What is the size of a “typical” tax firm? This question can be answered by analyzing two IRS datasets: the External Customer Data Store (ECDS) and the Preparer Tax Identification Number (PTIN) (IRS, https://tinyurl.com/2z3wxk5h; https://tinyurl.com/aduujnw7).
These give the following picture of the tax preparation industry:
- The volume of filings issued by each firm exhibits a long-tail distribution. The 325 highest volume e-filers submit 46% of all submissions. Intuit e-files the most (20%), followed by H&R Block (10%) and Tax Hawk (5%). Meanwhile, 89% of all e-filers file fewer than 1,000 tax filings each year.
- Electronic filing rejection rates vary significantly. The average rejection rate is 6.5%, but firms focusing on direct-to-consumer tax products have higher rejection rates. Inuit has a 14% rejection rate, and Jackson Hewitt a 61% rejection rate. In contrast, firms specializing in payroll services or complex returns have lower rejection rates, such as 1.6% for ADP or 2.7% for CohnReznick. Firms in the southern United States have higher rejection rates.
- The prevalence of single-preparer firms can be highlighted by linking the PTIN and ECDS datasets. The data can connect 44% of PTIN holders to a specific e-filing firm through unique business names, personal names, or phone numbers. Among linked firms, there are two clear patterns. Firms with only a single matched PTIN have a highly skewed distribution, with 9% submitting under 10 returns, 31% under 50, and 45% under 100. Firms with two or more matched PTIN holders have a more normal distribution of filings per person, averaging between 183 and 322 submissions. This indicates that there are a large number of part-time tax practitioners and single-signer firms in the marketplace.
While there are limitations of the conclusions that can be drawn from this data source, CPA tax preparers can use the below analysis to better understand how their firm compares to its peers. It highlights the importance of small firms and solo practitioners in serving tax clients.
Data Analysis
Firm submission volume.
As shown in Exhibit 1, Intuit submits the most filings (20%), followed by H&R Block (10%), TaxHawk (5%), and ADP-San Dimas (2%). The distribution of tax filings follows a long-tail pattern, with a few large e-filing firms at the “head” and many smaller e-filing firms far down the “tail.”
EXHIBIT 1
Returns by Firm
The long-tail distribution becomes most evident when categorizing e-filing firms based on the number of tax returns electronically filed in 2024. The categories of e-filing firms are large (more than 10,000 e-filed tax returns), medium (between 1,000 and 10,000), small (between 100 and 1,000), and tiny (under 100).
As shown in Exhibit 2, 325 firms accounted for 46% of the total e-filed tax returns. In contrast, tiny e-filing firms, comprising 46% of all e-filing firms, submitted only 2% of the total e-filed tax returns.
EXHIBIT 2
Returns Transmitted, by Firm Size
E-filed tax return filings saw a notable increase in 2024 compared to 2023, though much of this growth is driven by large e-filing firms. Among e-filing firms that submitted returns in both years, large e-filing firms experienced an average growth of 30.2%, medium e-filing firms grew by 3.5%, small e-filing firms by 1.1%, and tiny e-filing firms saw only modest growth of 0.3%.
Rejection rates.
The ECDS file tracks filing rejection rates over time, and while these rates have shown a slight increase over the past three years (i.e., 6.49% in 2022 to 6.55% in 2024), there is considerable variation across e-filing firms, as shown in Exhibit 3. Among the 325 e-filing firms submitting at least 10,000 returns, rejection rates range from 84% to 0.02%.
EXHIBIT 3
Rejection Rates, Selected Companies
These higher rejection rates can often be attributed to the e-filing firm’s specific focus. For example, Administrative Systems, Inc., with the highest rejection rate of 85%, appears to be a payroll service specializing in charitable trusts and funeral homes. Other e-filing firms with elevated rejection rates tend to focus on self-service or simple tax returns. For example, Jackson Hewitt has a rejection rate of 61%, while other self-service firms, such as H&R Block and Intuit, have significantly lower rejection rates of 28% and 14%, respectively.
What causes a tax return to be rejected? According to the Taxpayer’s Advocate’s 2021 annual report to Congress, 38% of returns are rejected for mismatches with the prior year’s Identity Protection Personal Identification Number (PIN) or adjusted gross income (https://tinyurl.com/3raxuhp3). Another 16% of rejections are caused by mismatches with Social Security numbers and duplicate returns.
Linking PTINs to firms.
Linking individual tax preparers to firms is challenging. Some e-filing firms serve as platforms for self-submissions, while others employ teams of licensed professionals to prepare each tax return. In addition, e-filing firms may handle tax returns of varying complexity. To simplify this analysis, larger e-filing firms were excluded, as they are more likely to offer a mix of self-service and professional services.
PTIN holders can be matched to e-filer identities. Among e-filing firms with matched PTIN holders, the median number of tax filings per tax preparer is 160. This figure can be misleading, however, as e-filing firms with only one associated PTIN tend to have a highly skewed long-tail distribution, as shown in Exhibit 4. In contrast, e-filing firms with multiple matched PTIN holders display a more normal distribution.
EXHIBIT 4
Number of Returns per PTIN Holder, by Firm Size
There are limitations to the conclusions that can be drawn from this linking process, but it reinforces a critical insight about the size of firms in the tax industry. Firms with a single matched PTIN have a highly skewed distribution of returns filed each year. In contrast, firms with multiple PTIN holders show a more normal distribution of returns filed. Single PTIN holder firms also average fewer returns per person. Together, this shows that single PTIN firms are different.
One explanation for the different distributions is that single PTIN firms may be solo practitioners operating on a part-time basis. Because 45% of these firms submit 100 or fewer returns per year, they may be operating on a seasonal basis or supplementing another business line with tax work.
