The Insurance Data Paradox: Why structure creates flexibility

At the largest and oldest insurance companies, data can be extremely disorganized. Innovating on this disorganized foundation is extremely difficult, but urgently necessary.

In an editorial in Carrier Management, Federato cofounder and CTO William Steenbergen explains how a balanced, opinionated data model developed specifically for insurance by a technical partner who understands the industry and its data patterns can provide a shortcut to innovation and differentiation.

Many carriers have five or more policy admin systems due to acquisitions. Critical data is often stored in legacy mainframe databases without an API, and may only be accessible via a database string. The schemas of core datasets use column names like 'field A', 'field B' and 'field C' rather than easy to understand column names.

There are two paths out of this chaos; building a custom data architecture entirely from scratch, or building on top of an established data model provided by a technical partner.

A data model provides an architectural template in the form of software built over years of testing across customers, lines of business and markets. It will include integrations to common databases, ETL functions to standardize and align data from disparate sources, and suggested rules to ensure the right teams and individuals can securely access relevant data when and how they need it. It should also include functionality to capture usage patterns in preparation for AI applications.

Read the Full Article

Read the full article at Carrier Management here.