Data Governance in P&C Insurance for Applied Epic and Vertafore’s AMS360

What is Data Governance in P&C Insurance

You want your Applied Epic or AMS360 to store current, accurate data respecting its business rules.

The challenge isn’t really about specific data quality dimensions. Agency Management Systems handle data integrity well. For many larger brokers the problem lies in throughput and scalability of Data Governance. Your data administrators need efficient ways to handle:

• Periodic and automated cleanup.
• Post M&A integration of data from acquired agencies.
• Data standardization.
• Scalable employee setup and bulk updates.
• Data quality checks.

This practical reality shapes how brokers should approach AMS Data Governance. Focus on common AMS data challenges, relying on tools and processes that help your data team work efficiently at scale.

Remember about the foundation of success in Data Governance – your people!

Data Admins – The Titans Carrying Your Agency On Their Shoulders

Insurance brokers need people who understand both data and broker operations. Forget theoretical governance roles like data stewards, custodians, etc. Roles aren’t really job titles, and remember that often these responsibilities already exist in your organization.

Focus on who actually maintains your Agency Management System’s data, and what they need to succeed.

Various roles deal with data quality, including: data administrators, data analysts, even business systems analysts, data integration specialists, data implementation specialists, Data Conversion specialists/analysts, and so on.

They clean records, enforce standards, and manage system settings. Producers and account managers own the accuracy of their client and policy data.

The work of these people is so demanding that it deserves recognition.

These roles demand deep system knowledge and attention to detail. Your data people often work overnight during conversions or spend weekends fixing carrier hierarchies. They maintain data quality without recognition, keeping your AMS reliable for front-line teams.

What can you do to help them organize their work better?

Essential Elements of AMS Data Governance

Your AMS Data Governance needs clear rules and practices, not an overblown theoretical framework. Let’s examine what actually helps maintain data quality – and what might create unnecessary overhead.

Practical Division of Responsibility

While you may consider to appoint stewards or build a Data Governance council, the main goal is to ensure Data Governance has enough flexibility to be efficient. Focus on clear ownership of critical data and efficient communication between teams. Your data quality depends more on good practices than formal structures.

A formal body of stakeholders and experts may be a good idea to limit siloed decisions about data within the organization. At the same time, it shouldn’t be used to hinder autonomy of individual teams or take arbitrary decisions about data.

Practical Policies

Skip creating hundred-page data governance manuals. They end up as shelf-ware, pulled out only to impress executives or be impractical when problems occur. Your teams need clear, actionable guidelines for common scenarios.

P&C insurance brokers keep their data neatly structured in their AMS. There is absolutely no need to throw time and money on consulting to create an inconvenient top-down protocol..

Keep your rules specific: “Check carrier names and NAIC codes before creating new records” works better than “Maintain optimal data quality standards.”

Build guardrails and rely on business rules validation to prevent errors rather than embrace perfect compliance with manuals.

Working Knowledge Base

Document how your AMS organizes information, but stay practical.

It is very tempting to say that your knowledge base is in your Slack or Teams. Don’t do it.

The problem with keeping knowledge in the messaging system is that when someone tries to find an answer, instead of the latest up-to-date information they get 3 years worth of message history with outdated information, solutions etc. Instead keep all knowledge base in an in-house Confluence or SharePoint – and yes, that’s a lesson learned at a start-up.

Keep that knowledge accessible and current. Your data administrators need clear references when training new team members or handling unusual cases.

Describe exceptions, special records, and ways of prefixing entities. Maybe there is a good reason to keep that DNU (do not use) or keep 2 similar carrier names as separate records.

Common AMS Data Governance Challenges

Insurance brokers face data management hurdles that theoretical frameworks fail to address. Daily operations create constant data pressure while M&A events expose hidden problems under tight deadlines.

Handling Multiple AMS Installations

Mid/large brokers often maintain several AMS installations for practical reasons. A broker might keep AMS360 for one region and Applied Epic for another, converting acquired agencies into matching platforms.

Sometimes brokers do this to deliberately convert Applied Epic data into Applied Epic rather than run a conversion to AMS360. Each system accumulates its own data practices, carrier hierarchies, and operational standards.

This split approach minimizes disruption but demands careful data practices. Your data teams must understand different data models and maintain standards across platforms without forcing artificial uniformity.

Then you will still have to somehow analyze all that as a whole to know where your business is. We’ve actually written an article about approaching analytics and designing your data mart as an insurance broker/agency.

Post-M&A Data Integration

Third party data sources, data integration, system consolidations, M&A and system-to-system Data Conversion. There are so many instances in which your data admin team cannot be proactive until they open some external Pandora’s box of mishandled data, errors, and years of piled data quality issues.

