What Are AMS Data Conversion Roles About?

Data conversion in insurance focuses on transferring and adapting information between different Agency Management Systems. Rather than being purely technical, these roles are primarily data-driven, concentrating on:

  • data format and structure
  • data quality and accuracy
  • data completeness and integrity
  • mapping between different systems

Who Exactly Does Data Conversion in Insurance?

There are a few job titles that may be involved. The role is not always explicitly about agency management system data conversion. Full scope of responsibilities may vary agency to agency.

  • (AMS) data conversion analyst
  • (AMS) data conversion specialist/associate
  • data migration specialist
  • implementation analyst/specialist
  • business systems analyst
  • systems data analyst
  • quality assurance analyst

Technical competences are appreciated, but often come with time and career progression. Generally, analyst positions come with way more technical requirements.

Let’s see why data conversion even matters.

Why Is Data Conversion a Thing in Insurance?

Insurance agencies and brokers rely heavily on Agency Management Systems (Applied Systems Epic and Vertafore AMS360 etc.) to store critical policy information about:

  • policyholders
  • issuing papers and top-level carriers
  • coverage details
  • premium information
  • policy-related documentation

During mergers and acquisitions, companies often need to consolidate data from different AMS platforms. This process is complex because:

  • AMS systems differ by entity types, relationships, and data structure (for example, in Applied Epic companies are a flat list whereas in Vertafore AMS360 the companies structure is a two-level tree, with mandatory Parent Company)
  • there’s limited standardization across individual agencies (i.e. naming conventions, IDs, etc.)
  • quality of data governance and resulting data accuracy varies broker to broker
  • it involves conversion Excels as well as vendor portals and professional services
  • the most critical part of this process largely happens manually
  • larger brokers may work with two or even a few installations of an AMS, further increasing complexity

Now, whenever a large broker acquires an agency, that M&A process comes with integrating a new part of operations. Typically, the acquiring company wants to consolidate what they acquired into their operations and data. This means that information from the acquired system needs to be moved into the main destination system.

The Unseen Data Heroes of Insurance – Listen to Our Guest Episode

Our founder, Roman Stepanenko, shares insights into challenges of data administrators and data conversion teams in insurance.

Discover the gaps in the process, and the reality of manual workflows of insurance's data people. They are some of the most hard-working and unnoticed 'silent teams'.

Data conversion analysts, business systems analysts, implementation specialists, and data admins keep large brokers going after agency acquisitions.

The problem is that different agencies don’t have a common standard for naming companies in their systems. Companies from source and destination systems overlap only to a degree. When a larger broker wants to move data into their AMS, they need to establish a link between records describing the same issuing paper to accurately reassign policies.

What Does AMS Data Conversion Process Involve in Insurance?

What you typically get is an excel file with 2-4 important columns filled with destination company information, and you need to populate it with IDs of companies from the new system to say that “Phil Indemnity Ins. Co.” in the acquired system really means “Philadelphia Indemnity Insurance Company” in your destination system (and the company codes as well).

This process is absolutely tedious.

This is where data conversion teams come in to make sure data from system A gets adapted to the requirements of system B.

Free Book: Practical Guide to Implementing Entity Resolution

Interested in implementing an in-house record matching solution with your own development team without using any outside vendors or tools?

guide to implementing entity resolution e-book cover

There is hardly any way to automate that task, and never a way to automate everything due to differences, and edge cases (e.g. coding/spelling standards and conventions). Technologically, vendors support technical minimums to enable data conversion at all. Yet the largest systems are mostly prepared to migrate and map data between their own installations and support data conversion for their largest competitor.

In the end, it’s still largely manual. Then if you need to migrate a legacy system or a less known AMS brand, then you are doomed to get a robust conversion Excel template to populate by hand.

What Background Do You Need in AMS Data Conversion?

Data conversion is something that you learn by practice. Many AMS data conversion specialists come from backgrounds related to system vendors.

Many have worked as official product trainers, AMS implementation consultants, professional services specialists dealing with insurance agency/broker data, or even advanced their careers internally within agencies from former account managers, or claim analysts with deeper AMS knowledge.

Is it required to have that kind of background to get into data conversion? Naturally, it’s the best possible card you can have to your advantage. However, more and more often job offers become more open and inviting non-specialized talents!

