How AI Enables Smarter Claims Processing & Fraud Detection?


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AI technologies have well and truly reformed information systems by making them far more adaptive to humans while significantly improving the interaction between humans and computer systems.

With this, Artificial Intelligence within the Insurance industry has overhauled the claims management process by making it faster, better, and with fewer errors. Insurers now have the option of achieving far better claims management by utilizing the technology in the following ways:

 Facilitate a real-time Q&A service for a first notice when it comes to losing.
 Pre-assess claims while automating the damage evaluation process.
 Automate claims fraud detection through rich data analytics.
 Predicting patterns of claim volume.
 Augment loss analysis.

From smart chatbots that offer quick customer service round the clock to the array of machine learning technologies that spruce up the functioning of any workplace through its automation power, the expanding potential of Artificial Intelligence in Insurance is already being used in many ways.

With increased awareness and resources about the game-changing influence of AI in the Insurance industry, the initial hesitations and shallow discomfort around its implementation are now fading quickly as it begins to trust in the caliber and numerous opportunities brought forward by Artificial Intelligence and Machine Learning. The only question that remains is – how far can we push its capabilities?

The role of AI in the Insurance industry

In 2017, Artificial Intelligence has shown its substance in various business verticals by rapidly creating controlled, digitally enhanced automated environments for maximum productivity.
Apparently, Insurance companies, in particular, have a lot to gain from investing in AI-enabled technology that can not only automate the scheduling of executive-level tasks but can also enrich service quality by helping agents make right decisions and irrefutable judgments.

A glimpse of AI-enabled innovations and solutions

Insurance companies, as on today, face 3 major challenges:

 Reaching out to prospective customers at the right time.
 Providing the right set of products that suit customer requirements.
 Fastest claim support to loyal customers and rejection of spurious claims.

Insurance companies are striving for a technologically advanced system that helps keep all their employees synchronized. These employees vary from agents, brokers, claim investigators to market and support team. These group of employees coupled with redundant processes create layers of confusion in the Insurance ecosystem.

Ai in insurance

To make the system more refined and efficient, they should opt for stable and consistent AI-powered solutions that can penetrate the layers of confusion and propel a clear value proposition towards customers. AI in the Insurance industry offers several promising technology-enabled solutions:

The uninterrupted flow of business information

Numerous industries have already adapted to the changing environment of digital technology and have creatively integrated automation and robotics to reshape their productive channels and unsynchronized structures. Some of the industries that have experienced and leveraged the power of Artificial Intelligence are Hospitality, Healthcare, Customer Service, E-commerce and more.

The fact that insurers and insurance companies are surrounded by piles of data and many other scattered management segments isn’t exactly new.

Leveraging AI’s data processing capability, insurers can enable a strategically built sophisticated environment where information pertaining to business and customer interactions can flow from one specific department to another on a common platform without any chain breakers. Thus, insurance companies not only organize task management for their employees but in many ways, it helps elevate the quality of the end-to-end information management system.

Automated claim support

AI-based chatbots can be implemented to improve the current status of the claim process run by multiple employees. Driven by Artificial Intelligence, the touchless insurance claim process can remove excessive human intervention and can report the claim, capture damage, update the system and communicate with the customer all by itself. Such an effortless process will have clients filing their claims without much hassle.

For e.g., an AI-powered claims chatbot can review the claim, verify policy details and pass it through a fraud detection algorithm before sending wire instructions to the bank to pay for the claim settlement.

This is the best example of how claims with standard documentation can minimize human efforts and can be reviewed by bots, thus saving on the workforce for Insurance giants and deliver instant customer assistance. Additionally, AI-powered automated claim support system can liberate companies from expensive fraudulent claims, human errors and resultant inaccuracies by identifying data patterns in claim reports.

Interactive power of Insurance chatbots

Because of lengthy documents, complex policies and tedious instructions, customers often develop a phobia and feel confused and daunted at the idea of settling for Insurance policy. They need human-like interactions that enable both smooth transaction and education.

Intelligent chatbots exceed the capability of Insurance agents and serve as a virtual assistant in messaging apps on customers’ devices. For an in-depth understanding of customer queries, chatbots should have NLP support along with sentiment analysis to assess a customer’s reaction and resolve issues accordingly.

Customers can either type or use their voice to communicate their concerns pertaining to different policies which chatbots can process to deliver personalized solutions. Starting with fundamental questions related to claims, chatbots can do a lot more such as product recommendations, promotions, lead generation or customer retention. These bots can be integrated with the channel of your choice (Website, Facebook, Slack, Twitter, etc.) to guide customers with quotes, policy explanations and purchase of insurance covers.

Advanced underwriting

IoT and tracking devices yield an explosion of valuable data which can be utilized to make the process of determining insurance premium upright and regulated. Fitness and vehicle tracking system in both health and auto insurance sector give rise to the dynamic, intelligent underwriting algorithms that cleverly control the way premium is dictated. Using Artificial Intelligence and Machine Learning, insurers can save a lot of time and resources involved in the underwriting process and tedious questions and surveys, and automate the process.

