Insurance company have to imbibe a culture where business leaders trust Data Analytics and act on the insights provided to get maximum value from the potential value of Big Data. Insurers should take steps to create that culture today if it doesn’t already exist in their companies.
The key is to start small with a PoC. Following is an example of how insurers can leverage a Big Data platform and some key considerations to keep in mind. In this example, IT is interested in using a Big Data environment to speed up long-running ETL processes in a traditional data warehouse environment, because the traditional processing is leading them to miss reporting SLAs for business.
Big Data Challenges: Insurers are faced with a number of factors that combine to make Big Data a big challenge:
The key is to start small with a PoC. Following is an example of how insurers can leverage a Big Data platform and some key considerations to keep in mind. In this example, IT is interested in using a Big Data environment to speed up long-running ETL processes in a traditional data warehouse environment, because the traditional processing is leading them to miss reporting SLAs for business.
Big Data Challenges: Insurers are faced with a number of factors that combine to make Big Data a big challenge:
- Proliferation of channels and the explosion of data
- Increasingly competitive landscape, especially in the P&C and life sectors
- The financial tsunami of the past several years, as well as the resulting increasingly demanding regulatory requirements in both North America and Europe
- An unusually high number of catastrophic losses caused by natural disasters like brush fires, hurricanes, earthquakes in recent years;
- Siloed data environments.
Having said that, it is important for insurers to develop a good business use case for meeting the strategic objectives of that line of
business. In addition, solid backing from top level executive is extremely important not only for funding, but
to evangelize and communicate the objectives and need for adoption of Big Data to the entire organization,
including partners and vendors. Although the scope and investment in terms of people (a dozen employee big data team), tools (for example, open source Hadoop ecosystem), technologies and infrastructure might be small, the architecture should keep the long term view in mind.
For the effective harnessing and harvesting of Big Data, close collaboration between IT and business is imperative
to iteratively experiment and drive actionable insights by building proof of concepts. Insurers can then use this incremental success to get
increased funding for next phases and/or use cases.
Insurers who aren’t exploring and embracing Big Data, and developing a Big Data strategy will find that they are
losing their competitive advantage. They will be unable to get actionable
insights from the mountains of data flooding into their organizations. Some of the key findings of the market research with
respect to Big Data adoption and opportunity in Insurance vertical were:
- A vast majority of insurers are using analytics for actuarial & pricing processes. Very few insurers are using analytics to improve operational areas like sales, marketing or optimized work assignment for underwriters & claims adjusters.
- Relatively few insurers have got a comprehensive Big Data strategy and are reaping its benefits However most insurers are planning their Big Data approach.
- Even fewer insurers capture, persist, and analyze Big Data within their computing environment today, but those that do typically leverage traditional computing, storage, database and analytics, in addition to newer platforms such as the Hadoop ecosystem.
- Larger insurance players plan to embrace Big Data and analytics across all financial and risk management areas while less than 50% of the smaller insurers are planning the same actions.
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