Datasets:

FinanceRateCalc
/

fha-denial-timeseries-2018-2025

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'state'}) and 3 missing columns ({'lender', 'originated', 'denied'}).

This happened while the csv dataset builder was generating data using

hf://datasets/FinanceRateCalc/fha-denial-timeseries-2018-2025/fha_state_denial_timeseries_2018_2025.csv (at revision 3eb08c507a1dbafc92aba722dffda74beaed44e6), ['hf://datasets/FinanceRateCalc/fha-denial-timeseries-2018-2025@3eb08c507a1dbafc92aba722dffda74beaed44e6/fha_lender_denial_timeseries_2018_2025.csv', 'hf://datasets/FinanceRateCalc/fha-denial-timeseries-2018-2025@3eb08c507a1dbafc92aba722dffda74beaed44e6/fha_state_denial_timeseries_2018_2025.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              year: int64
              state: string
              denial_rate_pct: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 625
              to
              {'year': Value('int64'), 'lender': Value('string'), 'originated': Value('int64'), 'denied': Value('int64'), 'denial_rate_pct': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'state'}) and 3 missing columns ({'lender', 'originated', 'denied'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/FinanceRateCalc/fha-denial-timeseries-2018-2025/fha_state_denial_timeseries_2018_2025.csv (at revision 3eb08c507a1dbafc92aba722dffda74beaed44e6), ['hf://datasets/FinanceRateCalc/fha-denial-timeseries-2018-2025@3eb08c507a1dbafc92aba722dffda74beaed44e6/fha_lender_denial_timeseries_2018_2025.csv', 'hf://datasets/FinanceRateCalc/fha-denial-timeseries-2018-2025@3eb08c507a1dbafc92aba722dffda74beaed44e6/fha_state_denial_timeseries_2018_2025.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

year int64	lender string	originated int64	denied int64	denial_rate_pct float64
2,018	Planet Home	1,019	444	30.35
2,018	loanDepot	30,200	20,120	39.98
2,018	Guild	15,311	1,187	7.19
2,018	Rocket	66,007	35,212	34.79
2,018	NewRez	5,469	5,238	48.92
2,018	UWM	20,704	3,861	15.72
2,018	Mr. Cooper	9,697	5,072	34.34
2,018	Freedom	19,454	18,703	49.02
2,018	CrossCountry	8,746	824	8.61
2,018	Wells Fargo	2,303	2,020	46.73
2,018	PennyMac	3,138	3,510	52.8
2,019	Mr. Cooper	33,390	10,470	23.87
2,019	Freedom	40,677	9,626	19.14
2,019	PennyMac	8,333	7,683	47.97
2,019	UWM	49,197	6,857	12.23
2,019	Guild	18,904	1,281	6.35
2,019	loanDepot	25,472	12,727	33.32
2,019	Planet Home	3,514	891	20.23
2,019	Rocket	93,525	39,496	29.69
2,019	NewRez	8,098	4,371	35.05
2,019	Wells Fargo	2,289	2,018	46.85
2,019	CrossCountry	12,968	760	5.54
2,020	loanDepot	25,814	8,389	24.53
2,020	PennyMac	13,631	9,844	41.93
2,020	Mr. Cooper	41,451	10,447	20.13
2,020	Rocket	83,289	36,256	30.33
2,020	Guild	21,063	1,473	6.54
2,020	CrossCountry	23,396	1,352	5.46
2,020	Wells Fargo	1,503	1,598	51.53
2,020	Freedom	137,000	14,924	9.82
2,020	NewRez	13,840	5,012	26.59
2,020	Planet Home	5,688	1,157	16.9
2,020	UWM	24,042	5,306	18.08
2,021	Wells Fargo	1,272	1,362	51.71
2,021	Freedom	117,575	9,702	7.62
2,021	NewRez	17,147	8,396	32.87
2,021	Mr. Cooper	33,738	8,597	20.31
2,021	UWM	38,516	7,130	15.62
2,021	CrossCountry	25,540	1,793	6.56
2,021	Rocket	127,771	49,320	27.85
2,021	loanDepot	25,844	10,429	28.75
2,021	PennyMac	31,773	10,508	24.85
2,021	Guild	18,543	1,519	7.57
2,021	Planet Home	5,609	1,314	18.98
2,022	Rocket	73,003	34,165	31.88
2,022	Guild	11,221	1,198	9.65
2,022	loanDepot	25,288	14,644	36.67
2,022	Planet Home	2,906	1,127	27.94
2,022	NewRez	5,627	9,044	61.65
2,022	UWM	47,735	9,884	17.15
2,022	PennyMac	12,930	6,386	33.06
2,022	Freedom	17,217	4,978	22.43
2,022	CrossCountry	20,009	1,471	6.85
2,022	Wells Fargo	1,746	2,666	60.43
2,022	Mr. Cooper	11,245	4,232	27.34
2,023	CrossCountry	21,064	1,450	6.44
2,023	Guild	11,986	1,054	8.08
2,023	UWM	64,537	13,529	17.33
2,023	Mr. Cooper	6,120	1,980	24.44
2,023	Planet Home	2,237	895	28.58
2,023	Rocket	68,367	27,894	28.98
2,023	PennyMac	9,251	4,568	33.06
2,023	Freedom	9,384	4,642	33.1
2,023	loanDepot	19,411	12,128	38.45
2,023	NewRez	8,901	7,996	47.32
2,023	Wells Fargo	1,501	1,937	56.34
2,024	CrossCountry	22,994	1,342	5.5
2,024	Guild	17,932	1,375	7.1
2,024	UWM	74,402	18,484	19.9
2,024	Planet Home	3,246	997	23.5
2,024	Freedom	23,149	7,488	24.4
2,024	Mr. Cooper	5,517	1,862	25.2
2,024	PennyMac	15,078	5,466	26.6
2,024	Rocket	66,721	26,429	28.4
2,024	loanDepot	20,996	12,339	37
2,024	NewRez	9,596	8,804	47.8
2,024	Wells Fargo	848	1,197	58.5
2,025	CrossCountry	27,608	1,877	6.37
2,025	Guild	20,919	1,609	7.14
2,025	UWM	87,294	24,022	21.58
2,025	Planet Home	5,823	1,303	18.29
2,025	Freedom	27,636	8,159	22.79
2,025	Mr. Cooper	5,480	2,024	26.97
2,025	PennyMac	24,044	7,444	23.64
2,025	Rocket	65,337	28,619	30.46
2,025	loanDepot	22,700	12,191	34.94
2,025	NewRez	10,547	12,022	53.27
2,025	Wells Fargo	1,295	1,226	48.63
2,018	null	null	null	24.34
2,018	null	null	null	24.81
2,018	null	null	null	25.05
2,018	null	null	null	25.48
2,018	null	null	null	25.56
2,018	null	null	null	25.82
2,018	null	null	null	28.08
2,018	null	null	null	28.09
2,018	null	null	null	31.22
2,018	null	null	null	32.19
2,018	null	null	null	32.29
2,018	null	null	null	32.48

