University Credit Union Mortgage Lending & HMDA Data, 2009
In 2009, University Credit Union of Miami, FL reported 61 mortgage applications totaling $3.8 million, up 74% from 2008. The average application was for $62,327, and applicants reported an average income of $92,967. 80% of its applications resulted in an originated loan and 0% were denied. Its largest markets were Miami-Miami Beach-Kendall, FL (52), Fort Lauderdale-Pompano Beach-Deerfield Beach, FL (8) and Deltona-Daytona Beach-Ormond Beach, FL (1) (applications in parentheses).
| Mortgage Company & Address | University Credit Union 13241 Sw 136 Street Miami, FL 33186 Tel #: available with data download |
| Federal Regulator | * available with data download |
| Years | 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 |
| Total Number of Mortgage Applications | 61 |
| Total Mortgage Loan Application Amount | $3,802,000 |
| Average Mortgage Loan Application Amount | $62,327 |
| Highest Mortgage Loan Application Amount | $150,000 |
| Average Applicant Income | $92,967 |
| Highest Applicant Income | $295,000 |
About this data: figures come from the Home Mortgage Disclosure Act (HMDA) records University Credit Union filed with the FFIEC and count every application it reported (approved, denied, withdrawn or purchased), not just closed loans.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.
| Metro Area | Total Number of Mortgage Loan Applications | Total Dollar Amount of Mortgage Loan Applications | Average Mortgage Loan Application Amount | Average Applicant Income |
|---|---|---|---|---|
| Miami-Miami Beach-Kendall, FL | 52 | $ 3,299,000 | $ 63,442 | $ 92,000 |
| Fort Lauderdale-Pompano Beach-Deerfield Beach, FL | 8 | $ 353,000 | $ 44,125 | $ 96,000 |
| Deltona-Daytona Beach-Ormond Beach, FL | 1 | $ 150,000 | $ 150,000 | $ 118,000 |
Mortgage Loan Application Detail Totals for University Credit Union in 2009
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 Improvement | 40 | $2,296,000 | $57,000 | $150,000 | $87,000 | $271,000 |
| Refinancing | 14 | $1,159,000 | $82,000 | $150,000 | $89,000 | $222,000 |
| Home Purchase | 7 | $347,000 | $49,000 | $100,000 | $135,000 | $295,000 |
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 |
|---|---|---|---|---|---|---|
| Hispanic | 30 | $1,853,000 | $61,000 | $140,000 | $75,000 | $199,000 |
| White | 15 | $970,000 | $64,000 | $150,000 | $136,000 | $295,000 |
| Black or African American | 7 | $311,000 | $44,000 | $102,000 | $77,000 | $271,000 |
| Asian | 6 | $503,000 | $83,000 | $130,000 | $112,000 | $226,000 |
| Not Provided | 3 | $165,000 | $55,000 | $75,000 | $63,000 | $72,000 |
| American Indian or Alaskan Native | 0 | $0 | $0 | $0 | $0 | $0 |
| Native Hawaiian or Other Pacific Islander | 0 | $0 | $0 | $0 | $0 | $0 |
| Not applicable | 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) | 61 | $3,802,000 | $62,000 | $150,000 | $93,000 | $295,000 |
| 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 | 49 | $3,108,000 | $63,000 | $150,000 | $102,000 | $295,000 |
| Application Withdrawn By Applicant | 9 | $530,000 | $58,000 | $140,000 | $61,000 | $148,000 |
| Application Approved But Not Accepted | 3 | $164,000 | $54,000 | $80,000 | $40,000 | $62,000 |
| Application Denied By Financial Institution | 0 | $0 | $0 | $0 | $0 | $0 |
| File Closed For Incompleteness | 0 | $0 | $0 | $0 | $0 | $0 |
| Loan Purchased By The Institution | 0 | $0 | $0 | $0 | $0 | $0 |
| 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 |
|---|---|---|---|---|---|---|
| Collateral | 0 | $0 | $0 | $0 | $0 | $0 |
| Credit Application Incomplete | 0 | $0 | $0 | $0 | $0 | $0 |
| Credit History | 0 | $0 | $0 | $0 | $0 | $0 |
| Debt-To-Income Ratio | 0 | $0 | $0 | $0 | $0 | $0 |
| Employment History | 0 | $0 | $0 | $0 | $0 | $0 |
| Insufficient Cash (Downpayment, Closing Cost) | 0 | $0 | $0 | $0 | $0 | $0 |
| Mortgage Insurance Denied | 0 | $0 | $0 | $0 | $0 | $0 |
| Other | 0 | $0 | $0 | $0 | $0 | $0 |
| Unverifiable Information | 0 | $0 | $0 | $0 | $0 | $0 |
Our comprehensive HMDA mortgage statistics provide invaluable insights into University Credit Union's 2009 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 University Credit Union'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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