Statewide Denials by Gender
Table 12 summarizes statewide and top 50 denial data:
Table 12 - Summary of Statewide and Top 50 Denial Data|
All Origs |
Female Denials |
% of All Fem Apps |
% of All Apps |
Male Denials |
% of All Mal Apps |
% of All Apps |
Fem:Mal Ratio of Denials |
|
|
Statewide |
91,065 |
2,188 |
9.9% |
2.0% |
7,067 |
7.9% |
6.3% |
1.26 |
|
TOP 50 |
33,586 |
769 |
9.6% |
1.9% |
2,470 |
7.6% |
6.1% |
1.26 |
State and Top 50 male and female denial levels, and the corresponding female-to-male application denial ratios, are consistent.
Women appear to be denied more often than their male cohorts, both in the state and among the top 50 institutions. Figure 5 illustrates the wide variation in the female-to-male denial ratio among individual lenders. Again, some of this may be attributed to the size of the data set: only one lender (First Fidelity) in the top 50 institutions denied over 500 applications; only 10 denied over 100 applications. On average, institutions in the top 50 denied only 64 total applications.
Still, the statewide and top 50 average denial ratios (1.26) do indicate that female applicants are more likely to be denied than their male counterparts. This merits further investigation. There are a number of medium and larger institutions (originated over 400 loans) at which women were more than 25% more likely to be denied loans:
Table 13 - Medium and Large Lenders with Denial Ratios above the Statewide Mean|
Institution Name |
All Origs |
All Denials |
Female Denials |
% of All Fem Apps |
% of All Apps |
Male Denials |
% of All Mal Apps |
% of All Apps |
F:M Ratio of Denials |
|
Columbia Savings Bank, SLA |
550 |
22 |
7 |
6.4% |
1.2% |
15 |
3.1% |
2.5% |
2.08 |
|
Hudson City Savings Bank |
2,157 |
82 |
19 |
5.1% |
0.8% |
63 |
3.0% |
2.6% |
1.68 |
|
Sovereign Bank, F.S.B. |
899 |
128 |
32 |
15.0% |
2.8% |
96 |
10.3% |
8.4% |
1.46 |
|
PNC Mortgage Corp. Of America |
2,968 |
170 |
46 |
6.3% |
1.3% |
124 |
4.4% |
3.5% |
1.44 |
|
United Jersey Bank |
2,051 |
187 |
60 |
10.0% |
2.5% |
127 |
7.1% |
5.3% |
1.42 |
|
Summit Bank |
2,334 |
106 |
20 |
5.3% |
0.8% |
86 |
3.9% |
3.3% |
1.35 |
|
First Fidelity Bank, NA |
2,621 |
541 |
151 |
18.8% |
4.4% |
390 |
14.8% |
11.4% |
1.27 |
At first glance, it may be apparent to suggest that high denial ratios might be related to unfair underwriting standards, but this is not necessarily the case. There are a number of competing explanations. To start, only First Fidelity denied over 100 female applicants—for all of the institutions, the data set is small. With so few observations, it is difficult to correlate these ratios to institution-wide underwriting standards. Application and origination data are more appropriate measures. None of these institutions fall more than .03 below the average female-to-male origination ratio—they are making loans to women.
First Fidelity Bank NA and United Jersey Bank have high female-to-male application ratios (female-to-male application ratio greater than .29) and high female-to-male denial ratios. Figure 5 shows the distributional data. These institutions are attracting more female applicants, and may be receiving fewer suitable applications as a result. However, Summit and Hudson City Savings attract a rate of female applicants (female-to-male application ratio below .2) lower than their industry counterparts and reject these applicants at a higher proportion—their performance should be tracked over more than one year to substantiate any conclusions regarding underwriting standards. (See APPENDIX I, Table 29 for tabular data).
Figure 4 - Female-to-Male Denial Ratios

It is difficult to utilize the "denial reason" variable to shed light on denials because lenders are not required to list a denial reason, and may list up to three.
Table 14 and Table 15 detail statewide and top 50 denial reason data:
Table 14 - Summary of Statewide Denial Reason Data|
Denial Reason |
All Denials |
All Female Denials |
% of Fem Denials |
All Male Denials |
% of Male Denials |
F:M Denial Ratio |
| Mortgage Insurance Denied |
109 |
34 |
1.7% |
75 |
1.2% |
1.42 |
|
Unverifiable Information |
268 |
68 |
3.3% |
200 |
3.1% |
1.07 |
|
Debt-to-Income Ratio |
2077 |
525 |
25.8% |
1552 |
24.3% |
1.06 |
|
Credit History |
1913 |
482 |
23.7% |
1431 |
22.4% |
1.06 |
|
Insufficient Cash |
728 |
183 |
9.0% |
545 |
8.5% |
1.05 |
|
Collateral |
757 |
184 |
9.1% |
573 |
9.0% |
1.01 |
|
Employment History |
438 |
103 |
5.1% |
335 |
5.3% |
0.96 |
|
Credit App. Incomplete |
412 |
89 |
4.4% |
323 |
5.1% |
0.86 |
|
Other |
1706 |
364 |
17.9% |
1342 |
21.0% |
0.85 |
|
Denial Reason |
All Denials |
All Female Denials |
% of Fem Denials |
All Male Denials |
% of Male Denials |
F:M Denial Ratio |
|
Mortgage Insurance Denied |
61 |
22 |
2.4% |
39 |
1.3% |
1.79 |
|
Credit History |
810 |
219 |
23.9% |
591 |
20.3% |
1.18 |
|
Insufficient Cash |
374 |
97 |
10.6% |
277 |
9.5% |
1.11 |
|
Employment History |
226 |
58 |
6.3% |
168 |
5.8% |
1.10 |
|
Debt to Income Ratio |
1084 |
249 |
27.2% |
835 |
28.6% |
0.95 |
|
Collateral |
334 |
75 |
8.2% |
259 |
8.9% |
0.92 |
|
Unverifiable Information |
89 |
19 |
2.1% |
70 |
2.4% |
0.86 |
|
Other |
658 |
138 |
15.0% |
520 |
17.8% |
0.84 |
|
Credit App. Incomplete |
197 |
40 |
4.4% |
157 |
5.4% |
0.81 |
(From APPENDIX I, Table 29)
For both women and men, the top three reasons for denial were debt-to-income ratio, credit history, and "other". This was true for the state and the top 50.
For both the statewide totals and the top 50 institutions women were somewhat less likely than their male counterparts to be denied because of an incomplete application or for "other" reasons.
The most noteworthy statistic in the denial reason data is the female-to-male denial reason ratio due to the denial of private mortgage insurance. The statewide "mortgage insurance denied" female-to-male denial reason ratio is 1.42 . The contrast is more pronounced among the top fifty lenders; the female-to-male denial ratio is 1.79. Still, the total numbers are small—only 34 women and 72 men were denied private mortgage insurance statewide.
Because of the erratic reporting of denial reason, it is difficult to use this variable to "hone in" on the behavior of the outliers with overall high female-to-male denial ratios (see Table 13). Five of the seven institutions in that group report more denial reasons than applications denied; two of the five do not uniformly report denial reason. Institutional anomalies among the various denial reasons probably reflect reporting procedures and not lending practices.
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