Under these conditions they typically meet with a source of data that relies on completely different data structures, relationships, naming standards, and formats. Trying to fit that into your data environment is a huge endeavor. You may know that ‘Phil Ind Ins’ means ‘Philadelphia Indemnity Insurance Company’, but your system still needs it explicitly mapped to associate bound policies with the proper golden record.

When a mid/large broker acquires an agency, they face practical hurdles:

• Mapping hundreds of carrier records between systems.
• Validating policy data accuracy – true story: a broker acquired an agency, and discovered only at the last moment during the Data Conversion process that the acquired agency used either writing company name with both writing and pay-to or an intermediary company name in both writing and pay-to on a policy level.
• Setting up new employees and permissions.
• Maintaining service during transition (the go live).

Ongoing Data Management

Insurance brokers face constant data challenges M&A events. Daily operations demand efficient ways to handle routine changes that affect multiple records.

A straightforward task like setting up or modifying employee records taxes your data team. Each change requires configuring multiple settings across different screens – roles, flags, permissions, time zones, login parameters. By default, what should take minutes stretches into days of repetitive clicking.

Then there is a more implicit type of work with data. Creating a record is one thing, but there will be cases when your data needs maintenance to stay updated.

Your AMS must reflect market evolution. When Marquette National Life Insurance Company becomes Nassau Life Insurance Company of Texas after multiple mergers, your data team needs to update carrier records, maintain policy relationships, and ensure accurate reporting. This is one of those invisible tasks that can easily get overlooked in day-to-day work. Brokers don’t readily find out about changes in the industry.

Your AMS accumulates inconsistencies over time too. Inevitably, you will see variations of carrier names and regional offices developing different naming practices. Even your past successful post-M&A projects can leave a few mappings or a duplicate company record here and there. These small divergences may multiply over the years until they affect operations.

Your data administrators need tools that match these realities. Native AMS interfaces force them to handle changes record by record, screen by screen. This approach breaks down as organizations grow and change accelerates.

Beyond Perfect Plans

No governance framework prevents all problems. Your data team faces:

• Surprise data quality issues.
• Urgent Data Conversion deadlines.
• Applied Epic and Vertafore AMS360 UI system limitations.
• Resource constraints.

Addressing these challenges requires technical solutions. Yet this is where Data Governance in P&C insurance brokerage tends to fail. There is a gap that is only seemingly about technology.

The Gap in AMS Data Administration

Most data quality issues trace back to a fundamental problem: Agency Management Systems weren’t built for data administrators. Their interfaces focus on producers and account managers who drive direct revenue.

Data teams deal with tools designed for individual record updates, not bulk operations or systematic maintenance.

Think about your data administrator trying to configure twenty new employees. Each record requires clicking through multiple screens to set roles, permissions, and system flags. This manual work creates opportunities for errors while consuming valuable time.

Native Tools in P&C Insurance Fall Short

Why do data administration and Data Governance initiatives fail specifically in P&C insurance? Where’s the common denominator?

Agency Management Systems are not built for your data administrators.

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Their interfaces are not made for scalable work and large throughput.

There, we said it. As with any other type of business-facing system, all the features are oriented at people who make a direct impact on revenue, customer satisfaction, or otherwise deal with critical compliance areas like billing and accounting.

The Cost of Limited Tools

What does it leave your data admins and Data Conversion people with? Well, it’s a workflow that relies on repetitive micro tasks like clicking through the same navigation path over and over again for every single entity they are working on. Your data admins most likely cannot even readily see a full list of entities there are in your system – often having to remember them and look them up.

Post-M&A data migrations are especially painful. Your Data Conversion team utterly deals with vendor portals and reports you may never have heard about, working closely with the vendor’s services team. At first they wait for an acquired AMS database backup restoration, and then get to work in spreadsheets, manually mapping company codes and names.

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Then they may need to set up 400 new employees, which will take weeks.

Data teams work nights and weekends during conversions. Projects drag on because manual processes can’t scale. Quality suffers as teams rush to meet deadlines.

You won’t notice that when your agency is small, doesn’t do any major acquisitions, and maybe adds a dozen new employees or handful of carriers per year. As your scale grows, most likely something will feel off i.e. data teams working slowly, not quite matching the tempo of growth and M&A activity. You may find yourself relying on costly outsourcing companies, being scheduled weeks away by your system’s vendors service team, and wait months for post-merger data integration projects to go live.

In the broader world hardly any vendor cares about a group of geeks – in a positive sense – doing something so obscure but necessary with data.

You don’t win a client for your core business system by telling executives and directors that it has an awesome UI for data management – unless your business model relies on this. Producers, line account managers, customer service roles, and their output makes up the largest surface area of interest.

As brokers grow, inadequate tools create serious problems in Data Governance!

What do we do with this?

