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How ICICI Lombard Leverages AI and Analytics For Automated Processing Of Insurance Claims

How ICICI Lombard Leverages AI and Analytics For Automated Processing Of Insurance Claims

Vishal Chawla
Girish Nayak ICICI Lombard Insurance

In the last decade, insurance providers have had to move away from their traditional core systems towards more flexible, cloud-based applications that have auto-scaling capabilities. This has been done to help consumers have a seamless insurance purchase and a faster and better consumer experience. In this context, the insurance industry is leveraging several technologies, including digital platforms, robotic process automation (RPA) for quick policy issuance and servicing, AI and ML for claims and policy servicing, and bots powered by Natural Language Processing techniques. 

Insurance was one of the first data industries and most insurance organisations continue to leverage data to solve some of the business problems in insurance, including identifying and segmenting customers, identifying new products, identifying new service propositions, driving claims efficiencies, identifying fraudulent behaviour and also in identifying various operational efficiencies. Today, the insurance industry is witnessing new and quickly evolving consumer expectations and behaviours emerging. This is basically driven by an expanding internet user base driven by the smartphone penetration within India. This has also caused a fundamental shift in how insurance companies serve customers.

Recently, we interacted with Girish Nayak, Chief-Service, Operations and Technology, ICICI Lombard General Insurance to further know the evolving customer needs across digital platforms and how ICICI Lombard is transforming its insurance processes. The insurance company continue to build technological solutions that make it easier and simpler for its customers to purchase or renew their insurance and simplify their servicing needs.



To give an example, ICICI Lombard launched its AI-based break-in inspection service where customers whose motor insurance renewals have expired can instantly renew their policies. All customers need to do is to take several photos of their vehicle, and its cloud-based AI-powered engine decides on instant policy issuance or on passing this case to a human adjuster for further verification.

According to Girish Nayak, prioritisation of key technology initiatives is instrumental in servicing customers and holds the key to maintain a long term competitive advantage in the instance sector. In the following interview, we get to know more about how technology, particularly data analytics, is powering the insurance company. 



How has the COVID-19 pandemic impacted IT spending at ICICI Lombard?

Girish Nayak: We at ICICI Lombard are always committed to providing a healthy, safe and flexible working environment for each of our employees and at the same time committed to serving our customers, channel partners and our stakeholders. Obviously, no one could have predicted the gravity of the current situation six months ago. With this prevailing pandemic, every business will need to look at their overall budgets, including their IT spending. As an organisation, we always focus on prioritising IT initiatives that are of utmost importance in servicing our customers. 

With a majority of people working remotely, immediate spending was and will continue to be centred on enhancing seamless and secure remote operational abilities including IT security, facilitating cloud and data centre infrastructure as needed. However, currently, the safety and security of our employees, customers and partners are of topmost priority to us. We will continue to evaluate the situation as it evolves and tailor our budgets according to the situation. Services and support are essential for a business to continue functioning smoothly and will continue to take priority in times like this.

How does ICICI Lombard use innovation to maintain a competitive edge? Can you elaborate with a few examples?

Girish Nayak: We all know that technology acts as a key enabler for any organisation today, and even more so with the situation that we are currently in. We all know that consumer expectations continue to evolve, and at ICICI Lombard, we are committed to satisfying the needs of our customers and our stakeholders. At ICICI Lombard, we continue to use technology to develop innovative offerings to help customers to have a seamless insurance purchase and in faster and better customer experience at the time of servicing policyholders.

We have AI-based bots, and today, our customers and partners can instantly get answers, quotes or can easily complete various transactions without any manual intervention through our AI-based chatbot platform – MyRA. e.g. customers can buy TW insurance, renew their health and motor policies on this platform. Similarly, we are leveraging natural language processing and robotic process automation technology for automating the manual process of quote generation and policy booking for our corporate and SME customers. For instance, for certain SME products, ~ 90% of our policy issuance is done through our automated system.  

How is ICICI Lombard utilising data to solve commercial and operational inefficiencies?

Girish Nayak: First, we are adopting new ways of personalised pricing. In the private car insurance space, we are leveraging data obtained from telematics devices to identify and segment customers based on their driving behaviour and offer pricing in accordance with their driving behaviour. We are finding that driving behaviour is highly correlated with claims data and offers new insights on how we can adopt this as a rating variable and offer advice to customers on how to alter their driving behaviour. Similarly, in the health insurance space, organisations have started to evaluate how health-related behaviour of customers like exercising and walking obtained from wearable devices has an influence on future events and how we can prevent them.

