Why is up-front data profiling important?
Example #1:
This is a real life example of an issue that was detected when profiling a legacy mainframe system. One policy was found to have an insured with a gender code of “C”, a company. We would open a TIM item to record this as no life policy can have a company as the insured.
We want to detect such anomalies early, as the gender code would need to be corrected and also to investigate the accuracy of premiums due to this error.
Example #2:
This is another real life example of an issue that was detected when profiling a legacy mainframe system. Two policies were found to have a premium discount percentage. This was a term life block of business and discounts were not allowed.
We want to detect such anomalies early, as the premium discount percentage affected premium calculation. Clicking on number “2” initiates Onward’s drill-down process. It will retrieve the two underlying records and send output to Excel. See results below.
Drilling down shows that policies pol#555a and 000000000001207 have discounts applied, 2.5% and 5%, respectively.
A TIM item would be opened to raise this issue and have it investigated.
