The Problem Every DBA Attorney Knows
A claimant walks into your office. They worked security for a defense contractor in Kabul. Got hurt on the job in 2018. They have no idea who their employer's insurance carrier was, and neither does the employer's HR department, which may no longer exist.
You need to file a claim under the Defense Base Act. But first, you need to identify the carrier. And that means navigating a maze of DOL records, FOIA requests, and fragmented public data that was never designed to be searched this way.
We built ClaimTrove to solve this problem. And we started by ingesting every relevant federal data source we could find.
What Does the Data Actually Show?
ClaimTrove's Afghanistan dataset draws from 18 federal and FOIA sources. The numbers give you a sense of the scale:
- 43,000+ prime contract awards filtered to Afghanistan operations
- 4,300+ subcontract awards linking subs to primes
- 30,000+ OWCP coverage card filings spanning decades of DBA coverage
- 5,000+ OALJ administrative law judge decisions with employer-carrier party pairs
- 29,000+ contractor presence records from FOIA releases covering Afghanistan operations
- 4,900+ DOL case summary records by carrier, employer, and nation
When you cross-reference these sources against each other, patterns emerge. The same carrier names appear again and again, tied to the same employers and contract vehicles. But the relationships shift over time, which is exactly what makes manual research so unreliable.
How Many Carriers Are Actually Active in Afghanistan?
You might assume the DBA market is broad. It is not. Our data shows that a relatively small number of carriers account for the vast majority of DBA coverage in Afghanistan. The top six carriers appear in over 80% of the coverage filings and legal decisions we have indexed.
That concentration sounds like it should make identification easy. It does not. The challenge is that the same employer can be covered by different carriers in different years, and the same carrier name can appear under different corporate entities depending on the policy period. Add in corporate mergers, carrier group structures, and rebranding, and the picture gets complicated fast.
For example, one major carrier family includes at least three separate legal entities that appear in DBA filings. Filing against the wrong entity in the group means filing against the wrong carrier, even though they share a parent company.
Why Date of Injury Changes Everything
Carrier identification is not just about matching an employer to a carrier. It is about matching the employer to the carrier that was on risk at the time of the injury.
Consider a security contractor who worked in Kabul. If the injury occurred in FY2016, the responsible carrier could be completely different from the one on risk in FY2020 for the same employer. Contracts get rebid. Insurance policies lapse and renew with different underwriters. TPAs change hands.
Our data shows that roughly 30% of large defense contractors in Afghanistan changed their DBA carrier at least once between 2009 and 2022. Some changed multiple times. Without knowing the exact date of injury, you could identify the right employer but the wrong carrier.
This is why ClaimTrove weights temporal proximity in its confidence scoring. A coverage filing from 2017 is significantly more relevant to a 2018 injury than one from 2012, even if both name the same employer.
The TPA Trap That Costs Attorneys Time
One of the biggest pitfalls in DBA carrier identification is confusing a Third Party Administrator with the actual insurance carrier. TPAs appear in OALJ decisions and DOL records as if they were the carrier. They are not.
A TPA administers the claim. The carrier underwrites the risk. If you file against the TPA instead of the carrier, you are filing against the wrong entity. And you may not discover the mistake until weeks into the process.
At least three major TPAs appear frequently in Afghanistan-related DBA records. Each one administers claims for multiple carriers, and the TPA-carrier relationships are not static. A TPA that handled claims for one carrier in 2015 may have switched to a different carrier by 2019.
ClaimTrove's engine detects known TPA names and resolves them to the actual carrier that was on risk. These mappings come from verified investigation outcomes and confirmed relationships in our database, not from guesswork.
The Agency Shortcut Most Attorneys Miss
Some carrier identifications are more straightforward than others. Certain federal agencies have historically mandated a single DBA carrier for all their contractors during specific periods. If you know which agency funded the contract, you may be able to narrow down the carrier without searching every database.
The problem is knowing the exact dates these mandates were in effect, whether they applied to the specific contract in question, and what happened when mandates expired. Our research shows that at least three major agencies ran mandatory DBA insurance programs over the past two decades, but the details of when each started, ended, and what happened afterward are not widely known outside a small circle of DBA specialists.
ClaimTrove has mapped these mandatory contract periods and checks them automatically as the first step in every investigation.
What This Means for Your Practice
DBA carrier identification used to take hours of manual research, multiple FOIA requests, and a lot of institutional knowledge. The data existed, but it was scattered across more than a dozen federal databases, none of which were designed to answer the question "who was the carrier?"
With over a million records cross-referenced and searchable in under 30 seconds, ClaimTrove turns that question into a structured investigation with percentage-based confidence scoring and source citations. Every carrier match traces back to a specific filing, legal decision, or contract record.
The data does not lie. But it does require knowing where to look and how to connect the dots across sources that were never meant to talk to each other. Run your first investigation and see what the data says about your case.