The 5 Top Trends in AI and RPA

AI and robotic process automation will transform operations, customer service, risk assessment and mitigation and regulatory compliance.

Insurance companies are only beginning to harness the potential of artificial intelligence (AI) and robotic process automation (RPA). AI refers to computer systems that can mimic human capabilities by learning and solving problems. RPA is an emerging form of business process automation technology based on using software robots or AI “workers.” Here is a look at the top five AI/RPA trends in the insurance industry: 1. Machine Learning for Fraud Detection and Risk Assessment Humans learn from experience and thus can predict outcomes. Insurers are beginning to use AI algorithms with big (and small) data to accurately predict outcomes. Machine learning, or AI, is being used to improve customer service, guide the development of products, detect risks and cross-promote products. It is helping insurance companies to improve their efficiency by facilitating damage assessment, identifying billing anomalies, boosting fraud detection and identifying lapsed policies. 2. Chatbots Offer Personalized Customer Care Chatbots use AI to work as autonomous, internal customer-service agents that respond to customer queries. They keep a log of most frequently asked customer questions. Chatbots can efficiently handle many routine requests, such as changing the policyholder’s address or adding a beneficiary. By handling grunt work, they can free skilled human advisers to offer the kind of guidance they do best. See also: Next Big Thing: Robotic Process Automation But there’s more. Using AI, chatbots can talk with customers to identify their needs and recommend the most appropriate coverages to them. They can even cross-promote products based on the customer’s needs. Then, the customer is turned over to a human adviser to answer any questions and complete enrollment. 3. AI Uses Data to Better Predict and Mitigate Risk Insurers depend on their ability to predict and manage risk. The more information they have access to, the better their ability to assess risk. AI enables the collection of both structured and unstructured data. Besides the insurer’s own data on insureds, structured data includes information collected through sensors in wearable devices and other IoT devices. Unstructured data is collected from public spheres such as social media pages and search engines. This data can then be used to create insights that not only help insurance companies protect their bottom lines but also give them a true competitive edge. Employee benefits is a particularly promising area. AI is now being applied to streamline pre-approval workflow. For instance, before an insurance-company employee replies to a customer, the response can be passed through a smart compliance system that reviews it and makes any necessary adjustments before it goes out. 4. Automating Routine Processes Other processes that are now being automated using RPA include copying and pasting data to spreadsheets, logging into applications, transferring data from one database to another and opening emails and processing them. See also: How to Automate Your Automation   5. Claim Processing AI and RPA are now being used to automate claim processing, especially in property-casualty insurance and employee benefits insurance. The system assigns adjusters, integrates the disparate claim information and facilitates claims payments. For instance, ClearPay is an insurtech product that insurance companies, agents and brokers can use to integrate the settlement process and monitor claim payments in real time. AI and RPA are only beginning to transform how business is done in the insurance industry. We can expect to see burgeoning usage in operations, customer service, risk assessment and mitigation and regulatory compliance.

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