The global AI market is estimated to grow at a CAGR of 42.2% to $733.7 billion by 2027, and with that the AI & ML applications in insurance are only going to increase in leaps and bounds.
AI has been widely adopted across the world by businesses in diverse industries and the insurance sector has been no different. From claim processing to underwriting to fraud detection, AI has garnered immense popularity and proved highly beneficial to insurance carriers. The pandemic has only reinstated the need for the swift adoption of AI/ML applications in business operations.
What makes insurance industry even more appealing is the amount of invaluable data held by the carriers- a treasure trove to build the perfect business intelligence!
So, let’s look at the top ways in which AI & ML may find rapid adoption in the insurance industry.
Heavily dependent on data and analytics, the underwriting process in insurance involves risk analysis and pricing, thus ensuring it as an integral part of the insurance process. A highly manual task, with AI in the equation, the process of underwriting has become easier, quicker and more accurate.
Intelligent underwriting algorithms can analyze customer information to create reliable customer profiles and detect risk more efficiently. Efficient underwriting will move the benefit to the customers as well by charging the right rates for each applicant – thus ensuring personalization at its best.
Claims Reporting, Management, Investigation
Yet another key and cumbersome part of insurance, AI/ML is of immense usage in claims reporting and management since settling a claim involves processing loads of data and interacting with many stakeholders. But with AI/ML applications, all the routine data checks, as well as interactions, can be automated.
With advanced AI systems, insurers can report, route, triage, and assign claims with or without any human intervention. Digital assistants, paired with NLP and automatic speech recognition, can both effectively and efficiently manage the processes, thus enhancing productivity.
Similarly, insurers can leverage AI tools to streamline their claims assessment and settlement process. AI can regulate all of the processes from data-capturing, claims creation, authorizations, approvals, payment tracking to recovery tracking.
In the United States alone, insurance frauds have been the reason for the additional costs to the tune of $40 billion in losses each year for the insurance industry. Scammers are found to use numerous ways to commit insurance fraud. Insurance fraud detection using machine learning can be an efficient way to identify these scams.
Analyzing large data sets of genuine claims, AI/ML-based software can create models of typical insurance claims. Any deviation from typical claims will be flagged as a potential fraud, thereby enabling insurance companies to reduce risks and costs related to frauds and achieve superior results. AI can play a pivotal role in finding patterns in historical data, which helps in the early detection of fraud and prevent them from taking place.
When combined with deep learning and other applications like interactive bots, artificial intelligence in insurance can improve customer-facing operations multifold. For instance, AI-based chatbots can provide speedy responses to routine insurance queries with higher accuracy than human agents. In fact, 40% of customers don’t realize that it isn’t a human answering their questions in the online chat.
Additionally, using chatbots, insurance companies can save almost $1.3 billion by 2023 across motor, life, property and health insurance, according to Juniper Research.
AI software can help marketers collect and analyze valuable information from different sources such as website visits, chatbot conversations and social media channels. This data, when combined with tailored lead interactions, personalized recommendations and timely suggestions can help drive new business. Using NLP and deep learning to analyze routine conversations, chatbots can collect data around individual preferences, behaviors, past purchasing habits, age group and income, all of which can help provide personalized product recommendations. This also opens up possibilities for cross-selling and upselling policies.
AI-driven chatbots have already gained traction in the sphere of customer service. In the insurance industry, these chatbots can enhance scalability and take the load off of human resources for more critical matters. At the same time, the chatbots can play to their strengths and cross-sell or upsell products depending on the customer profile and history. In short, AI can help tap into various thrust areas of improving overall customer experience.
The regulatory landscape of the insurance industry is complex and ever-changing. One of the biggest challenges that insurance companies face is keeping pace with regulatory changes and incorporating these into policies. For instance, the relatively new regulations of General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have raised the stakes for data protection and privacy for insurers. NLP technologies can help scan internal policies as well as claims documents to check their compliance with different regulatory policies. AI and ML applications in insurance can augment human intelligence to help companies avoid regulatory missteps that could cost them millions in non-compliance penalties.
AI brings about a wave of uniformity across different market segments, industrial verticals, and service providers. As a result, obtaining insurance and claims settlement procedures can be more standardized throughout. Other benefits that we can anticipate would be greater operational excellence, lower costs, and enhanced customer experience. By leveraging Artificial Intelligence in insurance, the insurance players can gain a host of benefits such as better productivity, enhanced customer experience, efficient claims management, reduced frauds, and more. Clearly, the future of AI-driven insurance is a bright one, and the use of AI in insurance sector will see a massive boost in the coming future.
Today, insurance chatbots can basically be deployed as a customer’s personal insurance manager while equipping the sales team with valuable and contextually relevant insights at the same time and the industry is soon to become seamless and chat-intensive!