“Data and analytics are essential for insurance carriers to gain a competitive edge in the market. Data and analytics can help carriers improve their pricing, underwriting, claims, risk management, customer service, and innovation. However, data and analytics are not a one-size-fits-all solution. Carriers need to consider whether to buy or build their own data and analytics capabilities, depending on their needs, resources, and goals.
Buy vs. Build
Buying data and analytics means relying on third-party providers, such as vendors, consultants, or reinsurers, to supply data and analytical tools or services.
Building data and analytics means developing and maintaining in-house data and analytical resources, such as databases, models, algorithms, and platforms.
There are pros and cons for both options.
Buying data and analytics can offer some advantages, such as: (i) Access to a wide range of data sources and analytical methods that may not be available internally; (ii) Cost savings and efficiency gains from outsourcing non-core functions and leveraging economies of scale; (iii) Faster time to market and easier adoption of new technologies and best practices; (iv) Reduced risk of obsolescence or failure of in-house systems.
However, buying data and analytics can also pose some challenges, such as: (i) Loss of control and ownership over data and analytics, which may affect the quality, security, privacy, or compliance of the results; (ii) Dependency on external providers, which may limit the flexibility, customization, or integration of the solutions; (iii) Potential conflicts of interest or misalignment of incentives between the carrier and the provider; (iv) Higher long-term costs or lower returns on investment due to fees or margins charged by the provider.
Building data and analytics can offer some benefits, such as: (i) Full control and ownership over data and analytics, which may enhance the accuracy, reliability, confidentiality, or governance of the results; (ii) Independence from external providers, which may increase the agility, innovation, or differentiation of the solutions; (iii) Alignment of data and analytics with the carrier’s strategy, culture, and values; (iv) Higher long-term value or competitive advantage from creating proprietary assets or capabilities.
However, building data and analytics can also entail some drawbacks, such as: (i) Limited access to external data sources and analytical methods that may be more relevant, diverse, or advanced than internal ones; (ii) Higher upfront costs and resource requirements for developing and maintaining in-house systems; (iii) Slower time to market and harder adoption of new technologies and best practices; (iv) Increased risk of inefficiency or redundancy of in-house systems.
How to Decide
There is no definitive answer to the question of buy vs. build in carrier data analytics. Each carrier needs to evaluate its own situation and objectives, as well as the available options in the market. Some factors that may influence the decision include: (i) The type and scope of the data and analytics needed. For example, some data and analytics may be more generic or standardized (such as demographic or weather data), while others may be more specific or customized (such as claims or underwriting data); (ii) The level of expertise and experience in data and analytics within the carrier. For example, some carriers may have more skilled or qualified staff or leaders in data and analytics than others; (iii) The availability and quality of data and analytics from external providers. For example, some providers may offer more comprehensive or reliable data and analytics than others; (iv) The cost-effectiveness and value proposition of data and analytics from external providers. For example, some providers may charge more reasonable or competitive fees or margins than others; (v) The strategic vision and direction of the carrier. For example, some carriers may have a more aggressive or ambitious growth strategy than others.
Conclusion
Data and analytics are vital for insurance carriers to succeed in the digital age. However, data and analytics are not a magic bullet that can solve all problems. Carriers need to make informed decisions about whether to buy or build their own data and analytics capabilities based on their specific needs, resources, and goals. By doing so, carriers can optimize their performance outcomes while managing their risks effectively.
Data is not just numbers, it is stories waiting to be told. But to master the data, you need to ask the right questions and listen to the answers carefully!”