Second, we are using big data and analytics to identify fraud: we have been using big data-driven AI and ML-based fraud detection models that use extensive amounts of data to predict and highlight probable fraudulent claims. Large quantities of internal and external data are processed at the time that a claim is intimated and logged within the system. Since these models follow the continuous self-learning approach, it helps us to implement solutions that auto-correct very fast, reducing the time for learning and execution.

How can insurers take a more customer-centric approach using data rather than focusing on selling products?

Girish Nayak: Today’s generation of digital natives are very much multimedia oriented, are extremely social digitally, prefer digital over physical interactions and ratings & reviews influence their buying decisions a lot. They prefer instant gratification, need highly personalised products, and brand loyalty is becoming a thing of the past.

On the other hand, we are also witnessing various kinds of emerging technologies and innovative business models which have the potential to transform the insurance business. Broadly that includes big data and data analytics, ML and AI, IoT, Robo advisors, comparative engines and distributed ledger technology (DLT), blockchain and smart contracts, as well as peer-to-peer, usage-based or on-demand insurance models. 

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To respond to these evolving customer needs, and the availability of digital technologies, insurance providers have increased their digital distribution capacity through either their own online channels or through partnerships with digital platforms that provide a one-stop-shop to address the needs of customers – e.g. e-commerce sites, web aggregators, and product comparison engines. We continue to move in the direction of helping the customers to buy an insurance policy as seamlessly as possible and in settling claims for such policies in near real-time. 

What are the various AI and analytics that ICICI Lombard leverages, and how can data analytics solutions help the insurance sector gain deeper insights into customer needs?

Girish Nayak: As stated before, the insurance sector continues to evolve, some of it is driven by the changing customer behaviour, and some of it is driven by the availability of new technological solutions. Artificial intelligence and machine learning play a key role in achieving this, and a couple of examples of where AI and ML are helping us in this journey. To elaborate, for medical claims processing, AI is being used to process the cashless claims as requested by hospitals. The policy-related information, doctor’s diagnosis and the course of action recommended by the doctor are ingested in the AI algorithm, which decides the admissibility of the case. This was decided by a doctor at our end, earlier.

Based on the case admissibility, an ML program decides on the optimum claim amount to be sanctioned based on the overall policy sum insured and other parameters. For example, if the claim amount requested is for an amount of Rs 1 lakh, then an ML algorithm could potentially predict an initial sanctioned amount of ₹ 80,000 is sanctioned based on the information provided by the hospital and the policy terms and conditions. The ML program sends a message to the hospital, and the final sanctioning amount is established during the discharge of the patient from the hospital. 

This entire initial sanctioning process takes about 90 seconds. The same process, when done manually, would take 3 to 4 hours. We introduced this last year for corporate health claims. Of all the corporate health claims, over 40% per cent is processed using the AI/ML process. The rest of the 60% goes through human intervention. The doctors can thus dedicate more time doing the investigation for more complex cases leaving the simple cases for AI to process. 

Finally, what according to you are the ways by which business organisations can constantly re-skill their IT workforce so that they can meet the ever-evolving technology landscape?

Girish Nayak: An organisation’s ability to identify new opportunities is linked to its ability to adopt new technologies and solutions that help in servicing its customers and its stakeholders. We all know that skills of today are very different from the skills of yesterday. Most organisations talk about adopting AI/ML and robotics as compared to the digitization of data today. Reskilling has become even more important in today’s world, considering the pace at which the world is changing. The World Economic Forum predicts that by 2022, 42% of core skills required to perform existing jobs are expected to change and that more than a million jobs are likely to be transformed by technology in the next decade. 

While it is true that there will be a larger need to develop technological and scientific skills, it is also going to be equally important to develop specialised skills in how people interact, collaborate, and create new products and solutions. The best way to learn some of these skill sets is obviously to learn this in a real-world scenario. We constantly encourage our employees to develop innovative solutions using some of these new technologies. A lot of our AI and ML solutions are developed in-house by data scientists who have learnt these skill sets on the job. We have deployed these AI/ML solutions on the cloud platform. We have worked with both leading technology providers to arrange for training programs for our employees and in certain cases, company-specific hackathons which have helped our employees to learn and also create solutions on these platforms.

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