Using NLP: A Modernized Claims Processing Solution For Insurance

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Claims processing has always been one of the most difficult and important areas of insurance.

In this article, we’ll outline the current trends in claims processing in insurance. Some of the modern technologies are likely to become integral components of claim processing in the nearest future. And the companies that start using them among the first will reap the most benefits and gain a competitive advantage over those who still use outdated workflows and routines.

PROBLEMS IN THE INDUSTRY

As we see it, most insurance brokerages operate in a very similar way. Their claims processing workflows have the following traces:

1. CUSTOMER SERVICE IS FAR FROM BEING PERFECT

Claims processing quite often turns out to be a headache for insurance customers. Clients transferred from one agent to another happens occasionally.

2. REPORTING PROBLEMS

When an accident happens, the first thing to do is calling the insurer. Some claims can be made over the phone, but most often the insurer would send a form to fill out.

In both cases, there is a high risk of providing incorrect information. People may not remember their medical codes, they can misinterpret and misspell.

Filing an incorrect claim can not only put the insured in jeopardy of being denied compensation but could result in far greater trouble such as lawsuits for insurance claim fraud.

The filed claim must contain complete, accurate, and up-to-date information.

Insurance agents then spend their time examining and correcting the misspellings, wrong information, re-ask the person, and checking the claim again. And even if a claim is filled in the correct way, an agent must review and formalize that information.

And agents deal with lots of papers, not just one claim.

People may go in circles, wasting their time and nerves.

We wouldn’t say that the solution is to eliminate human contact. It plays an instrumental role in building trust with a client. For this reason, the contact should be positive for both sides, not repulsive.

3. CUMBERSOME INTERFACES

Websites and applications used by insurance companies to provide remote services are often too overflown with excessive features, which makes the newcomers perplexed and disappointed.

Even though interfaces may look pretty modern, the existing feature overload distracts rather than helps. A user gets confused by the menus, submenus, checkboxes, and other elements. And often there are insurance terms all around, which is a different language for a non-related person.

As a result, such sites and apps fail to fulfill their intended use of providing self-service and alleviating customer service departments. The great opportunity is lost.

A user has nothing else to do than to turn to a customer service representative.

4. WORKING WITH LITTLE DIGITAL SUPPORT

As a rule, claims adjusters work with little digital support. The commonly used software is MS Office Word, Excel, and a simple CRM with no integration between emails or IP telephony. It takes quite a lot of time to enter client information into a table and later to a CRM.

It is surprising that in this modern times, the claim processing procedure hasn’t changed much. There is a great opportunity for automation, which is unfairly not used.

WHAT DO THE INSURERS DO ABOUT THE SITUATION?

Insurtech firms have already made their first step towards next-generation insurance. Some of them have introduced virtual assistants and AI-based bots into their work.

Their results are quite impressive.

One example is the ability of the insurer to insure a client in just 90 seconds.

Usually, all client information is validated by humans. But it would be more efficient if the data is initially processed by an algorithm. More and more companies prefer the software to process data instead of the personnel because the probability of mistakes made by machine is much lower. The only thing your personnel would do is approve of the results.

And that was just one example. The future of insurance will be shaped by intelligent text and speech recognition tools, data processing algorithms.

It’s high time the companies have a serious look at modern technologies while deciding upon their future strategy. The main of them are Natural Language Processing (NLP), Machine Learning algorithms, and Artificial Intelligence.

REAL-TIME NATURAL LANGUAGE PROCESSING FOR CLAIMS PROCESSING

Natural language processing (NLP) is the area of Artificial Intelligence aimed at empowering computers to recognize human speech. As recognizing human speech is a cognitive function, NLP is considered to be one direction of Artificial Intelligence.

The underlying principle of the technology

The underlying principle of the technology is that an NLP-module finds the relations between human language (input) and the sample data (its “database”).

NLP is implemented in Google Assistant, Amazon Alexa, Apple Siri, and Microsoft Cortana. Basically, they record a voice message, compress it, and send it to the server. At the server-side, that message is uncompressed and analyzed by Machine Learning algorithms. As a result, the system understands the user request and sends back the feedback. The whole process is quick.

Note, that there are two types of NLP: traditional and real-time. Real-time NLP is slightly different from traditional NLP in that it’s faster and extremely close to real-time.

How can NLP optimize claims processing?

For Phone Calls

Real-time NLP can be used during a phone call. The software would recognize the client’s speech and automatically fill out the claim form. Speech recognition can be based on the list of words related to every field of the quote. If some fields are not filled or filled incorrectly, the system could ask the respective questions.

For Emails

Moreover, AI that uses real-time NLP can be used alongside an existing manager that processes claims. That approach will boost the manager’s productivity and decrease the number of mistakes made due to negligence.

Finally, the client could be fully served during only one phone call, without redirects to other managers and repeated calls.

NLP INTEGRATION BENEFITS

Great improvement of customer service

No more redirections from one manager to another. One manager can provide a full range of services in short terms and without delays.

Accelerated claims processing

Intelligent software can analyze incoming information — both human speech and plain text — faster than humans. Algorithms can process data 24/7. The only thing that people would do — check data after the machine and confirm the result.

Increased insurance claims processing workflow productivity

If we use a chatbot like an assistant, it will decrease the number of mistakes made by personnel and increase the number of processed claims. Let your workforce concentrate on high-value tasks while improving productivity.

By the way, such claim processing chatbot can be integrated with insurance claim anti-fraud solutions. Such interaction will lead not only to claims processing optimization but also to decrease the number of fraudulent claims.

HOW TO IMPLEMENT REAL-TIME NLP IN A SIMPLE WAY AND AVOID COMPLEXITY

Even a few years ago Artificial Intelligence software development was quite expensive, but today the situation has changed. Nowadays, AI solutions and neural networks use popular frameworks and libraries in their core.

Almost all the frameworks and libraries are fully open-source and contributed by well-known companies or independent developers. For business, this means a great reduction of the development cost for AI-based software, as instead of developing a core of the system, developers have the opportunity to use well-known, secure, and documented solutions.

It should be also noted that an hourly rate of development is also decreasing. It’s easy to find highly qualified developers at affordable rates all over the globe. If you have an international project, you can rely on an outsourcing dedicated team. As already been said that price would be also reduced if the developers use open-source frameworks.

Another issue is data that is needed for successful neural network training. It’s quite hard to provide a sufficient amount of data. But it doesn’t totally apply to the insurance industry, as an insurer stores thousands of phone call records and emails. In these terms, most of the companies are already prepared.

Inmediate is an insurtech startup from Singapore that is using the latest technology such as Artificial intelligence, Distributed Ledger, and NLP, making insurance processing and underwriting fast, cheap, and flexible. That gives for better processes, lower costs, improved time to market, and new revenue opportunities.

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Introducing Inmediate: a platform on which customers, distributors and insurers using smart contracts connect. https://inmediate.io

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