Insurers collect a wealth of data, but only a few have found ways to harness its true potential. Most insurance business and technology leaders have very low confidence in their data assets’ ability to meet customer and competitive demands.

Almost all incumbent insurance companies support disparate lines of business and individual parts of the value chain through a plethora of legacy systems and disjointed data silos. For example, policy administration systems have different data stores and differing data formats from claims management systems, making it impossible to match risk with loss data. Add the complexity of siloed data representing each line of business, and you have entangled chaos for data environments.

AI technologies are advancing at breakneck speed and the use cases for AI in insurance are immense, but only high-quality data can adequately serve as training data for these AI use cases. Feeding bad data to AI engines dramatically increases the chances of bad outcomes. Carriers need improved data postures if they want to scale AI and see some real gains from the transformative technology.

The consequences of poor data posture in today’s operating environment are far-reaching. Poor data adds risk to almost all parts of the insurance value chain and can significantly challenge several business and technology areas:

      1. Underwriting performance
      2. Attracting the right distribution partners
      3. Product innovation
      4. Claims experience
      5. Seizing the power of AI

Historically, the plight of mediocre data posture hasn’t been as dire. But with growing competition, increasing expense pressures, a greater push for digitization, demand for product innovation, and consumer expectations of seamless digital experiences, strong data postures are a prerequisite for strong operating performance.

The insurance industry’s evolving needs require insurers to get their data houses in order with urgency. Data readiness requires a comprehensive and systematic approach. Insurers that do not get their data in order will be left with an adversely selected pool of risks that could affect operating performance. Digital leaders need to consider a range of impactful internal and external solutions to this data conundrum to drive innovation, be competitive, and meet the evolving needs of their business.

Our new report, Insurance Industry Survival Relies On Data Sophistication, explores this topic and provides practical approaches to data readiness. Clients interested in discussing this report and increasing their data sophistication can connect with me via an inquiry or a guidance session.