Developing an effective data strategy & the use of AI


The Cornerstone of remaining relevant in Insurance [3-5min read]

You can’t move these days without hearing about an AI experiment, and with good reason. Commercial insurers are at a pivotal juncture with the advent of artificial intelligence (AI). But the success of integrating AI into insurance operations hinges on a robust data strategy being in place. Most are selecting specific use cases to learn from rather than critically thinking about a holistic view of how AI will be a strategic lever for competitive edge.

Whichever approach is taken, a data strategy is what will enable success.

TINtech London Market 2024 driving change in the Lloyd's and London market

 1. The Imperative of a Strong Data Strategy

The first step for insurers in adopting AI should be on establishing and executing a comprehensive data strategy. This strategy is the bedrock upon which AI applications are built. Insurers must use a data model and ensure data quality and standardisation, as AI-driven solutions are only as reliable as the data they process. Without a solid data foundation, efforts to implement AI are like building a house on sand.


2. AI's Role in Risk Assessment and Efficiency

Commercial insurers are using AI's potential to transform operations and risk assessment. While AI can significantly enhance efficiency and decision-making, by for example ‘reading’ hundreds of documents at a portfolio level to gain new insights that a human couldn’t, its efficacy still relies on the availability and integrity of the underlying data it is ‘reading’, and again quality is key.


3. Operational Excellence Through Blueprint Two

Blueprint Two, a transformation initiative, is a prime example of how operational excellence can be achieved through data. By focusing on data quality and standardisation, commercial insurers can enable seamless operations across the insurance lifecycle with the ‘reuse’ of data throughout, the much sought after ‘straight through processing’. This approach, supported by AI is enhancing and not replacing human capabilities.


4. Balancing AI with Human Expertise

In claims processing where customer interactions and relationships are key, the synergy between AI and human expertise is crucial. Technology, driven by high-quality data, can take over routine tasks, allowing experts to focus on strategic and value-added activities. Yet again, AI serves as a tool to complement rather than replacing human input.


5. Preparing for a Future Driven by Data and AI

As the insurance industry leans more towards a data-driven model, the skillsets required in the workforce are evolving. Commercial insurers must develop a data-centric culture, where professionals are adept at data and use critical thinking for strategic decision-making. This shift further highlights the importance of a foundational data strategy in preparing for an AI-enhanced future.


So What?

For commercial insurers, the path to leveraging AI effectively is grounded in a comprehensive data strategy. This approach is not about replacing people with technology; it's about achieving operational excellence where AI and human expertise coexist and complement each other. By prioritizing data quality and standardisation, insurers can harness AI to enhance efficiency, improve decision-making, and maintain the human touch that is vital in insurance.

TINtech London Market 2024 driving change in the Lloyd's and London market


Lloyd's of London - Artificial Intelligence and Robots Create New Risks and Opportunities.

Lloyd's of London - Taking Control: Artificial Intelligence and Insurance.

Lloyd's of London - Seizing the Opportunities of a More Data-Driven Market.

NS Insurance - Study Shows Lloyd’s of London Insurance Market Has an Appetite for AI.

Lloyd's of London - Lloyd's Statistics.


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