Poor Data Infrastructure Inhibits Analytics

April 22, 2015 / by ReSource Pro Editorial Team

With the increased focus on analytics in all areas of the insurance industry, property-casualty insurers are facing serious challenges in achieving their analytics goals. Information technology leaders at large P&C insurers suffer with obsolete data infrastructure that inhibits analytics and adds an average of 25% to the cost of IT projects, according to a new Novarica/Informatics report.

Poor data infrastructure costs the industry more than $1 billion a year and insurers know they have a problem. On average, they rate their own master data management capability at just 2 out of a possible 5. Among the top problems the study points to:

  • Disparate legacy systems
  • Complex data infrastructure
  • Lack of maturity in master data management

As the industry tries to get up to speed, insurers have begun implementing programs, such as enterprise data warehousing, operational data stores, big-data technology, improved data governance and organizational changes. Allocations for data-related projects this year are projected at 13% of new-project spend.

Enterprise data improvements will support:

  1. Predictive analytics programs for underwriting and claims
  2. Straight-through processing
  3. Cross-selling and upselling
  4. Underwriting and service that is “account-aware”
  5. Enterprise risk management
  6. Customer profitability analysis

While underwriting and claims are the natural candidates for programs that exploit quality enterprise data infrastructure, distribution and marketing are growing as important users of data and systems.

To cope with the demand for forward movement in the data sphere, insurers are making organizational changes. Half of those in the study had either recently created a senior position overseeing enterprise data or rejuvenated existing data governance at their company.

Integrating data systems into the wider carrier business model rather than having it siloed as a separate unit is part of the data maturation process, the study suggests. Most chief information officers in the study indicated they expect their companies to grow increasingly reliant on analytics to handle both the burgeoning volume of data across consumer lines nationwide and security. Staff training on analytics and use of data in decision making at the leadership level are challenges insurers will face as they begin implementing enterprise data upgrades.

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