AI's role in Insurance Sector
Applications of Artificial Intelligence in the Insurance Sector
The terms Artificial Intelligence (AI) and Machine Learning (ML) have seen a recent upsurge in use by companies. Needless to say, AI/ML has become a significant aspect of the future. Recognizing the potential of AI/ML technologies has, the companies are trying to adopt and implement them into their service capabilities. As the insurance industry has a widespread reach, the applications for AI/ML technologies exist throughout the entire gamut of services that these companies offer.
Need for Insurance
The main function of the insurance is to provide protection against the probable chances of loss. The time and amount of loss are uncertain and at the happening of risk, the person will suffer loss in absence of insurance. This leads to claims by an insured party in case of adverse situations happening.
Slowly but steadily, the entire landscape of the insurance industry is being influenced by AI technology. Currently, the insurance market worldwide is dominated by massive national brands offering several legacy products that have not substantially altered for a long time.
Change is inevitable in this industry and AI is a harbinger of these changes. Insurance companies are trying to transform utilizing the potential of AI technology.
The insurance companies are providing services to the customers either on their own platforms or via third-party vendors on which people can buy or renew their policies.
For example, in India, the Policy Bazaar app has become quite popular. Here, one has to just provide a few details and one will get a personalized policy in just a few minutes without any paperwork.
Insurance management with AI systems will automate the underwriting process. Based on big data analyzed through ML algorithms companies can make better decisions for the customers.
Automated agents (often called chat-bots) can assist the user online, in determining insurance requirements.
Today, with the support of natural language processing, companies can ensure customer-centric conversational experiences for their clients. AI-powered chatbots have proven to increase user engagement and customer acquisition. Therefore, chat-bot adoption is growing fast in the insurance industry. Following are the prime use cases of chatbots in this industry.
Conversational bots in insurance are widely being used for customer support since chat-bots can resolve a complaint instantly.
Chatbots are faster than human workers in looking up information and answering questions. Also, chatbots are available at any time. They can quickly provide information on a variety of insurance plans available and help customers zero down on an appropriate choice.
Customer support chat-bots in insurance can be integrated with the company’s website, a messaging platform, or a mobile application. They can provide quick help in case of emergency and guide users through complex premium and claims handling processes.
Underwriting in insurance is the process of evaluating the risk of insuring a home, car, driver, or individual in the case of life insurance or health insurance, to determine if it’s profitable for the insurance company to take the chance on providing insurance. After determining risk, the underwriter sets a price and establishes the insurance premium that will be charged in exchange for taking on that risk.
Automatic underwriting fastens the process. One can employ the data sets that were used before to access the risks, to then lower the probability of damages happening to the insured and to the insurer.
One such company that offers AI-based underwriting services is “underwrite.ai.” Brief details are presented in the graphic below.
How it’s using AI in finance: Underwrite.ai analyzes thousands of data points from credit bureau sources to assess credit risk for consumer and small business loan applicants.
The platform acquires portfolio data and applies machine learning to find patterns and determine good and bad applications. Because of its accuracy, Underwriter.ai claims it can reduce defaults by 25–50%.
Industry impact: Since working with Underwriter.ai in 2015, a major online lender providing dental financing reduced its default rate from 17.8% to 5.4%, according to a case study cited on the company’s website.
Fraud Detection and Claims Handling
Fraud-related losses and damages are common in the insurance industry. To restrict the occurrence of such instances, insurance companies started utilizing AI/ML technologies. ML tools collate trends leading to enough data necessary for conviction. AI tools also learn and monitor user’s behavioral patterns to identify exceptions and early warning signs of fraud attempts and incidences.
Claims management can also utilize ML techniques at various stages of the claims handling mechanism. These algorithms identify patterns in the data to help recognize fraudulent claims in the process. With their self-learning abilities, AI systems can then adapt to new undiscovered cases and further enhance the detection over time.
By leveraging AI and handling a huge amount of data in a small duration, insurers can automate the handling mechanism. It can even hasten certain claims, to reduce the overall processing time, and to reduce handling costs. This enhances the customer experience manifold.
The major applications that would guide the adoption of AI by insurance companies are driven by the following:
Chatbots/AI assistants: This will play a role in improving customer service. The automated AI chat-bots can assist customers in a far better way than human assistance. This is one application that is bound to grow.
Insurance Product Development: Machine learning algorithms are being applied to client data to help develop more customized products for insurance clients. This can also be coupled with IoT (internet of things) to assess behavioral patterns.
Market Analytics: Machine learning algorithms can be applied to the industry data to interpret and monitor market trends. This will help in identifying and building new business opportunities in the sector.
Customized Claims Settlement: Online interfaces and AI-based claims settlers will make settlement processes more customized and efficient. This would also decrease the likelihood of fraud.
Underwriting: Historically, the process of underwriting was an art based on personal judgment. With the advent of AI technologies, the underwriting part of insurance has made this process increasingly scientific.
AI has immense possibilities to disrupt the insurance industry. On one hand, it liberates the customers from frustrating and bureaucratic experience to an easier and quicker customized resolution yet, on the other hand, insurers can optimize their cost and reduce the customer churn.
In the future, bespoke insurance products will help customers get insured at more scientific premium rates. Several new products will be spawned based on Big-Data analytics to provide features such as flexible insurance with on-demand, pay-as-you-go insurance, and premiums that are heuristically adjusted in response to accidents, customer health, etc.
Finally, the insurance will become more and more personalized, due to usage of AI by insurers to better understand what their customers need. In addition, insurers will also be able to drive cost savings by more efficient workflows.