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Why Automated Data Management Helps Reduce Risk in the Insurance Industry

Brett Hansen highlights how data automation enables rapid analysis and makes business more efficient.

Data management is a critical part of the insurance industry and the very foundation of insurance policies, but many companies are missing out on the benefits of automation. These companies manage high volumes of data using manual methods or cumbersome technology. Because data plays such a critical role in the industry’s function, the collection, analysis, and action process should be optimized and effective. Unfortunately, rarely is this the case.

While insurance customers have largely adopted a data-first approach, insurance providers are lagging. Bain & Company recently wrote on the “digital reckoning” facing insurance companies if they don’t update and adapt to consumers’ expectations of data-driven experiences. However, this same reckoning will apply to insurance companies at the internal level. If they do not update their strategies and implement a modern data management process, they will lose customers, face more significant risks, and be replaced by more innovative insurance providers.

Automated data management will help insurance companies reduce risk, make better decisions, manage higher volumes of data effectively, and reduce costs overall. Here’s why automated data management is the future of the insurance industry.

Data automation enables rapid analysis and makes business more efficient.

To do their jobs, stakeholders in the insurance sector must collect, manage, and act on large data sets. Managing this data is a time-consuming process, especially if it is done manually. Automated data management can provide the same essential information processing without labor hours, freeing workers to do other necessary tasks. In an effort to refine data communication, the American Association of Insurance Services (AAIS) looked to Semarchy xDM to provide a data management, integration, and versioning system that could connect to the organization’s data lake, back-end systems, and other business tools. The automated data system improved the not-for-profit organization’s overall efficiency by 75% and reduced affiliate implementation time by 85%. AAIS leveraged the configurable data management solution to create a fully auditable and governed solution.

In this instance, automated data management had a considerable impact on the overall efficiency of the organization. Others in the insurance industry will benefit similarly by implementing an automated data management system like Semarchy xDM. Efficiency is critical for reducing risk in the insurance industry. It enables stakeholders at insurance companies to set aside the meticulous tasks of data entry and management and focus on assessment and analysis. Insurance companies achieve better results and reduce risks when time is freed up for deeper, better, more thorough analysis. Automation also enables insurance companies to work faster because the data management platform can easily collect and analyze data in a single space. With a data hub like this, stakeholders can take action more quickly.

Automated data management reduces costs.

When we think of risks in insurance, we usually think of personal, property, or liability risks. These are certainly concerns of insurance companies, but there’s one greater risk that has a considerable effect on how the insurance industry functions: the business success of an individual insurance company or organization. Insurance companies cannot function well without properly managing business assets—time, money, resources, data, etc. Mismanagement of data processes and other assets can increase the company’s overall risk. This is why it’s essential to manage costs by prioritizing efficiency with data management. Automation is key. It reduces costs and creates more efficient organizations.

Better data means better risk assessments.

More data is better, no matter the industry. In insurance, however, a higher volume of data means that companies can make better risk assessments, be more informed when underwriting policies, and rapidly act on available data. However, a higher volume of data means that companies will need more efficient means for data management. This is where automation comes into play. Data must be available if companies want to make better risk assessments and overall business decisions. Insurance companies can’t safely underwrite policies or serve customers with the needed experiences without adequate data management.

The insurance industry must embrace data automation as part of the industry’s overall digital transformation. Insurance companies will need more data to serve their customers more effectively, and, as a result, this will require more effort when collecting and analyzing information. Companies will also need flexible, configurable data management tools that allow for matching, consolidation, and quality. This was the case for insurance services provider APRIL. When the company chose Semarchy xDM, they rapidly implemented the platform’s data management technology to improve customer knowledge, streamline data input and management, get better insights about the business, and improve data governance. In addition, because of the platform’s configurable design, APRIL can easily update, change, and modify rules and interfaces when needed.

Automated data management will transform the insurance industry if providers adopt new technologies and implement them in their overall data strategies.

The insurance industry can’t afford to put off automation and stick with manual methods. The industry is changing rapidly, and automation is one critical way companies can stay competitive, reduce risks, and find stability in a volatile market.

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