The long-term benefits of the data fabric will be very high, as it will automate many repetitive tasks in data integration, quality and data delivery, thus providing an economical path to greater speed and scale. More complex tasks — such as cataloging metadata, delivering integrated views of data, and even automating complex data modeling tasks in unstructured content through semantic knowledge graphs — will also be automated by the data fabric. Over time, the data fabric will add semantic knowledge for context and meaning, as well as provide enriched data models. Ultimately, the data fabric evolves into a self-learning model that recognizes similar data content, regardless of form and structure, enabling automated broader connectivity to new assets. Thus, the data fabric is transformational compared to current data landscapes, which are siloed, inconsistent, hard to query, impossible to cross-validate and, ultimately, cannot deliver fast access to data in a scalable manner. Insurers can potentially leverage data fabric in order to combine risk and pricing data to improve the accuracy of decision making in underwriting. Data fabric can also be used to unlock new insights in combating fraud, for example, by joining up claims and underwriting data silos to prevent a previously identified claims fraudster from applying for a policy in the future. Ongoing regulatory compliance and evolution of reporting structures, such as Solvency II, will also benefit from the ability to compose data flows.
Recommended Actions:
Take first steps toward the data fabric by building augmented data catalogs that become a single repository of metadata to find, tag, annotate and understand an organization’s data sources, including distributed data assets. Include an insurance- specific set of objects and data dictionary. ■ Stimulate the demand by communicating the business benefits of the data fabric so business users drive the need with IT departments, where investment in current approaches and, consequently, resistance to data fabrics could be highest. ■ Start by demonstrating the value that data fabric brings in optimizing existing insurance processes in underwriting, claims and actuarial functions, before expanding relationships with insurers to more transformational data fabric use cases, such as personalization and dynamic pricing. ■
Recommended Reading:
Emerging Technologies: Critical Insights on Data Fabric ■
Gartner, Inc. | G00786204
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