WOMEN'S ACCESS TO MORTGAGE LENDING IN NEW JERSEY

Report to New Jersey Citizen Action

May 12, 1997

HMDA DATA ANALYSIS


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

(From
APPENDIX I, Table 29)

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

(From
APPENDIX I, Table 29)

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

Denial Reason

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

(From
APPENDIX I, Table 29)

Table 15 - Summary of Top 50 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

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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