Artificial intelligence (AI) is starting to play a vital role in automated fraud detection for insurers looking to better enhance fraud prevention measures. By utilizing machine learning (ML) algorithms that improve with usage, insurance companies have expanded the integration of AI beyond fraud detection to areas such as claims management, risk assessment and pricing, sales and marketing, and customer service. According to Accenture, 75 percent of insurance executives believe AI will provide significant industry changes in the next three years.

AI can uncover hidden correlations and patterns previously undetectable to the human eye. The initial impact in insurance has been in the narrow AI space, which focuses on specific tasks that can be automated to vastly improve output and efficiency, because computers don’t get tired or require sleep. When combined with mobility, AI’s potential to impact the insurance industry and its workers is limitless.

IoT Feeds the Machine

To generate multiple decisions, AI must be fed lots of data. The voracious hunger for big data has spawned the Internet of Things (IoT) to provide an endless stream of round-the-clock data derived from connected sensors that spot trends and assess behavioral patterns of consumers, employees, customers, elements, devices and machines. ML algorithms spot these patterns to develop and progressively improve working real-time models, which are analyzed and produce new insights.

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By utilizing big data analytics and real-time IoT data streams, AI can efficiently build more accurate predictive risk models to support robust pricing for personalized insurance products. By pairing behavioral patterns with the most suitable products, AI can improve ROI and ignite sales growth by targeting the most receptive prospects. Personalization enhances the customer experience by matching them with the most relevant insurance products. AI-powered risk assessment tools can improve underwriting specialized lines of insurance, which have historically been difficult to cover. These smart insurance products embody the customer-centric solutions-based trend that is reshaping the financial services industry.

AI Powered Automation Drives Efficiency

Insurance claims processing can be a monotonous task susceptible to errors stemming from uniquely human factors like fatigue, boredom and deadlines. AI can enhance fraud prevention, as ML algorithms automatically filter and push through valid claims while flagging “suspicious” claims for investigation. The technology can also continually improve the fraud detection process because it has the ability to refine analytical models as new data presents itself — ML lets the system learn from this new data and enables independent adaption. With this ability, insurance companies can consistently ensure their automated fraud detection algorithms are up to date and as accurate as possible. With AI-enabled software on mobile apps, workers have access to up-to-the-minute information while they’re in the field.

AI Streamlines the Workforce

According to the Mainichi, a recent report states Tokyo-based Fukoku Mutual Life Insurance Co. will slash 30 percent of its claims payment department staff for IBM’s Watson-powered AI system that will help manage over 130,000 insurance claims annually. The cognitive learning system can “think like a human” with the ability to understand speech and gather, research, analyze and interpret both unstructured documents, images and videos and pre-formatted, machine-ready structured data.

This automation will alleviate much of the tedious legwork and flag suspicious claims for further investigation by human specialists. The $200 million yen ($1.8 million USD) AI system costs an additional $15 million yen ($133,000 USD) annually for maintenance, but pays for itself in under two years by expected savings of $140 million yen ($1.25 million USD) in annual labor expenses alone, the Mainichi reported.

AI Powers Fraud Prevention and Detection

French AI startup firm Shift Technology incorporates this technology in their fraud prevention services, which have already processed over 77 million claims. The cognitive machine learning algorithms have reached a 75 percent accuracy rate for detecting fraudulent insurance claims. The ML algorithms provide details on suspicious claims with potential liability and repair cost assessments and suggest procedures that can resolve and enhance fraud protection.

AI Chatbots Enhance Customer and Employee Service

Insurers are discovering the efficiency of AI chatbots, as they provide convenient and frictionless customer service that can address common inquiries and transactions; this frees up human reps to handle the more complicated situations. AI chatbots are up to 1,000 times faster than a human and always accessible with no hold times. True AI chatbots are built on natural language processing and ML that help them replicate human learning capabilities.

One current example of this is Allstate Insurance and their AI chatbot ABIe (Allstate Business Insurance Expert). The chatbot is a one-stop shop to answer questions, walk through the quoting process and retrieve documents for agents. ABIe processes over 25,000 monthly inquiries from their agents and alleviates call center traffic, so representatives can spend their time on more productive tasks.

AI Moving Forward

Though it’s still early for the advanced integration of AI, it’s become a well-established belief that the future of the insurance industry will be shaped by this technology. While current AI applications are concentrated on narrow AI, which automates specific tasks, the future will see more deep machine learning integration to augment general AI — bringing machines closer to emulating human reasoning. AI adoption is growing daily, and it’s quickly becoming a standard embedded component for forward-thinking insurance carriers. However, to have the greatest impact, AI needs a mobile solution built on top of it and a mobile-enabled workforce.

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Jea Yu

Jea Yu is a co-founder of, an online trader education site that has served over 10,000 traders, fund managers and investors worldwide since 1998 and was voted Forbes Best of the Web for four consecutive years in the active trader category. He has published best-sellers through McGraw-Hill, John Wiley and Bloomberg Press and has been interviewed in popular periodicals including the Wall Street Journal, Stocks & Commodities, the Financial Times, Active Trader Magazine, Traders Magazine and USA Today. Follow him on Twitter: @jeayu21

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