Insurance providers agree that 80% of them use or will eventually use AI in their work in the next three years. To understand why AI is crucial for the insurance business, let’s take a look at how AI software development redefines the traditional approach to fraud detection, customer service, policy design, and claim assessment.
Combating fraud: spotting fraudulent requests using machine learning
Earlier, deciding whether a claim is legit was solely an experience test for the employee handling the request. Now, the first stage of dealing with payment claims may not involve humans at all — AI can be taught to analyze any claim in a matter of minutes using smart customer profiling.
A customer profile includes past credit score, spending behavior, history of claims and other public records, available online or in a company database. Each application will be scored by an AI-powered machine and receives a mark with recommendations. The final decision, depending on the complexity of the claim, might still be up to a human insurance specialist.
If there are concerns regarding the identity of the insured or the agent, AI can address them by employing biometric authentication methods. These may include signature, face- and voice recognition to prevent identity theft and stop intruders early on.
Automating customer service: covering upcoming claims instantly with a virtual agent
Imagine there is a natural disaster like the Katrina hurricane, with thousands of concurrent requests. While the cause is the same, every situation is unique and demands immediate attention from the assigned agent. AI will take that burden off the insurer’s shoulders by processing triage and categorization of multiple claims faster than a human would ever do.
Virtual agents, chatbots and voice-activated interfaces never sleep or lose an objective view. They won’t miss a detail, and their ‘thought’ process is completely trackable: if there is a misunderstanding, the reasoning behind the decision will be reflected in the code.
AI contributes to eliminating unconscious age, gender, and racial prejudice during research and paperwork for claim settlement. It will only focus on what matters for the claim, and stay completely neutral, leaving customers satisfied.
Discovering trends: using analytics to reveal business-critical insights
According to the 2018 Advanced Analytics and the Future Survey, in two years AI will evaluate 70% of all claim applications. That means, AI-driven software will not only streamline the insurance-related tasks but also gather reliable statistics on what customers gravitate to.
By leveraging AI, you will enhance customer segmentation, and recognize ongoing patterns that are not visible to agents that work directly with clients. It will help come up with new ideas of insurance options by covering new, never-before-seen scenarios and nuances like autopilot cars and smart home setups.
The same research shows that mobile interactions will grow by 53%. Since people want to buy insurance online and get the papers signed the same day, the industry tends to become mobile-first. AI hasn’t got a problem with that — when an insured event happens, some insurers can approve a claim in under a minute.
Individualizing options: redesigning insurance products to ‘pay-as-you-live’
The mechanisms of building risk models and identifying high-risk cases are now mostly the tasks of ML-enabled applications. With a growing number of property types like electronics and smart home ecosystems, these tendencies pave the way for behavior-based insurance options like home and vehicle telematics.
Telematics means IoT-enabled monitoring, powered by sensors on a car or around the house, and paying premiums on a ‘pay-as-you-drive’ or ‘pay-as-you-live’ basis. The monitoring includes gathering precise data and real-time risk assessment. This can make an insurance plan potentially cheaper — if there are no events to cover with insurance. But if you get a ticket for speeding or break a pipe occasionally on your own, you pay more.
Such opportunities shift insurance pools from large unspecified categories to individuals that are ready to submit their data for a discount. At the same time, it helps providers collect insanely valuable real-life insights for a better understanding of risks.
Refining underwriting: reducing human involvement
The number of agents will initially become lower with the rise of AI and online-only insurance. But the demand for the insurance service won’t go anywhere. The technology and property around us become smarter and require increasingly more maintenance and therefore, insurance coverage.
The good news is, the delicate art of underwriting can be automated. AI-powered systems can redistribute employee resources where actual human input is needed, and save time on paperwork, researching social profiles, medical conditions, and credit scores. Instead of scanning multiple personal records, specialists can focus on reviewing complex cases and teaching AI to improve risk monitoring and mitigation technology.
Evaluating damage is one more duty that AI can be trusted with. Computer vision-based solutions will be able to recognize and prioritize car incidents based on their severity — making risk classification and rate calculation more informed and accurate
AI-driven insurance is inevitable
As in any other business, insurance providers are interested in lowering costs, accelerating decision-making, and increasing customer satisfaction. Due to the industry specifics, AI-related technologies happen to be the lever that pushes insurance forward in each of these directions.
The challenges of fraudulent claims, complex underwriting and reassessment, personalization, data collection and analysis will stay — but cause less friction because of biometric-based identification, ML-driven risk monitoring, and usage-based policies.