Managing the data glut with AI and ML
Across business verticals, massive amounts of data are being generated through connected devices and KYC driven processes. In the wake of this data glut, the already data-centric insurance industry is making use of technologies like machine learning (ML) and artificial intelligence (AI) to process data at high speeds and uncover new insights to improve business operations and address the evolving customer needs. Here are a few areas in which the insurance industry is reaping benefits by making use of AI/ML technologies:
Customer service: According to a report, 74% of customers are happy to receive a computer-generated insurance advice. With customized services becoming common in many segments like banking and finance, the users look forward to similar experiences and services in insurance as well. From reviewing customer profiles to offering personalized policies, AI-driven systems reduce human intervention and offers delightful customer experience.
Claims data: Automating claims processing without human intervention means reducing human errors, saving a lot of time and increasing customer satisfaction. Even chatbots are replacing human-led claims processing by resolving claims and answering simple queries. On the other hand, AI-based analytical applications are highly capable of analyzing claims data and offer critical insights and outliers.
Detect fraudulent activities: Insurance companies have an indispensable responsibility to monitor fraudulent activities closely. Failing could cost millions in terms of incorrectly paid claims. AI algorithms can help in analyzing deep data to offer meaningful information, identify potential patterns of likely fraudulent claims and highlight them for further investigation and corrective measures.
Mitigate risk: Tech innovators in the insurance space have started encouraging their customers by incentivizing the use of wearables, monitoring systems, and connected devices. Data from such devices provide opportunities to gather relevant, real-time data and profile a customer. With AI it becomes easy to cut through this data density and review the risk factors like heart rate and driving behavior and decide the premiums.
But what is equally important is finding the right technology partner, who can help in your enterprise in realizing the full benefits of AI/ML technologies.