Insurance Data Analytics for Better Decision Making

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Insurance Data Analytics for Better Decision
Making
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• Introduction
• Insurance Data Analytics Improving
  Decision-making
• Managing Claims
• Calculating Risk
• Leveraging Customer Insights
• Balancing Customer Acquisition and Profits
• Conclusion

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Table of Contents
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Introduction
Data is a gold mine for insurers to make capable
decisions in the competitive industry. Insurance
Data Analytics improves decision-making in
crucial tasks like underwriting, premium
calculation, and risk prediction. With the
availability of Big Data, insurers need to
leverage the right data into relevant insights.
The solution for managing such a large volume of
data and benefitting from it is Insurance
Technology therefore, insurers are increasingly
considering partnerships with insurtech companies.
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How?
Insurance Data Analytics is improving
decision-making for insurers.
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Data Analytics Improving Decision-making
Managing Claims
Calculating Risk
Balancing Customer Acquisition and Profits
Leveraging Customer Insights
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Managing Claims

• With the use of insurtech in predictive analysis,
  frauds have been minimized to a remarkable low
  enhancing accuracy of insurance data analytics.
• Identification of the applicants who are likely
  to commit fraud is easier for insurers by
  insurance technology and hence, claims auditing
  decisions would be more accurate.

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Calculating Risk

• Insurance data analytics works as a primary base
  for any policy-making by underwriters.
• Data like one persons address, area of
  residence, distance from a fire station, and even
  unstructured data of a persons social media is
  crucial for insurance software to guide
  analytical decision making.

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Leveraging Customer Insights

• Morgan Stanley and BCG global customer survey
  reveal Insurance customers are in favor of
  digitalizing their insurance experience
  completely.
• This can be possible by rightly predicting
  customer behavior with the acquisition of
  relevant data to suggest a customized insurance
  policy for customers as required.

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Balancing Customer Acquisition and Profits

• To enhance customer acquisition, insurers need to
  reduce cost but it will also reduce their
  profits. Therefore, with Insurance data
  analytics, insurers manage customer acquisition
  and profits hand in hand.
• This is done by insurance technology solutions
  for running insurance processes with the wise
  help of analytical decision making.

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Conclusion
Insurance data analytics empowers the insurance
carriers to conduct an efficient analysis of data
available and come out with the best possible
decisions for every insurance task and process.
With the rising competition in the field,
insurers trust insurance technology to guide
their analytical decisions to not leave any scope
for human error.
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