Text Analytics in Insurance
Raghuram Anumula
20MBMB17
Text Analytics in Insurance
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The Insurance Industry can benefit from the application of technologies for the intelligent
analysis of free text (known as Text Analytics, Text Mining or Natural Language Processing).
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Insurance companies have to cope with the challenge of combining the results of the analysis of
these textual contents with structured data (stored in conventional databases) to improve
decision-making.
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In this sense, industry analysts consider essential the use of multiple technologies based on
Artificial Intelligence (intelligent systems), Machine Learning (data mining) and Natural
Language Processing .
Text Analytics in Insurance
Use-Case I: Fraud Detection
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Text analytics techniques allow analyzing the text of insurance claims, settlement notes, etc. to
prioritize their study by the insurance company’s research unit.
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For example, common patterns are sometimes detected in claims from multiple accidents,
which can be an indicator of organized fraud.
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Quick decision making, using the appropriate indicators (KPI, Key Performance Indicators),
helps to prevent fraud and increase the benefits.In this sense, text analytics, at times through
dashboards, provide vital information to make quickly well-justified decisions.
Text Analytics in Insurance
Use-Case II: Analysis of the Voice of the Customer
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Text analytics permits to classify interactions according to the products or services offered, the
marketing channels used, the operations employed, so and so forth.
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In addition, automatic opinion and sentiment analysis techniques help identify the polarity
(positive, negative or neutral sentiment) about issues or specific aspects of a product, channel
or procedure.
Text Analytics in Insurance
Use-Case III: Claims Management
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The analysis of complaints and claims is another natural area where text mining can be
applied to gain the relevant insights.
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Regardless of the inbound channel, complaints can be classified automatically according
to the insurer’s products, services or operations, as well as their gravity, in order to direct
them to the appropriate agents so that they receive in each case the appropriate
treatment.
Text Analytics in Insurance
Text Analytics Technologies beneficial for the insurance sector
1. Topics Extraction API: Extract the most relevant information
2. Text Classification API: Organize automatically into categories all types of content
3. Corporate Reputation API: Include in corporate reputation analysis the impact of social
comments and all kinds of media
Text Analytics in Insurance
Text analytics techniques in the Insurance Industry
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Sentiment analysis
Automatic classification
Entity Recognition or Extraction
Detection of semantic relation patterns
Development and application of specialized ontologies (or taxonomies) in the insurance domain
Content crawling on the Internet
Analysis of the Voice of the Customer
Analysis of the User Experience
Thank You