How NLP and AI are transforming the Insurance Industry
There are three cornerstones to success in the insurance industry: timely customer outreach, knowing your customers’ needs and being able to tell the difference between genuine and fraudulent claims.
To handle these three aspect effectively, insurance companies employ thousands of professionals - agents, brokers, marketing teams, support personnel, claim investigators, and utilize various technology systems. In this respect, the insurance industry is very much a people-centric one.
On the other hand, the insurance industry generates copious amounts of data, take, for example, the telematics services alone. Having so many channels that deliver data to serve one single purpose can result in a data chaos. This is the other side of the coin, which makes the insurance industry overly data-centric.
You might say that information is essential to any organisation, but with insurance companies, it literally forms the essence of them. Insurance manages risks and in it’s terms, accurate decisions (which are based on underwriting, regulation, upselling, cross selling, retention, distribution, and others) are down to the quality of information on which these decisions are made.
For the industry that is so people-centric and data-rich at the same time, utilizing smart data analytics can become a real remedy. Let us delve a little deeper into how NLP technology (Natural Language Processing) as field of AI can enhance enterprise analytics, connect people and data and thereby help insurance companies boost their performance.
NLP and text analysis open up new opportunities for the insurance industry, for example, personalized customer experience through the use of chatbots and virtual assistants, improved query response time and even fraud detection. Besides sentiment analysis of customers feedback in its turn can bring insights to brokers and insurers about their customers and prospective customers that will enable them to define their propositions in a much more sophisticated way than we have ever seen previously.
Another possible way of NLP application in insurance is the democratization of data access with the help of Natural Language Interface for databases, which can make dealing with data intuitive and powerful, thereby drastically enhance internal data analytics. In other words, it can provide everybodywith equal access to data needed to make decisions with no technical barriers to access or understanding.
Data democratization - Faster time to insights
The insurance industry generates vast amounts of data, particularly through aggregator and telematics services. This information represents a huge opportunity to gain insights into customers behavior. The ability to process, analyse, make decisions on this data has been relatively limited, but the recent growth of NLP technology means that self-service and real-time data analytics are now readily available.
How can this data democratization affect insurance businesses and it’s internal processes?
Having the right data at your fingertips is the dream of any employee and any business. Being able to just pull relevant data from your claims management systems directly into your back office system and interpret it without knowing a programming language has become possible with the help of intuitive, easy-to-use analytics. To get an instant answer a user needs to ask their internal database a simple question just like he would ask a fellow worker. An examples of such natural language query can be: "How many claims were paid last month?", or "What is the average claim payout in this quarter?”
Such intuitive data access via Natural Language Interface can:
- Equip brokers, insurers, claim processors underwriters and also C-suite with the information they need to inform all strategic and operational decisions faster
- Boost productivity of all decision-makers in insurance businesses and lower costs of analyzing and exploring data
- Increase adoption rate of Business Intelligence tools without additional training
This can be the key to data-driven, well-informed and successful decision-making, as well as a great time-saving solution. For example, a data-driven broker management platform can increase the ‘sales team - broker’ interaction tenfold, or equip relevant teams with the necessary insights at the right time to offer the best and most relevant product to a customer.
Underwriting and Claims Management
Undoubtedly instant access to a client’s data can drastically improve customer insights. And here a great deal of an insurance company's success is down to claim processors and underwriters. These have to deal with data coming from different sources, e.g. fraud lists and information from claims management database. The outcome depends on how well and how accurately the underwriter analyses all this information, so the accuracy of underwriters’ work is a critical factor in the success of the insurance company.
Democratized data access can increase underwriters’ speed and quality of work by enabling them to gain instant access and carry out a thorough analysis of data related to not only customer credit history, risks and market information, but also policy information, police reports, loss, and more.
Decisions need data and for an industry like insurance that is so data-driven and people-centered at the same time, allowing professionals have a quick and easy access to data is the key. In order for an insurance company to make informed and data-driven decisions, everyone in a business, from the sales team to the senior level, should have unrestricted and timely access to data.
With such next generation analytics NLP-interfaces like FriendlyData insurance businesses will be able to get the most out of company’s data and start delivering unique products, services and customer experience to your new and returning customers.