IBM helps insurance companies implement generative AI-based solutions

IBM works with insurance clients, and research conducted by the IBM Institute for Business Value (IBV) identifies three key imperatives that guide insurer management decisions:

1. digital orchestration
2. Improve core productivity (business and IT)
3. The need for flexible infrastructure

To meet key challenges and drive innovation in their companies, insurers must:

• Deliver digital products to your customers
• Increased efficiency
• Use data more intelligently
• Solving Cyber ​​Security Challenges
• Strive for flexible and stable service.

To achieve the above-mentioned goals, most insurance companies have prioritized digital transformation and IT core modernization using hybrid cloud and multi-cloud infrastructure and platforms. This approach can accelerate speed to market by providing enhanced capabilities for developing innovative products and services, driving business growth, and improving the overall customer experience when interacting with your company.

IBM can help insurance companies insert generative AI into their business processes.

IBM is one of the few companies in the world that can bring together the diverse capabilities needed to completely transform the way insurance is marketed, sold, underwritten, serviced and paid.

IBM focuses on AI across its portfolio of products and services and remains an industry leader in AI-related capabilities.

The IBM® watsonx™ AI and data platform is designed to scale and accelerate the impact of AI with trusted data across your business with its suite of AI assistants.

IBM is working with several insurance companies to identify high-value opportunities for the use of generative AI. The most common insurance use cases include optimizing processes that require processing large documents and large blocks of text or images. These use cases already account for a quarter of today’s AI workloads, and we are seeing a significant shift toward enhancing capabilities through generative AI. These improvements include extracting content and insights or classifying information to support decisions such as underwriting and claims processing. Focus areas where the use of generative AI capabilities can make a big difference to the insurance industry include:

• customer engagement
• digital labor
• Application modernization
• IT Operations
• cyber security

IBM is creating generative AI-based solutions for a variety of use cases, including virtual agents, conversational search, compliance and regulatory processes, claims investigation, and application modernization. Below is a summary of some of the current generative AI implementation initiatives.

customer engagement

Providing insurance coverage requires a lot of paperwork. These documents include insurance product descriptions detailing coverage items and exclusions, policy or contract documents, premium claims, receipts, submitted claims, descriptions of benefits, repair estimates, and vendor invoices. A significant portion of a customer’s interaction with an insurance company consists of inquiries about the terms and conditions of insurance coverage for various products, understanding the amount of an approved claim, reasons for not paying a submitted claim, premium receipts, and transaction status such as claim amount. , policy change requests, etc.

As part of our Generative AI initiative, we review structured and unstructured data (data related to customer queries) within insurance documents and provide tailored recommendations on a product, contract or contract basis, with rapid adjustments. Demonstrate ability to use models. General insurance inquiry. The solution can provide specific answers by accessing underlying policy management and billing data based on a customer’s profile and transaction history. The ability to instantly analyze large amounts of customer data, identify patterns to generate insights, and predict customer needs can increase customer satisfaction.

We are currently developing several use cases including:

• Obtain prior approval for medical procedures
• Health Benefits Management
• Explaining claims decisions and benefits to policyholders
• Billing Summary

Insurance agent/contact center agent support

Insurance companies have widely deployed voice response devices, mobile apps, and online web-based solutions that customers can use for simple inquiries, such as querying outstanding balances or checking claim payment status. However, our current solution set has limited functionality and cannot answer the more complex customer inquiries listed in the Customer Engagement section. Because of this, customers often call insurance agents or insurance company contact centers. Generative AI-based solutions designed for agents can dramatically reduce document retrieval times, summarize information, and enable advisory features, improving productivity from an average of 14% to up to 34% and increasing customer satisfaction. IBM has been implementing traditional AI-based solutions in insurance companies for many years, using products such as IBM watsonx™ Assistant and IBM Watson® Explorer. Now, we are starting to work with several insurance companies to integrate our foundational model and enable rapid reconciliation to enhance our agent support capabilities.

crisis management

To make underwriting decisions regarding property, insurance companies collect a significant amount of external data, including property data provided on insurance applications, records of flood, hurricane, and fire events, and crime statistics for the specific location of the property. Historical data is publicly available from sources such as data.gov, but well-known insurance companies also have access to their own underwriting and claims experience data. Currently, using this data for risk modeling requires manual-intensive efforts and AI capabilities are underutilized.

IBM’s current initiatives include collecting publicly available data related to property insurance underwriting and claims investigation to enhance the underlying models of the IBM® watsonx™ AI and data platform. This approach will be used by our insurance company customers, who will be able to integrate their own proprietary experience data to further improve the model. These models and proprietary data are hosted within a secure IBM Cloud® environment specifically designed to meet industry compliance requirements for hyperscalers. Risk management solutions aim to significantly speed up the risk assessment and decision-making process while improving decision quality.

Code modernization

Many insurance companies with over 50 years of history still rely on systems developed in the 1970s, 1980s, and 1990s, often coded in a mix of Cobol, Assembler, and PL1. Modernizing these systems requires converting legacy code to production-ready Java or other programming languages.

IBM is working with several financial institutions that are using generative AI capabilities to understand the business rules and logic contained in their existing codebases and support their transition to modular systems. The transformation process uses the IBM Component Business Model (for insurance) and the BIAN framework (for banking) to guide the redesign. Generative AI also helps generate test cases and scripts to test modernized code.

Addressing industry concerns related to the use of generative AI

In a study conducted by IBV, business leaders expressed concerns about adopting generative AI. Key concerns include:

• Explainability: 48% of leaders interviewed by IBM believe that decisions made with generative AI are not sufficiently explainable.
• Ethics: 46% are concerned about the safety and ethical aspects of generative AI.
• Bias: 46% believe generative AI will propagate established biases.
• Trust: 42% believe generative AI cannot be trusted.
• Compliance: 57% believe regulatory constraints and compliance are important barriers.

IBM addresses the above challenges with its suite of watsonx platform components: IBM watsonx.ai™ AI Studio, IBM watsonx.data™ data store and IBM watsonx.governance™ toolkit for AI governance. In particular, watsonx.governance provides the ability to monitor and manage the entire AI lifecycle by providing transparency, accountability, lineage, data traceability, and monitoring of model bias and fairness. The end-to-end solution provides insurance company leaders with the capabilities to support accountable, transparent, and explainable AI workflows when using both traditional and generative AI.

As described above, we have identified many high-value opportunities to help insurance companies begin using generative AI for the digital transformation of insurance business processes. Additionally, generative AI technologies can be used to generate new content such as articles (for marketing insurance products), personalized content or emails for customers, and can even create content such as programming code, increasing developer productivity.

IBM works with clients to demonstrate significant productivity gains when using generative AI.

• Talent: Achieve 30%-40% productivity gains
• Customers: Shifting 50% to 70% of all interactions from phone to various digital channels and using generative AI to drive this shift.
• Code Generation: Realize 30% productivity gains in code migration and modernization

Would you like to discuss the topic in more detail? Contact Kishore Ramchandani or Anuj Jain.

To put watsonx generated AI to work, get a free IBM watsonx.ai trial.