There are many P&C insurance agencies and brokerages in the USA, and only a few AMS system vendors with the biggest two players: Applied Systems and Vertafore. What does it mean?

This means that the need for data conversion roles exceeds the total number of people with specific AMS platform experience. Hiring for such people is costly and can take months, because they are not immediately available, and well paid for their system-specific know-how.

Let’s look at what data conversion analysts/specialists do.

decor - bridge in constrcution representing what AMS data conversion analysts do

Core Responsibilities For Data Conversion Roles

There are three main areas that related to the process and tools, data quality, as well as project management.

Data Migration and Mapping

  • obtaining data from source systems in various formats
  • format data into standardized templates (e.g. Applied Epic OldNew)
  • mapping companies and entities between systems
  • handle work in vendor portals (e.g. Vertafore SmartMap)
  • carry out post-go-live fixes

Quality Assurance

  • validate data using conversion tools and reports
  • conduct thorough data reviews
  • ensure data integrity throughout the conversion process
  • document and maintain conversion procedures

Data Conversion Project Coordination

  • collaborate with agency leads and stakeholders
  • coordinate with vendor and internal IT teams to finalize, troubleshoot, and optimize conversion processes
  • coordinate with development teams on tooling requirements
  • track conversion issues and milestones
  • enable and facilitate data cleanup initiatives

Requirements and Skills Needed for AMS Data Conversion Jobs

Let’s think about two sets of requirements – one stricter and one leaner when it comes to industry and system-specific requirements.

It’s not uncommon to see associate or entry-level job openings that don’t even require an insurance background – but this certainly comes with a lot of internal training and more senior colleagues coordinating conversion projects.

Leaner Requirements for AMS Data Conversion Teams:

associate, specialist, more open to new talent

  • 2 years minimum of Insurance agency / brokerage experience
  • general hands-on experience with Applied Epic / AMS360
  • proficiency in Microsoft Excel and data entry tasks
  • detail-oriented approach to work
  • good communication skills
  • (nice-to-have) previous experience in data analysis

Strict Requirements for Analysts and Experts in Data Conversion

  • 3-5 years minimum in AMS data conversion / migration projects
  • deep understanding of data structures, relationships, and relationships in Applied Epic / AMS360
  • ability to work with various data formats in Microsoft Excel, Microsoft SQL, Alteryx or other analytics applications
  • advanced proficiency in SQL, ETL tools, and data mapping techniques
  • project management experience and the ability to coordinate cross-functional teams
  • ability to explain technical concepts to non-technical users and senior stakeholders
  • excellent interpersonal skills – both written and oral
  • strong organizational skills and time management
  • (nice-to-have) previous AMS vendor experience
  • (nice-to-have) experience in improving data conversion as a process, knowledge of solutions and automation opportunities

Future Trends in Insurance Data Conversion

The P&C insurance industry grows fast with intense periods of M&A. This is where the demand for data conversion professionals spikes. The next wave of acquisitions is likely to happen in 2025-2026, making data conversion teams’ project pipelines full. We already see RecordLinker’s clients preparing.

The major issue with data conversion projects is the degree to which the work remains manual. With this comes the question whether to overhire for the next M&A spike, whether to turn to outsourcing companies, or increase efficiency of your existing team and look for great insurtechs.

Data conversion has looked largely the same for years – but it doesn’t have to be manual and tedious. Specialized ML can match records from disparate systems to your core system’s golden record set, ensuring accurate mappings. This simplifies and speeds up system data migrations, especially during growth phases, or replatforming efforts. ML can also automate the creation of vendor CSV or Excel conversion files, eliminating the need for manual file building.

RecordLinker uses Machine Learning to normalize records across your data systems

RecordLinker uses Machine Learning to make your data conversion and management painless.

Auto-map your records during system migrations (e.g. writing companies and parents), identify wildly different spelling variants as a single entity, bulk-create missing companies and configure employees in your core system. Standardize entire data marts.

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

Request a Demo

 

Suggested Reading About Data Conversion and Insurtech

Check our recommended reading list for practical insights and easy-to-understand resources to help you establish good data practices in your organization. Proper data management is not simple – learn foundational concepts to discover helpful solutions to your data challenges.