As insurance companies look to optimize performance, mitigate risk and meet rising consumer expectations, they still face a plethora of challenges when it comes to data and analytics. Companies continue to aggregate more and more data – but the manner in which they are doing so is not necessarily efficient. Some 40% to 50% of analysts spend their time wrangling the data, rather than finding meaningful insights.
To address these operational inefficiencies, TransUnion commissioned Aite Group to conduct a study of insurance and financial services professionals. The findings from this study outline how companies can stay competitive in the insurance industry while adapting to the evolving world of data and analytics.
Like most established financial institutions, insurance companies have multiple data repositories across the organization. Individual business units own their respective processes for capturing and managing data and, more often than not, manage at the product level rather than at the customer level. This often leads to inconsistencies, with no set definitions of key terms such as “customer.” As a result, information and insights are isolated to silos – by lines of business or by product – creating barriers toward seamless data integration.
To maintain a competitive edge, insurance companies recognize the need for new data sources. More than half of the study’s respondents plan to increase spending on most types of data sources, especially newer ones, such as mobile. However, as big data gets even bigger, it becomes increasingly difficult for analytics executives to find valuable insights. Addressing the challenges that arise from big data volumes requires an enterprise data management strategy as well as an investment in the proper analytics tools and platforms for processing and analyzing the data for meaningful insights.
The majority of these institutions are currently grappling with fractured data and legacy systems, which prevents these companies from extracting value and making the data actionable. 70% of those surveyed indicated that a single analytics platform, one that coordinates and connects internal and third-party systems, is a major differentiator. However, only about two in 10 respondents indicated that their current solutions have these capabilities.
This highlights the need for a coherent enterprise data and analytics strategy and a common platform to hold and integrate existing and new data sources, as well as analytical tools. The platform needs to be flexible to support different skill sets, react to changing market conditions and have the ability to integrate alternative sources of data.
See also: Why to Refocus on Data and Analytics
In addition to leveraging the right tools, sourcing the right talent remains a key challenge for executives. Nearly half (45%) of insurance professionals indicate that having the right talent greatly improves their ability to underwrite profitable policies. However, due to a lack of bandwidth, insurance companies often do not have the resources to allow their analytics teams to stretch their analytics creativity.
These operational challenges can result in a significant amount of time being dedicated to cleansing and prepping the data – preventing analytical teams from performing more valuable activities such as model development. The operational challenges create an obstacle for retaining talent as these sought-after data scientists are instead assigned to trivial work. 42% of the insurance professionals surveyed indicated that it is also challenging to find qualified data scientists in the first place.
As the use of descriptive, prescription and predictive analytics gains traction, it is imperative that executives recognize the challenges and explore solutions. By overcoming these barriers, the industry will be better prepared to embark on the next frontier of data and analytics.
For more information about the TransUnion/Aite Group study, please visit the “Drowning in Data: Thirsty for Insights” landing page.
