Powering Innovation Through Data Discovery: An Insurance Industry ‘Must’
Powering Innovation Through Data Discovery: An Insurance Industry ‘Must’
While most insurers are pursuing a combination of strategies to meet demand for a more seamless user experience, some are putting a particular emphasis on improving data utilization, particularly in the context of external data.

In the past few years, the insurance industry has come under tremendous pressure to innovate due to heightened customer demands for a more seamless user experience (e.g., mobile-first applications, consumption-based pricing, and accelerated claims) and the rise of new players (e.g., InsurTechs and MGAs) who are challenging incumbents by taking on new types of risks and delivering a high quality user experience. Take the example of Lemonade, which was one of the first InsurTechs to arrive on the scene with a design-centric interface and AI-driven underwriting processes. After acquiring customers in rental insurance, the company has gradually expanded to homeowners, car, pet, and life insurance policies.

In response to these challenges, insurers are developing world class innovation teams, expanding their data science and technology capabilities, and partnering with purpose-built MGAs to “test the waters” in a more limited scope. While most insurers are pursuing a combination of these strategies, insurers are putting a particular emphasis on improving data utilization, particularly in the context of external data.

Growth in External Data as a Key Driver

In the last decade, the market for external data has grown tremendously with large bureaus such as Experian, Equifax, and CoreLogic offering more data products than ever before and hundreds of new data vendors emerging on the scene. Insurers were already consuming vast amounts of external data to run risk decisioning functions, but now they are now inundated with thousands more products to choose from across many more data types.

Consider the following examples. Aerial imagery data can provide more accurate property details than tax assessor data, while also automating certain claims around roof damage. Footfall data can be used to verify the hours a business is open, and whether or not the property is regularly hosting large events or gatherings outside of normal business hours, suggesting the presence of additional risks. And digital intent data can provide clues about customer satisfaction, thereby helping insurers reduce churn through preventative methods.

The greater availability of external data is also valuable in improving data quality. According to a Corinium report on the Future of Insurance Data, only 41% of insurance executives were “fairly confident“ in their data. External data on people, businesses, and properties can be used to verify customer information at the point of application or on a regular basis. Key customer onboarding use cases such as marketing and prefill also benefit substantially from greater availability of external data.

Unlocking Innovation with Data Discovery Tools

 As insurers innovate across the new data landscape, they are faced with a series of challenges. First, not all data vendors are equal and careful attention must be paid to data quality, collection methodologies and usage restrictions. Second, onboarding each data vendor for testing can take months to even a year depending on whether customer data must be enriched for an accurate data test. Third, with so much new data, enterprises need tools to help them “sift through the noise.”

In this context, an External Data Platform (EDP) is a valuable tool to accelerate data discovery processes. EDPs provide the following data discovery features: rapid access (via API or Data Share) to a curated collection of external data products from hundreds of different upstream providers, data dictionaries, and due diligence certifications focused on usage restrictions and collection methodologies. When it comes to testing, EDPs also structure data in ways to feed into automated machine learning platforms that can test thousands of attributes and hundreds of model variations to identify the most predictive attributes across a sea of data sources. Indeed, EDPs save insurers a significant amount of time as they address the challenges of identifying and accessing new external data products.

Moving Beyond Data Discovery to Deployment

 While data discovery tools are absolutely critical to expand the aperture of what’s possible with external data, it’s also critical for insurers to be able to deploy new external data solutions rapidly. A common problem among many industries, not just insurers, is “getting stuck in the lab” and never actually deploying the innovative solutions that have been identified. Frequently, this occurs because of prolonged procurement and information technology processes.

EDPs can be helpful here as well, as they can provide access to production-grade data via APIs or full files delivered to in-house data lakes. Moreover, they provide the ability to procure external data from multiple vendors simultaneously via a single API. Thus, it can be said that these platforms provide access to hundreds of sources, via a single API and a single contract.

Changing customer expectations, an evolving risk landscape, and the emergence of InsurTechs—are forcing insurers to be more nimble. They must adapt and apply new tools to address these demands through more rapid solution deployment in order to retain their competitiveness. An external data platform can help enterprises accelerate data discovery and data deployment as they seek to provide their customers with world-class user experiences.

Source: Insurance Innovation Reporter

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