2023 Form 5500 filing — National Technologies, Inc. Section 105 Health Reimbursement Arrangement
Plain-English filing summary
According to public Form 5500 filings published through the U.S. Department of Labor (DOL) Employee Benefits Security Administration (EBSA) via the EFAST2 system, this is the 2023 Form 5500 filing (EFAST2 acknowledgement 20240515164509NAL0034700483002) for National Technologies, Inc. Section 105 Health Reimbursement Arrangement, reported by National Technologies, Inc. under EIN 39-0981304 and plan number 507. It reports 120 participants. Attached schedule details are not reported in the loaded dataset.
Filing snapshot
- EFAST2 acknowledgement
- 20240515164509NAL0034700483002
- Plan sponsor
- National Technologies, Inc.
- EIN
- 39-0981304
- Plan number
- 507
- Location
- Oak Creek, WI
- Received date
- not reported in the loaded dataset
How to read this filing
- This is a single annual Form 5500 filing, identified by its EFAST2 acknowledgement id.
- Schedule chips (Sch H / I / C) show which schedules this filing includes.
- Net assets = total assets minus total liabilities (Schedule H/I).
- Fields a filing did not report are labeled not reported in the loaded dataset — never estimated.
- For the plan's full history, open the plan profile.
Reported financial snapshot
Reported figures as filed, in whole dollars. Only fields the filing reports are shown.
This 2023 filing is loaded, but detailed Schedule H/I financial figures are not present for it in the current loaded dataset. Participant counts and filing identity above are reported; asset and contribution detail comes from the financial schedules where filed.
Frequently asked questions
- What does EFAST2 acknowledgement 20240515164509NAL0034700483002 cover?
- It is the 2023 Form 5500 filing for National Technologies, Inc. Section 105 Health Reimbursement Arrangement, reported by National Technologies, Inc. (EIN 39-0981304).
- Which Form 5500 schedules are attached to this 2023 filing?
- Attached schedule details are not reported in the loaded dataset.