(Image credit: Dollar Photo Club.)
In terms of data volume and complexity, insurance easily wins the top spot among industries. Data is the lifeblood of the industry, making data integrity and quality (data IQ) critical to every insurer’s operation. Yet as insurance data continues to multiply, achieving a high data IQ today requires a different approach.
Too often the result of data movement is data leakage, inaccuracy, or inconsistency that is then proliferated throughout the enterprise, impacting everything from customer service, decision making, and regulatory compliance—all of which can affect the reputation of the organization. As insurance data volume rapidly increases, insurers need a data IQ approach that controls data in motion as it flows through the business process, along with enterprise end-to-end visibility to provide transparency into the health of the data.
Data issues aren’t new news for insurers and while they continue on their transformation and modernization efforts they are discovering that the data issues only become more complicated. Whether working with legacy systems, new modern core technologies, or a combination of the two, data integrity and quality challenges persist. Sure, modern systems can help insurers deliver new products to market faster, provide more efficient processing and enable a great user, customer, or agent experience, but if the data isn’t trustworthy even the best new core processing systems will fall short on delivering full value. Adding in the industry’s increased adoption of business intelligence and analytics tools raises the bar for higher Data IQ to improve the accuracy of analytical outcomes.
Waiting to improve Data IQ may lead to some tough lessons—for example, from auditors discovering poor data control oversight to compliance concerns, poor product decisions, lost customers, and missed opportunities. As insurers continue on the modernization and transformation journey, data integrity and quality through good data governance should be a top priority.
What can insurers do to ensure high Data IQ?
Insurers have tried a number of approaches to conquer data challenges. Some have taken the ‘homegrown’ approach by building point-to-point controls, siloed or departmental controls, spot data controls between systems or manual controls. Others have established data repositories or hubs in an attempt to centralize the data from disparate systems, minimize system-to-system data movement and provide a level of data consistency. While there has been some degree of Data IQ improvement with these approaches, they offer no standardization and visibility across the enterprise and too often miss data errors that are introduced early in the process. Those often cause problems down the road in the way of errors in customer communications, flawed risk decisions, and inaccurate financials—just to name a few of the possibilities.
The way to ensure the highest possible Data IQ is to employ an enterprise approach to data controls rather than a tactical one—end-to-end versus system-to-system.
Standardized and automated data controls stop bad data early when it’s less expensive to fix and before it can cause harm. Being able to track the data through all of the data hops between systems, both internal and external, will enable not just better data, but also improved operational reporting, visibility, and decision making. Automated data controls need to integrate with existing systems to continually verify, balance, reconcile and track data as the data moves throughout, as well as into and out, of the enterprise.
Data IQ Only Half the Battle
Achieving high Data IQ is only half the battle. Once integrity and quality goals have been met, insurers need to also maintain that level of data trustworthiness. Data control tools need to be easy to use and accessible by business users. Data fixes should not require IT developing custom code, but rather involve a business user being alerted when a data issue occurs and providing an user friendly interface and dashboard to resolve data problems before they have a chance to corrupt the process. Good data control tools should revolutionize how data is managed similar to what rules-engines did for core insurance system implementation and customization in the 90s. Unless both business and IT users are able to access and use the data control tools, the hard won high Data IQ will be short lived.
Insurers will always deal with some of the most complex and confusing data and compliance requirements, but end-to-end enterprise data integrity and quality controls can make business transformation, day-to-day business, and ongoing compliance less difficult. When you have data you can rely on, everything in insurance is better.