models to more quickly and accurately assess risk and inform pricing. However, not all predictive models are created equally and are only as effective as the data used to build them. Models based solely on an insurer’s internal data will not be as effective as models enriched by a contributory data consortium. And even then, there are many different types of data consortia available, but only those with aggregated transactional and behavioral data — such as risk profiles, attributes, and claims histories — combined with third-party data will be able to deliver superior predictive power.

With access to more diverse data sets, carriers can begin to write business in new regions where they don’t have historical data. For example, if a workers’ compensation insurance carrier typically writes business in Oklahoma and wants to expand into Tennessee, using a predictive model built with transactional data from a data consortium that includes past regional policies and claims, along with geographic data from third parties, will help the insurer build its portfolio.

No. 3: Standardizing niche specialty business

Niche specialty lines of business are poised to become some of the strongest growth areas for insurers in a shared ecosystem. This market segment has always been attractive for insurers that want to add high-margin business while reaching mid-market and small business customers but is notoriously hard to scale. This is because most niche specialty insurance products typically require field specialists and lengthy questionnaires to properly underwrite risk. Leveraging targeted third-party data can reduce the need for specialist visits and standardize the onboarding of new customers, thereby improving scale and creating a truly profitable product.

As an example, professional liability insurance for lawyers would traditionally take a significant amount of research on law firms across the U.S. to assess each individual policy, including case records, win rates, judges, and many other factors. Utilizing third-party data sets that contain this information can help develop predictive models to score specialty products and help automate the process, enabling consistent decisions at a faster rate.

These are just a few examples of the positive impact more open access to data and analytics has on the future growth of insurance carriers. In this digital insurance era, organizations should no longer be constrained in their access to data and analytics. Rather, they must engage with partners who foster open ecosystems, enabling them to strategically achieve their business objectives and also more easily pivot when best-laid plans are thrown curve balls.

Kirstin Marr (Kirstin.Marr@insurity.com) is head of data solutions at Insurity, where she leads development and operations for the company’s portfolio of data and analytics solutions. These opinions are the author’s own.

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