Insurance bots can automatically explore a customer’s general economy and social profile to determine their living patterns, lifestyle, risk factors, and financial stability. Customers who are more regular in their financial patterns are qualified to feel safe through low premiums. Since AI is more capable of strict scrutiny of gathered data, it can predict the amount of risk involved, protect companies from frauds and give justified insurance amount to customers.

MetroMile, a US-based start-up, has established such a dynamic underwriting system known as ‘pay-per-mile’ where usage of a car determines the insurance premium. Here, an AI-based device installed on the vehicle by the company uses a special algorithm to monitor miles, jerks, collisions and frictions, speed patterns and other car struggles on the road, and it collects detailed data essential to decide whether or not drivers deserve low premiums.

Predictive Analytics for proactive measures

Predictive Analytics backed by Machine Learning is now perhaps the heart of intelligent services across many business verticals that have adopted AI-powered solutions. However, this smart capability is not just aimed at driving future insight into customer’s preferences and tailoring relevant products. Health insurance companies are coming up with rewarding pre-emptive care that is focused on encouraging customers to look after their personal well being. If a person remains healthy, companies don’t need to invest in claim payment and management process.

For instance, Aditya Birla Health Insurance has planned wellness benefits to encourage customers to stay healthy. AI’s predictive algorithms scan past year’s claim activities and hospitalization data to provide incentives to customers to improve health & wellness. This way, health risks will be minimized and so will be the company’s resources.

Thus, nowadays, start-ups leverage AI’s unique potential to scour through piles of claim data and coverage patterns to be more proactive and anticipate health risks at the individual level before they actually transpire.

Marketing and relevant products

Marketing is another action gear for insurance companies that wish to enhance their reach and secure higher customer acquisition. Being a part of the competitive market, insurers need to capitalize on a vital marketing strategy which goes beyond the traditional cold calling approach.

The old blanket methods are on the verge of extinction since digital disruption has already shaken the grounds of the insurance field. Customers today seek sophisticated, luxurious and extremely personalized services with custom sales tactics. Using the combined power of predictive analytics, NLP and AI in the insurance industry, agents can gain access to the full profile of customers and prospects. This data can be further analyzed to generate mature insight, accurate predictions on customer preferences and what exact products or offers should be added in their marketing activities.

A quick look at AI in the Insurance industry today

According to a survey Accenture, as on today, 74% of customers would like to interact with modern technology and appreciate the computer-generated system of insurance advice.
Companies who have been early to adopt automation of some aspects of their claims process can experience a significant fall in processing time and cost, and a good increase in service quality.

Talking about early adopters, All state Business Insurance has also recently developed ABIe in partnership with EIS. ABIe (spoken as Abbie) is an AI-based virtual assistant application designed to cater to Allstate insurance agents looking for information on ABI’s commercial insurance products. Hopefully, as time goes by, we will get to hear more such breakthroughs of AI investments in insurance companies.
The power combination of Machine Learning, advanced analytics, and IoT sensors enables insurers to reach prospect clients, study their real-time needs, develop insight from their profile on risk magnitude, and ultimately create bespoke solutions.

The future of AI in the Insurance industry

While challenges appear to dismay the present market, insurers still like to view the potential of AI in the Insurance industry with optimistic eyes. To reap the full range of benefits, insurance companies need to devise an enterprise-level strategy to implement AI in such a way that it offers more than just customer experience.

At Maruti Techlabs, we are already working on multiple applications of AI in the Insurance industry when it comes to claims management, damage analysis through image recognition, automated self-service guidance, and others.

When it comes to image recognition, the overall damage analysis, cost estimation, and claim settlement would be carried out by bots that scan through pictures and videos. This way, with time, companies can rely completely on image recognition technology for first level claim automation and subsequently, settle claims or resolve fraud detection in insurance automatically. By working on smart automation of existing workflows, we aim to reduce the time and resources spent on managing or monitoring claims, increasing process efficiency and enhancing the customer experience.

With new AI tools constantly reinventing the claims management, the payoff is bound to include smarter fraud detection, faster settlements, and better customer service.

Rapid advances in technologies over the next 10 years will lead to disruptive changes in the insurance industry. Companies that adopt new-age tech to develop innovative products, harness cognitive learning insights from a myriad of data points, streamline processes, and more importantly, personalize the entire customer experience will be the winners in the AI dominated insurance space.

Mitul Makadia
Mitul Makadia is Founder of Maruti Techlabs and a true technophile. With his industry experience, he has rapidly developed Maruti Techlabs in specialized services like Chatbot Development, Artificial Intelligence, Natural Language Processing and Machine Learning. Makadia has considerable expertise in Chatbot Development and NLP.


  1. Nice article!
    Fraud Detection Software – K-nearest neighbors (KNN). The algorithm predicts which class an unseen instance belongs to, based on K (a predefined number) most similar data objects. The similarity is typically defined by Euclidean distance but, for specific settings, Chebyshev and Hamming distance measures can be applied too, when that’s more suitable.


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