The importance of data quality and consistency

by  Roi Agababa  |  10 Mar 2019

How data is recorded, stored and used has always been an issue that insurers have grappled with. Actionable insights derived from a company’s data play a key role in helping management teams make effective strategic decisions

In turn, it follows that if firms are deriving insights from inaccurate data, this information could lead to the wrong decisions being made. Learning to identify and eliminate poor quality data is therefore essential for insurers and agents alike.


Companies can only begin to eliminate poor data if they know how to identify it, however. Generally, it’s information that’s either incomplete or duplicated. When thinking about books of business, this could mean having records on file that are missing vital information or having two sets of information for the same client.  It’s inefficient for any business, but particularly in the data-heavy insurance industry.

Paying the penalty

In order to derive actionable insights and base strategic decisions on hard facts, companies need to have accurate data. Relying solely on revenue figures to drive decisions is not enough, as they simply don’t show the full picture.  Instead, firms need to turn their data into real-time insights that can help them make better, more strategic decisions that drive the business forwards – we call this data monetization.

By using the data at their disposal, agents are able to determine who the most profitable customers are, which lines of business are performing best, and what is the total income a customer brings in versus the cost of service. This quantification of time, resources and effort not only enables accurate profitability analysis but also helps to reduce operational costs.

In short, this model turns data into action for improved renewal rates and, more importantly, gives firms the ability to easily identify accounts in the red and convert them to green. Furthermore, by putting these insights into action, strategic decisions can be based on fact, as opposed to intuition, which is key to choosing the right path for the business.

By contrast, if the data on file is poor or incomplete, profitability analysis would be almost impossible, meaning that these opportunities are far more difficult to identify. Additionally, the increasing demand for on-demand service in today’s tech-rich world means that businesses also need quick access to reliable data in order to provide a superior customer experience.

Two-pronged approach

For all these reasons, the risks associated with poor-quality data are clear to see, so how can insurers handle this part of their business better? Technology and management both have a big part to play.

Part of the problem is that the insurance sector still depends heavily on legacy systems, which are often quite limited in terms of functionality.  Insurers, therefore, need to embrace technological change by adopting more sophisticated software and platforms. Doing so will allow firms to easily access their data and extract insights and meaningful MI that can help to drive efficiency.

Management’s role is to ensure that employees managing, analyzing and storing data in the best way possible, and also to encourage a culture that appreciates the value of data. After all, management has a responsibility to showcase the benefits of effective data management in order to deliver the best results for the business.

Years of aggregating data across siloed systems and manual processes have left insurance professionals with a deluge of data that they are struggling to turn into actionable insights, and more often than not the data they have is inaccurate. To overcome this, companies need to work on spotting inaccurate data and eliminating it. By creating a culture that understands the importance of data and investing in modern insurance management technology, firms can turn this on its head and ensure they create a customer-centric business that makes decisions based on accurate, actionable insights.

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