The large number of low-volume PTIN signers aligns with this analysis of e-filing firms. There are 127,899 firms with 100–1,000 filings, and another 137,079 firms with under 100 filings. This suggests that 89% of firms registered with the IRS could be considered a small business. Forty-eight percent of PTIN holders matched to a firm are solo practitioners. Even when comparing successfully linked solo practitioners against all PTIN holders, this means that a minimum of 21% operate a solo practice.
Geography.
Geography also impacts e-filing statistics. This analysis excludes e-filers in US territories and foreign countries. It also excludes large firms (such as Intuit), as their e-filer identities serve clients in multiple states. Excluding large e-filing firms yields a more accurate distribution of e-filing firms by state, with an average of 0.37 filings per resident (compared to 0.57 filings per resident when large e-filing firms are included). Exhibit 5 shows rejection rates by state (excluding large e-filers). Southern states tend to have higher rejection rates than those in other regions, even when large e-filers are added back into the data set.
EXHIBIT 5
Rejection Rate, by State
Data Description and Transformation
This article uses two datasets. First, the ECDS has information on organizations submitting e-files. Second, the PTIN dataset has information on people compensated for working on returns. Both datasets required significant data transformations.
ECDS.
The ECDS contains three separate files. The most important is the “master file,” which contains one row for each e-filer identity, totaling 368,412 rows and 166 columns. Some firms have multiple e-filers identities, likely due to different business lines, geographic locations, or other operational aspects.
This analysis consolidated multiple e-filing identities into a single firm record. This included a manual review of all e-filing identities submitting more than 1,000 tax filings, as well as automated searchers for H&R Block and Jackson Hewitt. The term “e-filer” is being used to refer to a single ECDS identity, and the term “firm” is used to denote a consolidated entity comprised of multiple identities.
Notable discrepancies exist between the IRS’s official submission data and the ECDS file. For example, for 2024, the ECDS file reports 246 million e-filed tax submissions, whereas the IRS reported 152 million e-filed tax returns (https://tinyurl.com/4nm4wutv). This difference is likely due to the ECDS file failing to distinguish between original tax returns, amended tax returns, extensions, and other submission types.
In addition, the ECDS file does not distinguish self-prepared e-filed tax returns from those e-filed with the assistance of a tax professional. For example, for 2024, the IRS reports that taxpayers e-filed 152 out of 163 million total tax returns. Of this amount, taxpayers e-filed 86 million with assistance from tax professionals and 66 million through self-preparation (https://tinyurl.com/4nm4wutv). Similarly, a Treasury Inspector General for Tax Administration report on the 2023 filing season found that 72 million e-filed accepted returns were prepared by tax professionals, whereas 62 million were self-prepared (TIGTA, “Final Results of the 2023 Filing Season,” Nov. 9, 2023, Report Number: 2024-400-006, https://tinyurl.com/4922np73).
The other two ECDS files, which include a “partner file” containing information on people, required less pre-processing. De-duplication resulted in 350,102 unique customer IDs and names. Data on the number of partners at each e-filing firm was inconsistent, as the field in the master file did not align with the number of partners listed in the partner file. The last file has information on the primary and secondary contact for each firm, including a phone number.
PTIN.
The second dataset contains information about PTIN holders. Integrating this data with the ECDS dataset proved challenging due to the absence of a shared identifier between the two datasets. The following methodology was used to address this issue:
- 56,219 PTIN records match partner information based on doing business as (DBA) names and first/last names, where both DBA and first/last name are unique in the partner table.
- 138,941 PTIN records match contacts using phone numbers and first/last names, where both phone and first/last name are unique in the contact table. In cases where a person with the same name and phone number appeared across multiple e-filers, the most recent entry was selected, assuming they had transitioned to a new e-filer.
- 278,188 PTIN records match firms using phone numbers, where phone numbers are unique in the firm table, and the firm had submitted returns in 2024.
Since PTINs often match e-filers based on more than one rule, this results in 314,707 matched PTINs and 401,306 unmatched PTINs. Among the organizations that submitted filings in 2024, 190,165 had at least one matching PTIN, while 122,306 had no matching PTIN.
The likelihood of an e-filer having matching PTINs generally correlates with the firm’s size: 52% of tiny e-filing firms, 66% of small e-filing firms, and 77% of medium e-filing firms had at least one matching PTIN. Conversely, only 54% of large e-filing firms had at least one matching PTIN.
A More Complicated Picture
This analysis of the ECDS and PTIN datasets provides a picture of firms in the e-filing tax preparation industry. Large e-filing firms like Intuit and H&R Block submit a massive number of returns, while smaller e-filing firms dominate in number. While only 44% of PTIN holders can be matched to a specific firm, the prevalence part-time tax practitioners and single-signer firms is visible. Among matched firms, 45% submit fewer than 100 filings a year, and 48% are the only PTIN holder for their firm. Rejection rates vary widely, with self-service e-filing firms facing higher rejections. Geographically, the southern United States shows higher rejection rates when compared to other regions.
The hope is that this article provides a more accurate business context for tax firms. News about the industry often focuses on large national firms. This analysis provides a counterpoint, showing that the industry is highly fragmented, with many smaller players. The three largest players—Intuit, H&R Block, and TaxHawk—together only account for a third of e-filing submissions.
This article suggests a need to further study small firms and solo practitioners. The different rejection rates by region suggest that research should investigate how culture and geography affect firms. While the data available somewhat limits more detailed study, this analysis can help CPA firms understand how they fit into the broader tax preparation industry.