End of preview.

FHA Denial Rates, 2018–2025 — an eight-year time series

Eight consecutive years of federal HMDA filings, for major FHA lenders and for every state. Built for one question: does the lender hierarchy persist, or is it noise?

The finding: it persists

Ranking the major lenders from softest to hardest each year, the order barely moves:

CrossCountry ranks 1st in seven of eight years (2nd in the remaining one)
Guild ranks 2nd in seven of eight years
The hardest doors stay hardest; the softest stay softest, across a rate cycle that included the 2020–21 boom and the 2022–24 tightening

This is why a prior-year record is usable in the current year: the structure is stable. Analysis: https://financeratecalc.com/fha-lending-structure-research.html

Files

fha_lender_denial_timeseries_2018_2025.csv — year × lender (originated, denied, rate)
fha_state_denial_timeseries_2018_2025.csv — year × state (rate)
fha_denial_timeseries_2018_2025.json — both series plus method string

Methodology — important denominator note

This series uses the denominator originated + denied (HMDA actions 1 + 3). FinanceRateCalc's current-year lender, metro and reason datasets use decisioned applications (actions 1, 2, 3), which includes approved-but-not-accepted files. Rates therefore differ slightly between series — for example a lender at 6.37% here appears at 6.3% in the 2025 decisioned set. Neither is wrong; they answer slightly different questions, and mixing them without noting the difference is a common error in published comparisons. Full rules: https://financeratecalc.com/methodology.html

Denial rates partly reflect applicant mix. Historical observations, not predictions and not evidence of wrongdoing.

Citation

Primary data: CFPB HMDA 2018–2025. Derived rates: Yetiş, Z. (2026), FHA Denial Rate Time Series, FinanceRateCalc. https://financeratecalc.com — companion paper: SSRN 7156938.

CC BY 4.0 · Not a lender · No ads · A denial is a data point, not a verdict on the applicant.

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