The insurance industry’s historic legacy is a double-edged sword. As an industry with roots that span as far back as the days of Hammurabi’s Code, the insurance world’s stability has both provided security and, at times, resisted necessary change. One of these necessary changes is the adoption of new technologies to structure the processing of the massive increase in data that the modern world brings. As the global insurance ecosystem dives further into digitization, the problem of big data will only persist should carriers choose not to adapt to this new status quo.
However, not all challenges may affect all insurance industry players equally. Large and small carriers, in most cases, have inherently different business processes, capabilities and priorities due to their variance in size. How might these key differences affect their abilities to address the needs of the 21st century with new data-structuring technologies?
Larger carriers’ challenges lie in their scope and age. These organizations have typically existed for longer than their smaller counterparts, meaning they usually rely on relatively older legacy systems and processes. This long-standing dependency on legacy systems creates a greater technical debt, meaning that larger carriers will usually have to play digital “catch up” on a deeper structural level in their business processes.
Additionally, larger carriers typically use multiple platforms for the same business operations (e.g., multiple policy admin systems across different lines of business), as opposed to smaller carriers, which typically use one. Larger carriers face a lack of uniformity in data collection, adding operational efforts (such as extract, transform and load, or ETL) to sync up data formats from different sources.
The challenges smaller carriers face differ, but they are equally pressing. These smaller organizations often have a lower budget allocation for IT modernization. This may result in compromising on the benefits of data structuring in favor of short-term growth. Smaller carriers typically also face more competition in their segment of the economy, so any data restructuring may not establish them as leaders in their field right away. Additionally, once their initial investment is made, smaller carriers must keep up the momentum by staying in the loop of even newer technologies. This fast-paced modernization may cause some strain on their budgets and could be unsustainable.
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Larger carriers’ advantages come from their size and resources. They typically have larger IT budgets, so investments in new technology will not put as much of a financial burden on them. Because of these larger budgets, they also can sustain these investments for the long term. Larger carriers often inherently have more data than smaller carriers due to their many platforms and lines of business, and leveraging such data enables them to reap the benefits of modernization more immediately than their smaller counterparts.
Smaller carriers, on the other hand, have advantages in that they are typically dealing with less data relative to that of larger carriers. The platforms they use for business operations (such as billing and claims), are typically common across lines of business, as opposed to larger carriers that usually have multiple platforms. Due to these reasons, smaller carriers can adopt new technologies to facilitate data structuring with greater ease and flexibility.
Regardless of the unique considerations for differently sized carriers, it is clear that adopting technologies to drive better business function is an overriding business need. The benefits of embracing data structuring are far and wide; it can not only enhance the efficiency of insurance functions but can improve their accuracy. From risk underwriting to pricing algorithms, and target-driven product development to claims fraud detection, all aspects of the insurance value chain can greatly benefit from the enhancement of data organization.
How, then, can carriers of different sizes tackle the challenges of adopting new data structuring technologies? For smaller carriers, a key strategy is tighter planning and allocation of resources. Stakeholder expectations must be set realistically, as data restructuring may not yield immediate results. A well-tested method of alleviating financial strain is taking advantage of open-source or relatively inexpensive technologies to provide a basic framework for adoption. This helps alleviate the risks involved in investing with a limited budget.
For larger carriers, establishing long-term goals for adoption can help provide a solid foundation for implementing new technologies. The level of restructuring required at carriers of such a size is innately more complex and time-consuming than that required of their smaller counterparts. Therefore, aligning objectives and intent across the organization is an essential step in preventing delays and inaccuracies as new technologies are applied.
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Carriers of all sizes would benefit deeply from an investment budget that is flexible and makes room for contingencies. Persistence is the key when it comes to implementing modern technology. Defining clear goals and setting achievable expectations based on available resources will both allow technological investments to be sustainable and build a better foundation for future adoptions.
As the insurance industry becomes more global and digitized each year, the fact still stands. All organizations, large or small, must acquaint themselves with these new methods of enabling standardized data structuring, collection and sharing – or risk getting left behind in the modern digital age.