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Interesting side issue in article on increase in FIA complaints

Linda Koco reported on a Jack Marrion analysis of a 68% rise in Fixed Indexed Annuity complaints in 2014 on March 17, 2015 for InsuranceNewsNet. Mr. Marrion appears to believe that the 68% increase may not be reason for concern, for reasons explained in the piece.

However, I found an interesting issue somewhat buried in the story. Ms. Koco reports that Mr. Marrion used NAIC Aggregate Complaint data for his analysis “which showed 89 closed complaints involving FIAs in 2014 (and 57 in 2013). He extracted from the aggregate the complaints that were ‘miscoded’ (for instance, complaints against a carrier that has never sold FIAs). The resulting data refers to closed customer complaints of carriers that either currently offer or previously offered FIAs in 2013. Those carriers are associated with the 77 complaints for 2014.”

If Mr. Marrion’s “extraction” was correct, that means 13.5% of the aggregate complaints were miscoded. That seems to be a very high percentage to me. State insurance departments provide the complaint data and not all states report, so the data is only partially “aggregate” in that it does not reflect every state’s complaints closed. But that is not my issue here. My issue is that 13.5% of the reported complaints were miscoded. The NAIC says it “does not guarantee the truth, accuracy, quality or completeness of the data and is not responsible for errors, omissions or for results of further use.” It seems to me that the aggregation of the data is not very useful at all if it is only accurate 86.5% of the time.

We have worked with carriers on reviewing their internal coding for MCAS reporting and we know it is not easy to always code every complaint correctly and consistently. But this seems to be a very high error rate. We would certainly recommend training and revisions to procedures to a carrier if we found an error rate this high. This information is used to calculate company specific complaint ratios, which are then made available publicly. With such error rates, it may not present a very clear picture to consumers.