Text Analytics in Insurance Raghuram Anumula 20MBMB17 Text Analytics in Insurance ● 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). ● 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. ● 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 ● Text analytics techniques allow analyzing the text of insurance claims, settlement notes, etc. to prioritize their study by the insurance company’s research unit. ● For example, common patterns are sometimes detected in claims from multiple accidents, which can be an indicator of organized fraud. ● 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 ● Text analytics permits to classify interactions according to the products or services offered, the marketing channels used, the operations employed, so and so forth. ● 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 ● The analysis of complaints and claims is another natural area where text mining can be applied to gain the relevant insights. ● 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 ● ● ● ● ● ● ● ● 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