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Taking on Agency’s Dirty Data

Expanding an insurance agency's portfolio can take various forms, one of them being the acquisition of another agency's book of business. While purchasing an entire book presents an enticing opportunity to rapidly increase market share, it also comes with its own set of hurdles, the most challenging among them being the integration of disparate and often messy data.

In the relentless pursuit of revenue and market share expansion, agencies face the daunting reality that conventional strategies, such as increasing every insured client's premium or pushing producers to close more deals may fall short in achieving substantial growth.  

By streamlining processes and leveraging advanced technologies, such as automated data cleansing and deduplication, Synatic empowers agencies to unlock the true potential of their acquisitions. This ensures not only smoother integration but also maximized returns on investment and sustained growth in an increasingly competitive landscape.


The Complexities of Data Integration

One of the most significant hurdles agencies face when expanding their market share is the integration of data from acquired books of business. Acquiring another agency's portfolio may seem like a straightforward strategy, but it comes with its own set of challenges, particularly when it comes to data quality management.

The burden of ensuring clean data in an agency's Agency Management System (AMS) introduces a significant overhead. The purchasing agency must allocate resources to double-check the accuracy of the received information, diverting valuable time and manpower away from core operational tasks. Consequently, overall agency productivity takes a hit, hindering the efficient execution of critical business processes.

For instance, consider when an agency opts to acquire another agency's commercial lines policies. While the prospect of acquiring a ready-made portfolio is enticing, it also means inheriting a vast amount of data, much of which may be outdated, inaccurate, or filled with duplicate records. This "dirty data" presents a significant obstacle, requiring meticulous cleansing and validation before it can be effectively integrated into the acquiring agency's systems.


[Related Topic: Managing Commission Agreements as an Agency Grows]


The Manual Burden of Data Cleansing

The process of cleaning and validating acquired data is often labor-intensive and time-consuming. Manual intervention is typically required, with teams painstakingly reviewing each policy to correct errors, reconcile discrepancies, and remove duplicates. This can be a daunting task, particularly when dealing with thousands of policies, and it may take months to complete.

Moreover, the integration of newly acquired policies into the acquiring agency's AMS poses its own set of challenges. Even after cleansing, there's a risk of residual errors and duplicate data creeping into the system. This not only undermines the integrity of the acquiring agency’s AMS, but also creates downstream effects that can adversely impact operations and client satisfaction.

The presence of dirty data significantly impacts profitability by complicating the accurate evaluation of acquired portfolios. For example, if an agency buys 1000 policies and finds that 10% are expired or duplicated, determining the true profitability of the acquisition becomes challenging. Additionally, the need for more comprehensive data cleansing forces the acquiring agency to allocate more resources to the data cleansing process which decreases the profitability of the purchase.

With an estimated 90% of agency staff time devoted to cleaning up inherited datpost-acquisition, agencies find themselves mired in tedious and labor-intensive data cleansing tasks. This not only detracts from more value-added activities but also prolongs the timeline for realizing the full potential of the acquisition, impeding agility and responsiveness in a competitive market landscape.


[Related Topics: Solving Data Quality Challenges For the Insurance Industry]


Synatic’s DataFix Solution

DataFix By Synatic offers an all-in-one data quality management solution designed to alleviate the burdens associated with dirty data in insurance agencies. Specializing in identifying, matching, and consolidating client, contact, and policy information, DataFix excels at deduplicating data to provide a single, accurate, clean record of truth, thereby preventing future duplicate accounts and errors from infiltrating an agency's AMS.

The DataFix solution streamlines and simplifies the data cleansing process, enabling agents to spend less time grappling with data quality issues and more time serving clients and maximizing productivity. By automating data cleansing tasks, DataFix empowers agencies to maintain an accurate and duplicate-free AMS year-round, ensuring that they always operate on the most precise set of data available. Instead of dedicating months or even years to manual data cleanup, agencies can now accomplish the task in a matter of days, accelerating the timeline for realizing the profitability of a book of business acquisition.

By swiftly identifying and rectifying errors and duplicates in acquired data sets, DataFix ensures that agencies pay the correct amount for the purchased book of business, thereby optimizing acquisition costs and enhancing returns on investment (ROI). Simultaneously, during the absorption of new policies, DataFix maintains the integrity of the agency's AMS by preventing the influx of erroneous or duplicate data. This proactive approach to data management safeguards operational efficiency and enhances client satisfaction, ensuring that the AMS remains clean and free from data discrepancies.

If you want to learn more about how Synatic can help you streamline your data quality management processes and unlock the full potential of your data, Contact Synatic today.

Jamie Peers
March 19, 2024
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