Insurance has always been a data-driven business, from the old waybills recorded on papyrus under the Code of Hammurabi to the charters of the first property insurers after the Great Fire of London. What has changed in today’s insurance world is the speed, volume and variety with which data arrives and accumulates. Insurers determined to become a true data-driven business have realized that nothing less than their future depends on it.

Data modernization has been a top business priority for most insurers for several years. Macroeconomic trends such as rising customer experience expectations, demographic shifts among potential insurance buyers, the disruptive rise of insurtech, and a focus on digital transformation have converged to increase pressure on the insurance sector to improve its data set. To that end, many insurers have invested heavily in new data architectures, models, platforms, and the talent needed to implement and manage modernization efforts. So why does the industry always seem to be lagging behind when it comes to building real data-driven businesses?

Drowning in data
One of the biggest issues that insurers continue to face is the rapid proliferation of data. Every activity in the insurance value chain – marketing, sales, policy and claims management, actuarial and finance – creates data, and lots of it. This is especially true for traditional insurers who have accumulated huge amounts of data spanning decades or even centuries of business. Finding the right data in the right place at the right time, and presenting it in a consumable format, can be a daunting task for many insurer IT divisions. However, the lost opportunity costs of not taking advantage of these untapped data resources far outweigh the effort and expense involved in creating an effective data management program.

As decades of experience in creating and implementing data strategies have demonstrated, the first steps on the path to data modernization can be difficult. For many insurers, this first step may have less to do with the actual data and more to do with identifying the strategic use cases needed to demonstrate the value of a good data management program. Insurers must decide what information is most critical to current and future strategic goals and business operations, even if the data does not exist in their current data stores. This can be difficult for insurers who overstate existing data and processes. Employing structured thinking combined with hands-on experience in data modernization – internal and external – is important to envision a desired future where the strategic use of data supports strategic planning, proactive decision-making, and business processing. effective and efficient. The end result is a roadmap to guide an insurer to market success and profitability.

Turning Data into Opportunity
The whole point of becoming a data-driven business is to ensure that data drives value for an insurer and its key stakeholders. For customers, this value means better product choices and a better customer experience across touchpoints such as marketing, purchasing, complaints and billing. For agents, this value means better product training, better underwriting, and better relationship management. And for the insurer, that value means better customer and agent insights, market and financial forecasts, and strategic and operational performance.

Specifically, data-driven transformation requires an enterprise-level commitment to the priorities, investments, and resources needed for success. It’s an enterprise-focused effort that uses technologies and platforms to create the foundation for data modernization. It is a structured and cohesive effort as opposed to siled solutions and fragmented goals. Insurers who have been successful with their data modernization programs have used an iterative approach that uses proof-of-concept projects to test new ideas and approaches and scale them, if successful.

Insurers transitioning to a data-driven business have created architectures and analytical platforms that leverage large amounts of existing unstructured data. They recognize that new data analytics goldmines will include videos, social media posts, photos, presentations and voice recordings, and that insurers will need to have the tools and talent to transform unstructured data into meaningful information for business decision making. .

The future started yesterday
The race to become a data-driven business has already begun in the insurance industry. Some insurers are leveraging hybrid cloud infrastructures to meet regulatory data requirements while providing increased data storage and analytical processing capacity. Others are creating new data architectures to support the creation of data lakes, which can be used to diversify the data available for analysis and decision-making and support machine learning and AI initiatives.

However, the insurance industry lags behind several other verticals – including finance, retail and manufacturing – in using data to create new market opportunities and meet expectations in ever-changing customers. The industry also has work to do in the areas of data governance and security. As data-driven decision-making increases, insurers must continue to build consumer confidence in their ability to responsibly manage private information. Unfortunately, consumer trust only lasts until the latest data breach. It is therefore essential that insurers and the industry make the necessary investments to secure their data.

Strategy + Execution = Success
Strategy is only as good as execution, and to become a data-driven business, insurers must take it one step at a time. Defining what a data-driven future looks like, in terms of business processes and revenue growth, is a good place to start. Once a vision is established, the insurer can create the data architectures needed to achieve the future state. Then they can start implementing the necessary data infrastructure, including hybrid cloud data stores; analytical tools for internal and external, structured and unstructured data sources; and machine learning and AI platforms to process and present actionable data for informed decision-making.

Of course, this process is the ideal scenario. To succeed, it is important that insurers continue to prioritize investments in data modernization and the talent needed to implement, maintain and scale new data and analytics platforms. Emphasis should be placed on business problem use cases that improve data access and quality capabilities while providing learning opportunities for future data efforts.