While teasing out predictors for non renewal of an insurance policy in Insurance sector we investigate for clues for Policy surrender from a subset of call centre transcripts (subsample of 90 day conversations where an outbound CSR records the key points of conversation regarding a policy holders reasons for not subscribing. Since the volume of conversations is in the thousands its difficult to manually These conversations can be fed thru the unstructured text mining process which can extract the top 10 themes. Example we can track the frequency of occurrence of certain “WATCH LIST” keywords where a sudden increase in keyword frequency/themes like ‘ POOR SERVICE ‘, “PREMIUM AMOUNT” can signal a subscribers intent to not renew the policy
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