Last year, a Finnish insurance company, Turva, was all over the news in its home country when its chatbot committed a blunder by referring to a customer’s newborn baby as an accident and offering condolences. The customer had asked the on-line chatbot about the procedure for reporting the birth of a child.
While the incident led to a lot of jokes and funny banter, Turva later explained that the mistake could have happened because the inquiry included the words, “How do I report..”.
Since people typically ask how to report a loss, the bot was possibly confused, as it hadn’t been asked a question regarding the birth of a child before. That being said, the company’s bot was eventually trained on human birth aspects and can answer such questions with confidence now.
This is just one of the many incidents that go on to prove that Artificial Intelligence (AI) is only as good as the data it is trained on. Fortunately, data is one resource that is available in plenty with every insurance provider. Thus, AI, a technology that enables computer systems to accomplish tasks that typically require a human’s intelligent behavior, such as information gathering, data analysis, and decision-making, can prove to be a potent tool for transforming the insurance industry.
How Can AI Help Insurance Companies?
First, let me touch upon the three common problem areas faced by the industry. Inability to personalize their marketing efforts, ensuring quicker claim support, and detecting frauds and rejecting spurious claims – these areas have kept many COOs up at night.
But AI can help.
We are all aware that insurers are sitting on a large treasure-trove of unstructured customer data. This very data can be leveraged by AI to create more meaningful marketing material, offer personalized service, and sell the right product to the right customer through proper targeting and profiling.
However, personalization is just one of the challenges that AI can help insurers to overcome. AI can also uncover hidden correlations and patterns previously undetectable to the human eye, making it useful for detecting suspicious activity or fraudulent behavior. Here are some cases of AI in the insurance industry beyond customer support and marketing:
Fraud Detection
In the United States, the FBI estimates that insurance fraud robs the insurance industry of well over $40 billion a year. AI and machine-learning tools can considerably reduce this number by enabling insurers to spot unusual patterns that a human might miss. For example, by comparing new claims to the existing data, AI in the insurance sector can help detect claims that are unusually high and probably fake.
Insurance companies may also use visual analytics to assess auto or property damages based on images and videos. Using visual evidence, AI can examine whether the damage is worth the amount that has been quoted by analyzing data from similar claims in the past.
AI can also be used to continuously monitor employee and customer behavior to look for patterns indicating large-scale fraud. A customer making odd claims, or a debt-ridden employee making unusually large financial transactions – these are potential red flags that AI can highlight for further investigation.
Automated Claim Support
Currently, the claim process followed by most insurance companies needs action by multiple employees, which slows it down significantly. Artificial intelligence introduces a touchless insurance claim process that removes excessive human intervention from the equation.
With AI, a computerized system is used to report the claim, capture the damage, update the system, verify the claim’s authenticity, and even communicate with the customer – without the customers needing to fill up any lengthy forms or visit a physical office. Besides being convenient, this solution is relevant in the post-COVID era, where the focus has moved to digital transactions, and businesses are increasingly opting for touchless workflows.
If you have heard of Lemonade, you may want to check out their claim process, explained in the video that follows this paragraph. The insurance provider uses AI to manage the whole claim process, making it swifter and much more efficient. Users need to tap a button on the Lemonade mobile app to initiate the claim process. This leads them to chatbot Jim, to whom the customer may explain his or her situation. While the next steps are not clearly outlined anywhere, it seems like the application uses AI to match the claim description given by the user to similar claims stored in its database. This not only expedites the approval but also helps in determining whether the claim is genuine or fraudulent. If the claim is found legitimate by the system and isn’t too complex, the user can expect the payout (presumably in his or her bank account) in seconds. Of course, complex claims go to real Jim (a human representative), but gradually the system would be trained to deal with these as well.
Advanced underwriting
Today, the Internet of Things (IoT) and various tracking devices make it possible to collect data in real-time. This data can be used to determine various risk factors for individuals to determine the insurance premium in a regulated manner.
For example, instead of relying on the usual surveys and questions, a company may deploy a chatbot to automatically explore an individual’s lifestyle, financial condition, medical history, etc., by using a sea of data collected from various sources. Finally, it can employ predictive intelligence or machine learning to determine the future behavior or health of the customer based on his or her present actions – which can indicate the risk that the policyholder may pose to the company.
Some health insurance companies, like Aditya Birla Health Insurance, are also leveraging predictive analytics to encourage and reward pre-emptive care in customers. The logic is simple if a person remains healthy, he or she won’t go to the doctor and submit a claim, saving time and money for the insurer.
Some Final Thoughts
Today, AI has become an integral part of our lives. We use chatbots to interact with companies and rely on home assistants like Alexa to manage something as simple as our shopping list. In the insurance sector, while the usage of AI started in customer support, continually refining machine learning algorithms have expanded its applications to multiple aspects, such as claim management, fraud detection, risk assessment, and pricing.
However, it must be said that the role of AI in insurance is not to replace humans but to make their lives easier by taking up labor-intensive or repetitive tasks. If you are looking for customized AI-based solutions to improve your customer’s experience, contact Milestone for a quick demo of our POC on how you can detect frauds using AI….
