What can insurance companies do to exploit all their unstructured information?
Insurance companies collect huge volumes of text on a daily basis and through multiple channels (their agents, customer care centers, emails, social networks, web in general). The information collected includes policies, expert and health reports, claims and complaints, results of surveys, relevant interactions between customers and no-customers in social networks, etc. It is impossible to handle, classify, interpret or extract the essential information from all that material.
Most promising areas of text analytics in the Insurance Sector
The Insurance Industry is among the ones that most can benefit from the application of technologies for the intelligent analysis of free text (known as Text Analytics, Text Mining or Natural Language Processing).
It is estimated that in Europe insurance companies lose between 8,000 and 12,000 million euros per year due to fraudulent claims, with an increasing trend. Additionally, the industry estimates that between 5% and 10% of the compensations paid by the companies in the previous year were due to fraudulent reasons, which could not be detected due to the lack of predictive analytic tools. Moreover, efficient management of claims may also help to reduce operation cost
Text analytics techniques allow analyzing the text of insurance claims, settlement notes, etc. to prioritize their study by the company’s Research Unit. For example, common patterns are sometimes detected in claims from a multiple accident, which can be an indicator of organized fraud.
Analysis of the Voice of the Customer
When this type of analysis is applied to comments in open social networks, it is possible to detect trends in the sector, identify the brand perception (sentiment polarity but also which concepts, activities or entities we are associated with, and how we differentiate ourselves from competitors), qualify the corporate reputation of our company or brand, or provide early warning of possible reputational crises.
The analysis of complaints and claims is another natural area for the use of text mining. 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.
Subrogation in Property & Casualty Insurance
It is estimated that 5% of the cases in the P&C (Property and Casualty) area that should obey subrogation, do not. Text mining and data mining techniques allow to extract automatically subrogation indicators from the reports of the sinister, with a significant impact on the operating account.
Recommended products for the Insurance Industry
Among the text analytics technologies beneficial for the insurance sector, we can highlight:
Topics Extraction API
Complete semantic annotation of contents including entities (persons, organizations, concepts, themes…) , key concepts and relevant data (amounts, date and email).
Text Classification API
Build a classifier of your own with this powerful hibrid classification engine to match your workflow and route claims depending on theme, products or channel.
Corporate Reputation API
Analyze corporate reputation of your brand. Compare it with your main competitors. Detect in real time any menace for your corporate reputation from the analysis of social media content.
These are just some of the MeaningCloud products but there are more. Be sure to have a look our catalog.
Advantages of MeaningCloud for the Insurance Industry
MeaningCloud's products aimed at the Insurance Industry gather our expertise in projects for this industry and provide services for tagging, enriching and proofreading contents. These are some of their features:
Discover Relations Hidden in Text
Extract relations, e.g. “demand compensation for damages”
Classify in Categories
Classify text according to your own taxonomies or classification schemes (e.g. type of insurance: Auto, Health, Life, Casualty, Property, Liability, Credit, etc.)
Identify Key Words
Identify relevant concepts (e.g. negligence, injury, medical expenses, emergency room, car accident...)
Use your own dictionaries
Names of companies, trademarks, products, services, etc. can be added to system dictionaries for customization purposes.
Extract Key Data
Identification of monetary amounts. dates, temporal expressions, directions, URLs and e-mail addresses
Integrable with your CRM or CMS
Easy to integrate with your Customer Relationship Management solution or Content Management Systems