Insights

How Much Could Your Data Errors Be Costing You?

Written by Certus Solutions | Feb 14, 2016 8:30:00 PM

In 2015 it was revealed that some of Britain’s biggest insurance firms had been shortchanging retirement fund customers because of miscalculations, human error and computer-related system issues.

One firm was exposed for underpaying more than 6,000 customers with retirement funds due to what it called “processing errors” by staff.

Unfortunately, these simple errors are nothing new, especially when people’s retirement livelihood is at stake, and the repercussions can be huge and incredibly costly for organisations.

A data blunder at Aegon, a well-known superannuation, life insurance and asset management firm, resulted in £60m (NZ$131m) of underpayments over a number of years. Aegon was subsequently fined £2.8m (NZ$6.1m) by the Financial Conduct Authority and ordered to pay that £60m (NZ$131m) sum to customers who had been shortchanged.

With such large member bases, super funds must ensure the substantial amount of information on each customer is correct to enable them to make the correct payments, tailor the right financial options and meet auditability and regulatory compliance.

Unsurprisingly, those high-profile examples of basic data errors causing substantial financial and reputational damage have spurred super funds to implement data cleansing activities across their organisation.

However, the deficiency with these actions is that there is often no overarching framework keeping track of the activities, which can lead a to duplication of effort, inefficiencies in process and a lack of clarity on what the objectives are for data quality.

With the help of Certus and our Data Quality Framework (DQF), super funds in the region have been able to implement a data quality monitoring platform where critical issues are highly visible, clearly costed and explicitly owned – enabling the super fund to address high-impact data quality issues rapidly.

Using DQF, common queries can be identified as rules and these rules can automatically track down data quality issues that need to be fixed.

Watch our DQF solution video to find out how we can help you identify and fix any potentially serious data errors and better serve your customers.