The insurance industry uses data analytics to support its critical business decisions –i.e. whether to provide an organization coverage, what types of coverage to underwrite, and what level of premiums to set. All of this data has an enormous impact on the financial forecast for the profit and loss statement of an insurance organization. Good data is arguably one of the most valuable assets.
But can you trust your organization’s data? Is it accurate, consistent, a large enough data set to be relevant, and is it refreshed on a frequent basis? The concept of data governance was born to help organizations tackle this very issue. If you don’t focus on data governance you may be putting your organization at risk by going after unprofitable or risky lines of business in the wrong industry verticals, setting premiums too low or too high, producing inaccurate financial forecasts, or missing out on opportunities to use new data points for future decision making.
Data governance is defined as a control that ensures data entry (by an operations team member or by an automated process), meets precise standards (such as a business rule or a data definition), and applies data integrity constraints. That’s a tall order for insurance entities that handle marketing, policy, claim, and financial data via multiple proprietary internal and external systems. To further complicate the integration, these systems may or may not document best practices. Past decisions and data dependencies of data may not be known. Programming language may be difficult to interpret. Add to that a lean-and-mean workforce and whew….you need someone to govern this process or you may end up basing your business decisions on questionable data.
Simply put, strong insurance organizations have valued data governance teams. They rely heavily on the data because they are defining best practices across all of these systems. They feel confident. Every field, every business rule, every workflow/integration point has a documented definition and behavior. This includes the systems that were created 10 years ago by a programmer who has since retired or moved on in their career. This also impresses upon the importance of selecting good third party vendors who understand the importance of data governance when integrating with your organization and downstream systems.
Data governance teams are the unsung heroes who hold the keys to success in their insurance organizations.