How Insurers can use AI to increase profitable growth
![How Insurers can use AI to increase profitable growth Blog Article Key Visual As with many industries, Artificial intelligence (AI) has emerged as a powerful tool to rethink processes, challenge the status quo and transform the entire insurance industry. It provides insurers with the potential to develop highly personalized, efficient and responsive insurance products that align seamlessly with the specific needs and behaviors of policyholders. This technical upheaval closely intertwines with a firm’s ability to achieve profitable growth.](/.imaging/focalpoint/1600x960/dam/jcr:3be4dffb-6016-4726-b175-888661919bfa/gft-key-visual-blog-how-insurers-can-use-ai-to-increase-profitable-growth.webp)
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AI provides insurers with the potential to develop highly personalized, efficient and responsive insurance products that align seamlessly with the specific needs and behaviors of policyholders. This technical upheaval closely intertwines with a firm’s ability to achieve profitable growth.
The 3 levers of profitable growth
GFT sees the rise in AI affect three keys opportunity areas: new products, customer satisfaction and core underwriting. To understand and leverage this intersection of AI and profitable growth, it’s important to explore these three areas and consider how to build your AI strategy to optimize each of them.
3 keys to profitable growth
Profitable growth describes the connection between your organization’s earnings and its scalability.
As we know, not all top-line growth results in immediate profitability. As insurers balance sustainable growth with all-important profitability, GFT suggests focusing on these three key area
1. Creating new products that customers actually want to buy
Changing demographics, consolidation and ever-increasing competition across the insurance space has accelerated over the past five years. This competition places huge time and resource pressures on the traditional innovation process: analyze, design, program, integrate and test.
Your organization’s ability to create innovative and effective products is a direct indicator of success—consumers gravitate towards products that cut through copy-cat thinking and instead provide integrated value that fits with each customer’s unique lifestyle. Such products earn customer loyalty and lead to longer term relationships that insurers can, in turn, leverage to drive improved profitability.
2. Retaining customers and keeping them satisfied
While growing your customer base through new product adoption is critical to profitable growth, retaining existing ones is just as important. Classical methods of surveys and monitoring of consumer behavior are “table stakes” in today’s cut-throat market. Instead, leading insurers have become expert marketers and data miners across wide swaths of data—Including demographic shifts, social media data and buying patterns.
Furthermore, leading insurers have retooled their customer experience with the goal of anticipating needs before they even arise. If executed correctly, this virtuous cycle can lead to happier customers and increased profits for insurers.
3. Performing underwriting to remain competitive
As a core competency of insurance, it’s not an overstatement to claim that effective underwriting could be the single most important driver of both profitability and success for your firm. Unbalanced claim expenses versus premiums can lead to budget deficits, as can uncontrollable occurrences such as natural disasters and other unforeseen events. Clearly, it’s of paramount performance to create a robust, scalable underwriting process that ensures profit by effectively pricing products.
While leading insurance providers have leveraged increased automation to reduce manual tasks and free up expert resources and lower overhead, current conditions spell trouble ahead. For example, Mark Englert from ALM Property Casualty 360 states that “Economists predict that, in most markets, the industry will not be able to generate sufficient returns to cover its cost of capital in 2024 or 2025 due to the rising expense of litigation and economic inflation, which leads to higher claims costs.”
How can Insurers use AI and ML to Improve profitability?
Artificial Intelligence, including Machine Learning (ML) and Generative AI (GenAI) has swept through every industry and technical area—Insurance is no exception. GFT’s research and experience surfaced a number of ways that insurers should consider using the technology specifically to augment profitability improvement efforts, including:
New data-powered insurance products
Effective AI cannot be achieved without effective data management. As insurance firms grapple with data consolidation, quality and lineage, AI tools can accelerate how data is integrated, cleansed, and harmonized.
In addition, new technologies such as Vector Databases can represent multiple data types (i.e., sensor data, words, images, and audio) and allow them to be searched simultaneously. Large Language Models (LLMs) can be leveraged to understand and reason over huge amounts of data, helping insurers to both find patterns in existing data and refine insurance products to specific market segments. Two possible examples of this in action could be:
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Parametric Insurance: This includes policies that pay out a predetermined amount of money upon the occurrence of a specific event, as defined by pre-agreed-upon parameters, such as seismic activity, weather conditions, or financial indices reaching predefined thresholds.
