Seneca Savings Mortgage Lending & HMDA Data, 2016

In 2016, Seneca Savings of Baldwinsville, NY reported 260 mortgage applications totaling $40.5 million, up 6% from 2015. The average application was for $155,876, and applicants reported an average income of $99,334. 82% of its applications resulted in an originated loan and 7% were denied. Its largest markets were Syracuse, NY (223), Utica-Rome, NY (7) and Rochester, NY (4) (applications in parentheses).

Mortgage Company & Address Seneca Savings
35 Oswego St.
Baldwinsville, NY 13027
Tel #: available with data download
Federal Regulator * available with data download
Years 2025  2024  2023  2022  2021  2020  2019  2018  2017  2016  2015  2014  2013  2012  2011  
Total Number of Mortgage Applications 260
Total Mortgage Loan Application Amount $40,528,000
Average Mortgage Loan Application Amount $155,876
Highest Mortgage Loan Application Amount $656,000
Average Applicant Income $99,334
Highest Applicant Income $694,000

About this data: figures come from the Home Mortgage Disclosure Act (HMDA) records Seneca Savings filed with the FFIEC and count every application it reported (approved, denied, withdrawn or purchased), not just closed loans. Applications reported at $100 million or more are left out of these totals.

Mortgage Loan Application Totals for Seneca Savings by Metropolitan Area in 2016

Metro Area Total Number of Mortgage Loan Applications Total Dollar Amount of Mortgage Loan Applications Average Mortgage Loan Application Amount Average Applicant Income
Syracuse, NY 223 $ 36,604,000 $ 164,143 $ 102,000
Utica-Rome, NY 7 $ 994,000 $ 142,000 $ 77,000
Rochester, NY 4 $ 341,000 $ 85,250 $ 139,000
Dutchess County-Putnam County, NY 2 $ 75,000 $ 37,500 $ 48,000
Albany-Schenectady-Troy, NY 1 $ 139,000 $ 139,000 $ 85,000
Allentown-Bethlehem-Easton, PA-NJ 1 $ 32,000 $ 32,000 $ 46,000
Binghamton, NY 1 $ 60,000 $ 60,000 $ 52,000
Buffalo-Cheektowaga-Niagara Falls, NY 1 $ 65,000 $ 65,000 $ 60,000
Ithaca, NY 1 $ 179,000 $ 179,000 $ 76,000
Kingston, NY 1 $ 29,000 $ 29,000 $ 56,000
Lancaster, PA 1 $ 44,000 $ 44,000 $ 50,000
Montgomery County-Bucks County-Chester County, PA 1 $ 52,000 $ 52,000 $ 149,000
New York-Jersey City-White Plains, NY-NJ 1 $ 62,000 $ 62,000 $ 58,000
Norwich-New London, CT 1 $ 65,000 $ 65,000 $ 92,000
Salisbury, MD-DE 1 $ 38,000 $ 38,000 $ 180,000
State College, PA 1 $ 42,000 $ 42,000 $ 117,000

Mortgage Loan Application Detail Totals for Seneca Savings in 2016

Loan Purpose

Total Number of Mortgage Applications Total Dollar Amount of Mortgage Loan Applications Average Mortgage Loan Amount Highest Mortgage Loan Amount Average Applicant Income Highest Applicant Income
Home Purchase 197 $30,795,000 $156,000 $656,000 $104,000 $694,000
Refinancing 41 $6,778,000 $165,000 $540,000 $83,000 $251,000
Home Improvement 22 $2,955,000 $134,000 $500,000 $88,000 $194,000

Applicant Race

Total Number of Mortgage Applications Total Dollar Amount of Mortgage Loan Applications Average Mortgage Loan Amount Highest Mortgage Loan Amount Average Applicant Income Highest Applicant Income
White 217 $33,576,000 $154,000 $656,000 $103,000 $607,000
Not applicable 17 $3,620,000 $212,000 $540,000 $0 $0
Not Provided 9 $974,000 $108,000 $280,000 $144,000 $694,000
Asian 8 $951,000 $118,000 $364,000 $126,000 $694,000
Black or African American 5 $928,000 $185,000 $340,000 $185,000 $556,000
Hispanic 4 $479,000 $119,000 $311,000 $82,000 $150,000
Native Hawaiin or Other Pacific Islander 0 $0 $0 $0 $0 $0
American Indian or Alaskan Native 0 $0 $0 $0 $0 $0

Loan Type

Total Number of Mortgage Applications Total Dollar Amount of Mortgage Loan Applications Average Mortgage Loan Amount Highest Mortgage Loan Amount Average Applicant Income Highest Applicant Income
Conventional (any loan other than FHA, VA, FSA, or RHS loans) 260 $40,528,000 $155,000 $656,000 $99,000 $694,000
FHA-insured (Federal Housing Administration) 0 $0 $0 $0 $0 $0
FSA/RHS (Farm Service Agency or Rural Housing Service) 0 $0 $0 $0 $0 $0
VA-guaranteed (Veterans Administration) 0 $0 $0 $0 $0 $0

Outcome

Total Number of Mortgage Applications Total Dollar Amount of Mortgage Loan Applications Average Mortgage Loan Amount Highest Mortgage Loan Amount Average Applicant Income Highest Applicant Income
Loan Originated 214 $35,416,000 $165,000 $656,000 $103,000 $694,000
Application Denied By Financial Institution 19 $2,098,000 $110,000 $540,000 $40,000 $152,000
Loan Purchased By The Institution 13 $595,000 $45,000 $65,000 $96,000 $203,000
Application Approved But Not Accepted 8 $1,522,000 $190,000 $417,000 $159,000 $694,000
Application Withdrawn By Applicant 5 $687,000 $137,000 $334,000 $83,000 $251,000
File Closed For Incompleteness 1 $210,000 $210,000 $210,000 $136,000 $136,000
Preapproval Approved but not Accepted 0 $0 $0 $0 $0 $0
Preapproval Denied by Financial Institution 0 $0 $0 $0 $0 $0

Denial Reason

Total Number of Mortgage Applications Total Dollar Amount of Mortgage Loan Applications Average Mortgage Loan Amount Highest Mortgage Loan Amount Average Applicant Income Highest Applicant Income
Debt-To-Income Ratio 7 $947,000 $135,000 $540,000 $33,000 $61,000
Unverifiable Information 4 $469,000 $117,000 $146,000 $16,000 $52,000
Credit Application Incomplete 3 $182,000 $60,000 $99,000 $47,000 $60,000
Other 3 $188,000 $62,000 $99,000 $48,000 $52,000
Insufficient Cash (Downpayment, Closing Cost) 1 $32,000 $32,000 $32,000 $39,000 $39,000
Credit History 1 $280,000 $280,000 $280,000 $152,000 $152,000
Employment History 0 $0 $0 $0 $0 $0
Mortgage Insurance Denied 0 $0 $0 $0 $0 $0
Collateral 0 $0 $0 $0 $0 $0

Our comprehensive HMDA mortgage statistics provide invaluable insights into Seneca Savings's 2016 lending activity. By analyzing detailed data on mortgage applications, total loan amounts, applicant incomes, loan purposes, and approval rates, industry professionals, researchers, and analysts can gain a clear understanding of this lender's role in the mortgage market.

This in-depth HMDA data allows real estate experts, financial analysts, and policymakers to track lending trends, evaluate borrower demographics, and assess Seneca Savings's mortgage approval patterns. Utilize this powerful dataset to analyze market performance, compare lending practices, and make data-driven decisions in the ever-changing mortgage industry.
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