Published 18-11-2023
Keywords
- Insurance,
- Claim Management
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Abstract
Predictive analytics is concerned with the extraction of useful information from data to anticipate the future. The growing importance of 'data' in a plethora of activities, particularly in the decision-making milieu, is hypothetically grounded on the axiomatic adage that 'more data' leads to finer decisions. Sayings like 'data is the new oil' and 'in God we trust; all others must bring data' reflect the established philosophy of primarily relying on hard evidence to steer human endeavors in today’s digitally connected and data-centric world. Predominantly, the practice of insurance has increasingly inclined towards data, leading actuaries and financial analysts to scrutinize voluminous amounts of dynamic data variables like policy mapping, geographical location, socio-economic conditions, claim amount, customer profile, and patterns in worldwide losses arising out of varied perils. Insurance companies today are using predictive analytics techniques to better assess risks, recommend more suitable policy coverage, prevent fraud, and efficiently manage claims.
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