- Published on March 4, 2022
- In AI Features
Council Post: Driving effective digitisation in underwriting space with AI, NLP and analytics
As AI and NLP enable digitisation, the power of analytics boosts the effectiveness of extracted content by leveraging predictive modelling.
Image by Council Post: Driving effective digitisation in underwriting space with AI, NLP and analytics
- By Saurabh Khanna
Insurance is all about managing risk, but with AI it only gets better. Let's take the example of an oil and gas company. It produces terabytes of operational data daily– both structured and unstructured. Here, insurance companies can connect the data to predictive analytics systems to anticipate levels of degradation, perform automatic defect inspections, predict potential failure rates, operational risks, etc.
(Source: NVIDIA)
In another example, one of the insurance companies developed an AI/ machine learning algorithm for predicting the likelihood of flooding in the area using historical and geospatial data and inputs from digitised documents. This allowed the company to model a potential market with 83 percent accuracy, reduce throughput time in underwriting by 10x, a
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Saurabh Khanna
Saurabh is a Data science consultant with sound delivery & sales experience in Artificial Intelligence. Throughout his professional journey, Saurabh has established large teams from scratch and delivered benefits by endorsing AI, Analytics, or Lean Six Sigma solutions. Currently, he leads the Digital team at EXL.
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