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Usage-based Insurance: This is an auto insurance product where premiums are based on individual driving behavior and usage patterns rather than traditional factors such as age, gender or location.
Hyper-personalized support to drive stickiness
AI brings new possibilities to depth and breadth to the challenges of knowing customers, anticipating their needs and optimizing the Customer Experience (CX). Coupled with next-generation Data Lakes and Data Mesh-approaches and near-infinite storage, the long sought-after 360-degree view of the customer is finally achievable.
We have all seen -fueled customer sentiment analyses in chatbots and other interactive channels. The logical next steps are to further enhance CX to combine internal customer feedback with the rest of the front and back-office data and even external data services and products. The resulting federated data sets can then be used to train smaller LLMs for specific purposes. The end result will provide insurers with highly personalized views of their customer bases, leading to increased Customer Satisfaction (CSAT) scores and increased long-term repeat business. This investment leads to Insurers having increased options for specialization, monetization, and profit possibilities.
AI: the Underwriter’s new best friend
Modern underwriters already use Optical Character Recognition (OCR) and Natural Language Processing (NLP) as routine tools to extract essential information from unstructured data sources and documents. As above, GFT believes that the tsunami of growth in data volumes and the maturation of GenAI and associated technologies will only accelerate the benefits for leading underwriting firms.
Obvious expansions of this include historical claims data and public records. Additionally, specialized LLMs that understand medical history and lifestyle choices will become commonplace and help insurers to accurately predict health risks. Assuming data privacy, opt-in mechanisms and other critical security standards continue to protect consumers, insurers will be able to tailor policies and costs in favorable (but fair) ways.
How to start your AI-powered insurance strategy
With continuous advancements with AI and so many possibilities and options, it is sometimes challenging to know how to get started.
Based on hundreds of AI projects across insurance, financial services and manufacturing, we suggest these initial guardrails:
Get your data management house in order
A robust data management strategy is essential. Insurers must ensure data quality, accessibility and security to extract insights from data sets. This need not be perfect from day one but is a prerequisite if you expect success in specific subject areas. As a recent Gartner article suggests:
““GenAI capabilities for synthetic data and analysis of images and other types of media will help support industry processes throughout the value chain. The use of generative AI over the long term will help transform the insurance value chain, including customer self-service, data science, claims, underwriting and internal operations (IT and product fillings/compliance). ””
Identify use cases before solutions
Instead of tackling enterprise-wide solutions, you should instead look for tangible, bound use cases that your customers have asked for, or ones that you believe to be enables for additional value. And, at the beginning of AI adoption, incremental changes benefit your technical approach, data and measurements. This will pay off handsomely down the line.
Identify your key partnerships
Collaborating with the right set of technology and service providers is critical, as much of the industry is currently in learning mode. While early in the game, find firms (such as GFT) that can accelerate innovation and partner with you to “right size” your efforts and reduce risk.
Consider your core team
Developing and nurturing an internal team to spearhead your AI projects and build expertise is crucial. This core team can act as a hub to collect experiences and growth your firm’s technical memory. The team also assists in reducing confusion and duplication of effort, especially as AI efforts grow in size and business importance.
Do not neglect change management
AI Integration into traditional insurance can result in pushback, fear of reduced job security and other misgivings by internal staff. This cultural shift can be reduced by tying your AI efforts into existing change management mechanisms and management practices. This can actually help transform anxiety about AI into a set of personal and professional growth opportunities.
Visit GFT’s AI.DA marketplace, an ever-growing catalog of AI solutions, templates and thought leadership. There you will see and explore areas in which we’ve expanded our knowledge and experience. While not all explicitly tagged as insurance-centric, many are absolutely applicable to the industry. With a track record of excellence and a reputation for innovation, GFT features both ready-for-market solutions as well as custom systems to meet your digital needs.
Are you ready to continue this conversation? Contact us to discover how GFT can help you build your AI strategy to maximize your insurance business strategy.
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