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Persistency Prediction and Improvement

Predictable Persistency Estimation

Persistency also known as customer retention, is critical to a life insurers business as it drives revenue and asset liability calculations. It is also a direct reflection of the overall loyalty and customer experience with the brand.

Challenges in Persistency

Globally, insurers lose 18-20% of their customers annually. Life insurance companies have taken various initiatives to improve persistency rates, but the problem remains deep-rooted with no quick fix solution. It is a complex issue dictated by a combination of factors. Some of these include the macroeconomic environment, product parameters, demographics, payments, etc. Unfortunately there are no best practices documented for persistency control.

Data Analytics to Boost Persistency

The key to effectively arrest lapsation lies in leveraging the knowledge that is already available regarding the customer base. However, the key disconnect occurs in using the underlying information optimally and in real time. Data analytics, specifically that which incorporates both structured and unstructured data and combines customer and distribution level interaction has the potential to impact persistency.

Persistency Modelling with CRUX

We understand that the persistency approach has to be consistently refined and fine tuned to reflect not only the macro factors but also organizational strategy and tactics.
CRUX lets us do that and more by building comprehensive persistency control and management framework which works at the point of decision. It empowers the insurer to predict and manage the development of persistency across product lines. CRUX uses internal, external, structured, unstructured data sets to power these predictions and insights. These insights can further power other functions like customer service, collections, claims & marketing, etc.


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