Using AI to Fix Customer Data Quality in Your AMS

For insurance agencies, poor data quality can lead to significant repercussions, compromising the accuracy of policyholder information and hindering overall operational efficiency. Fortunately, advancements in Artificial Intelligence (AI) have paved the way for innovative systems that can automatically enhance the quality of your customer and policy data. By adopting AI-driven solutions, agencies can significantly enhance the accuracy of policyholder information and streamline their operations to achieve peak performance.

Challenges of Poor Data Quality

Poor quality data presents significant challenges for Account Managers (AMs), making it difficult to execute critical agency tasks such as policy renewals, remarketing, cross-selling, and upselling. Errors in policy information or duplicate client profiles can severely hinder these processes.

Agencies often resort to manual data cleansing to rectify issues in client information, such as names, email addresses, contact numbers, and physical addresses. However, this manual process is time-consuming, prone to human error, and never entirely accurate.

At a deeper level than contact information, when AMs need to verify policies within the agency's AMS, they must individually click on each policy to check and correct details. Handling several hundred policies can take hours; even then, complete accuracy is not guaranteed. To compound this challenge, the existence of multiple data silos across different systems results in inconsistencies in dates, account numbers, and personal information formats, complicating automatic reconciliation.

[Related Topic: I'll Fix My Data Later: Fixing Data After an Agency Merger]

The power and utility of an agency's AMS (Agency Management System) hinges on the quality of the data it processes. When poor data infiltrates the AMS, the agency misses out on the full benefits of the system, and AMs are unable to perform their tasks efficiently such as renewals and cross sells. Agencies need a single source of truth, and that should be their AMS.

Such data issues lead to significant productivity losses and erode confidence in the data that drives the business. Inaccurate records can result in misdirected mailings and ineffective communication with customers, causing delays in claims processing, customer dissatisfaction, and potential damage to the agency’s reputation. Additionally, poor data quality incurs additional costs. Incomplete, missing, or inaccurate client information necessitates further manual checks, delaying decision-making and hindering the efficiency of Account Managers (AMs).

AI-driven solutions offer a transformative approach to these challenges. By automating data cleansing, agencies can save time spent fixing errors and ensure clean data flows through its systems.

DataFix: the Solution to Poor Data Quality

DataFix by Synatic automates the manual data cleansing processes that insurance AM's perform daily. To handle duplicate information, DataFix employs advanced AI technology, including Vector Search, to detect and correct duplicate data. This process involves matching duplicates based on values like customer names, addresses and locations, identifying similarities and differences, and presenting the information in an intuitive graphical format. AMs can easily mark and merge duplicates, ensuring data accuracy.

Synatic’s AI software is also designed to fix errors in AMS databases using customizable parameters defined by the user. With an intuitive, ChatGPT-like prompt interface, DataFix automatically corrects errors, such as invalid email addresses, ensuring your data is accurate and reliable.  

DataFix not only identifies incorrect or missing data, but also provides a comprehensive report with suggested corrections. For example, a report around inactive customers with active policies. AM's simply assess the data in bulk that Synatic has identified automatically, verify the data, and the customers are updated in bulk, in the AMS for a single source of truth. This dramatically reduces the time AM's spend reviewing policies and data. Instead of manually sifting through every policy and customer in the AMS, AMs can now focus solely on the entries that DataFix flags for attention and correct them in bulk. This targeted approach saves countless hours, allowing AMs to work more efficiently and concentrate on higher-value tasks.

[Related Topic: Take the A Out of AI and Just Be Intelligent]

Benefits of DataFix

The primary benefit of DataFix is its ability to allow AM's to focus only on incorrect data, dramatically reducing their workload. Instead of scanning through 10,000 records, AMs might only need to check 100, freeing up valuable time to serve clients and boost productivity.

Beyond data cleaning, DataFix enables agencies to consolidate and distribute clean data across the right systems, ensuring it is presented in a usable format for accurate reporting.  

Clean, reliable data enhances business agility and responsiveness, reducing wasted efforts by AM's and knowledge workers. By minimizing costly errors and omissions, agencies can recover potential revenue losses and reduce E&O insurance costs.

To learn more about how you can leverage the transformative power of DataFix and its built-in AI toolset, contact Synatic today.

Jamie Peers
May 29, 2024
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