How AI has served as a gamechanger in insuretech
The use of Artificial Intelligence (AI) in the insurance sector has been steadily increasing in recent years. By 2028, the usage of AI in the insurance market is expected to be valued at USD 6.92 billion. It is likely to swell at a compound annual growth rate of 24.08% in the period.
According to a survey conducted by Accenture, 21% of insurance organizations intend to prepare their human resources for AI-based systems that are collaborative, interactive, and explainable. Decision-makers obviously feel that advanced AI will be sophisticated enough to support them.
The era to offer pre-conceived packages of insurance products is way behind. Sophisticated customers are now demanding personalized products that require automation for operational processes. AI facilitates the automation of operational tasks, eliminating fatigue and error associated with humans.
In insuretech, AI is used in several ways:
Risk assessment
To put in shape insurance packages, executives need to analyze copious amounts of data, including social media activity, health records, credit reports, and more to create applicants’ risk profile. AI is capable to conduct the analysis with efficiency with alacrity, enabling insurers to offer customized policies. The costs of these policies are aligned with risk factors, thus doing away with the risks involved.
AI can be used to analyze market data and identify potential risks, such as changes in market conditions or unexpected events. This helps insurers to make informed decisions about investments and manage their portfolios effectively. AI helps insurers address the relationship between complexity and risk variables to assess its impact on the cost.
Using algorithms helps insurers leverage cognitive technologies to anticipate and proactively assess risk. It enables them to gain a competitive advantage and power their organizations’ performance. Cognitive assessments enable tapping of unstructured information, personalizing services, and bringing down subjectivity in decision-making.
Fraud detection
By analyzing patterns in data, AI can identify fraudulent insurance claims. AI algorithms are trained with historical data to suggest possible risks. Insurers can use these suggestions to block or allow certain user actions, such as identity theft, suspicious logins, or fraudulent transactions to avoid fraud and augment profitability. AI systems can analyze thousands of transactions in real-time to uncover activities for fraudsters.
AI algorithms can identify patterns that indicate fraudulent activity. For example, if a user suddenly begins making large transactions, AI can flag it. AI can analyze text data such as emails, chat logs, and social media messages to identify potential fraud. If a user suddenly starts using unusual phrases, AI could indicate fraudulent activity.
AI can also be used to analyze networks of users and transactions to identify potential fraud. Identifying patterns in transactional data helps insurance providers to identify networks of users who might be engaged in fraudulent activity.
Customer service
AI-powered chatbots and virtual assistants can work with customers round-the-clock. This gives businesses the ability to handle a large number of calls without involving human agents. Even when human agents are involved, the quality of interaction increases. At a time when customer loyalties are fading, businesses can use AI to tide over the problem. Moreover, this helps businesses to optimize their resources and reduce costs.
In the past few years, as the circumstances have changed and technology became advanced, customer expectations have changed as well. Insurers need to adhere to altering customer needs and expectations. Today, customers expect an immediate reply to their questions. They are well-versed with chatbots and know how to chat with them efficiently.
An efficient way for companies to serve insurance seekers better is to voice AI. Rather than having an insurance agent get this information from new customers over the phone and manually feed it into the system, voice AI can accumulate the information, plug it into the pricing algorithm, and generate a precise quote. The result is much faster service for customers.
Underwriting
AI infuses better visibility into the underwriting process, identifying and eliminating any potential disparities related to age, race, gender, ethnicity, or other variables. This helps put in place a more equitable system sans conscious or unconscious biases. Moreover, it makes insurance underwriting transparent, allowing insurers to track data points and verify the process of decision-making. AI helps insurers to ensure their underwriting processes adhere to industry standards.
AI can be used to customize insurance offers based on a borrower’s individual risk profile and financial history. By tailoring insurance offers to individual requirements, insurers possible risks to them. The application of AI helps make real-time decisions based on real-time data, such as bank account activity or specific habits.
Advanced AI enables insurers to quickly respond to changing market conditions and optimize their process accordingly. The usage of AI in underwriting is transforming the insurance industry by making the process more accurate, efficient, and personalized.
Claims processing
Enabling automatic processing of claims with less probability of fraud, AI enhances speed. On the other hand, claims with higher probability are routed to human investigators for review. AI can recommend issues to focus on. When a claim is denied, AI systems can provide reason codes for the denial. When customers know the reasons behind the denials, they are able to fix the issues and re-file the claim for reprocessing.
AI can identify key risk indicators that human processors might miss in manual processing, streamlining the process. Algorithms can be used to analyze claims data and assign them to the appropriate adjuster based on factors such as severity, complexity, and adjuster expertise. This reduces the time it takes to process claims and ensures that they are handled by the most qualified adjuster.
Thanks to AI, images and videos of damaged property or accident scenes can be analyzed to estimate the cost of repairs and assess liability. This enables insurers to process claims more quickly and accurately.
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