How to Transform Your Mountains of Insurance Data into Actionable Insights

Data took center stage as a major buzzword in 2023, and its momentum has seamlessly carried into the current year. Insurance carriers, MGAs, and agencies need to harness the potential of both their proprietary data and third-party data to propel them toward informed and improved decision-making.

Insurance data has always been a rich source of insights but unifying disparate data sources or the continued dependency on manual entry into spreadsheets is going to get insurers nowhere. In the digital age, everything needs to be real-time and almost instantly accessible. If you are not yet using your data to the optimal limit then it is time to find a way to get across these challenges because the quality of your data determines your company’s ability to scale , compete, and thrive.

Insurance Big Data needs Automation

While insurance data is abundant, actual actionable information remains elusive for most insurance companies. Insurers still struggle to unify data but the challenge does not stop here, converting the raw data into actionable insights is a lot of work. Without automated data management, this would be a formidable task.

Data Automation is the strategic approach of utilizing software to automate manual tasks and processes traditionally performed by humans. It does not imply a complete replacement of all data management activities with software but aims to enhance efficiency by automating specific steps in existing data management processes.

Automation of big data in insurance involves automating the extraction, transformation, and loading of data from different sources into one central hub. This daily grind of identifying the newly added data between different connectors and cleaning it into the standardized format can take hours. Yet, this would hardly be a blip in the day’s proceedings when automation comes into play as the process can roll on its own without requiring human intervention.

What Happens in Automated Data Management

Data automation is a game-changer in handling diverse data types, covering structured data like flat files and databases, and unstructured data encompassing images, text, voice, and video. This transformative approach extends its reach across a spectrum of data sources, including internal databases, external databases, cloud-based data, and information from third-party applications, web services, and APIs.

Insurance data automation works across a spectrum of data sources, including internal databases, external databases, cloud-based data, and information from third-party applications, web services, and APIs.

Insurance data automation embraces a variety of cutting-edge technologies, from robotic process automation (RPA) to artificial intelligence (AI), machine learning (ML), and robust data integration tools. The power of AI and ML technologies shines through as they automatically analyze and extract valuable insights from the data.

Automated Data Management Tools Take Over Specific Aspects of Information Handling:

• Data Quality: Enhancing or cleaning up data, such as matching customer records from multiple sources.
• Data Integration: Consolidating disparate datasets into a central location, like merging online and offline sales data to analyze the effectiveness of marketing campaigns.
• Automated Reporting: Utilizing pre-configured reports to monitor key performance indicators in your business.
• Metadata Management: Managing data descriptions, including database schemas and information on where to locate specific data within different databases.
• Master Data Management: Facilitating the flow of accurate information throughout an organization to establish a single version of truth for each dataset. This ensures clean and consistent datasets within various business functions, such as customer records and product catalogs, managed through automation to avoid duplication across multiple systems and teams in your company.

After the data has been collected, validated, and cleansed, insurance companies can then integrate it into their systems and use it for analysis.

The Future of Insurance Insights will Rely on Data Automation

Reproduced with permission

Read the use cases in the original blog published at: https://www.simplesolve.com/blog/automating-insurance-data-and-analytics

Originally published at https://www.simplesolve.com.