Rethinking AMS Data Governance For Applied Epic and Vertafore AMS360

Insurance brokers need tools that enhance their AMS rather than replace it. Skip enterprise data platforms that ignore broker realities. Focus on solutions that respect how AMS platforms actually work.

What you really need are:

1. Tools that work alongside your AMS rather than replacing it. Enhance existing systems instead of creating new data repositories.
2. Interfaces designed for bulk operations and systematic maintenance. Let data teams work efficiently at scale.
3. Processes that maintain data quality without slowing business operations. Balance governance needs with demanding practice on a deadline.

Modern Solutions for AMS Data Management

Traditional data management tools fall short for insurance brokers. Your data teams need solutions that match how AMS platforms actually work.

The Administrative Hub Approach

The tools for Data Governance should enhance your AMS capabilities through bi-directional APIs. This lets them manage data efficiently while respecting your AMS as the system of record.

Good tools streamline common tasks without creating new data repositories. Your administrators should see current AMS data in a clean interface built for bulk operations. Any changes should get validated against business rules, and flow back to your core system, ensuring the data integrity is maintained.

Machine Learning in Practice

ML helps map records between systems during conversions and cleanup. But it must serve practical needs – not as implementing AI for its own sake. Your teams need accurate suggestions for matching carrier names and standardizing records, with clear human oversight of results.

You need humans in the process, because they carry so much context, they just know what goes where and most importantly why. After all, they are able to handle data tasks despite their underwhelming workflow for a reason.

Machine Learning can help them make accurate decisions faster or learn which data points may be missing or need updates.

Balancing Efficiency and Control

Modern tools must respect how brokers work. Project organization helps track conversions and major updates. Audit trails show who changed what and when.

The elements of this approach transforms how data teams work:

• Hours replace days for tasks like mass employee setup.
• Weeks vanish from Data Conversion timelines.
• Quality improves as manual errors decrease or get caught.
• Teams handle more work without expanding.

The right solution costs less than adding headcount while dramatically improving what your existing team can accomplish.

Usability, Workflow, ML with Insurtech, Featuring RecordLinker

RecordLinker tackles these problems head-on, because we realized that data admins are an underserved group of end-users.

Our tool already helps some of the top 50 US P&C insurance brokers.

We provide a specialized, insurance-first platform for AMS Data Governance and handling Data Conversion that works alongside your Agency Management System. Our solution enables your data administrators to handle tasks at scale while maintaining data quality.

RecordLinker is more than tech, because we reframe how Data Admin and Data Conversion teams work. Your team needs a multiplier to their capabilities.

Real Integration That Respects Your Core System

We partner with Applied Systems and Vertafore to provide bi-directional API integration. RecordLinker can sync with your Applied Epic or AMS360 in real-time, letting your data team work with live data while preserving your core system as the source of truth. Changes made in RecordLinker flow back to your AMS seamlessly.

Built for Data Governance Teams

RecordLinker transforms tedious manual work into manageable projects. Data administrators can:

• View and edit multiple records in a single interface.
• Configure entities in bulk rather than one-by-one.
• Organize work around projects and data domains.
• What happens in RecordLinker is treated like a draft until you approve and push changes to your AMS.
• Track progress and maintain audit trails.

Post-M&A Data Migration Support for Brokers

RecordLinker helps Data Conversion teams handle agency acquisitions efficiently. Instead of waiting weeks for database restoration, teams can start mapping data immediately using basic exports – which effectively means saving 8 weeks on just the wait times. Our platform provides:

• ML-powered suggestions for company mapping.
• Integration with vendor conversion tools and compliance with file formats.
• Project management features for conversion tracking.
• Data quality reports for your AMS and acquired source data.
• Library of Data Conversion formats supporting conversions from various types of systems into your Applied Epic or AMS360.

The platform costs less than hiring a single Data Conversion analyst while transforming how your entire team works. It’s a massive lever that increases throughput across your entire existing data team.

Suggested Reading About Data Management and Solutions

Check our recommended reading list with articles and pages discussing insurance’s problems. We want to help you understand why your data teams struggle, and what to do about it.

Taking care of your AMS data quality and post-M&A migrations is a process that requires a shift in thinking. Technology in P&C insurance can both fail and bring benefits – ultimately it’s about how that technology addresses the needs of the end-users and whether it contributes meaningfully to their work.

• Digital Transformation in Insurance
• Data Conversion Roles and Responsibilities in Insurance
• In-House, Outsourcing, and Tech in Data Conversion
• Insurance Agency Acquisitions – AMS Data Migration
• [Solutions] Data Conversion to Applied Epic
• [Solutions] Data Conversion to AMS360
• Simple Data Analytics for Insurance Brokers
• Machine Learning in Entity Resolution with Industry Examples

To learn more about how RecordLinker can help you improve the quality of your data, request a free demo!