Payday Lenders and the Military: A Study of Hampton Roads, Virginia
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1 Payday Lenders and the Military: A Study of Hampton Roads, Virginia Karen J. Hastings Advisor: Gregory Thomas Pennsylvania State University
2 Introduction Payday Lenders have long been identified as targeting military populations Area of concern to leadership due to security risks Hampton Roads has unique military and civilian makeup, making it an ideal area to study Large Military Population: Army, Navy, Air Force, and Coast Guard (arguably the most militarized region in the US) Varied Civilian Population: income, rural/urban, ethnic groups
3 Background Payday Lenders charge extremely high interest rates and have historically preyed on junior service members 2005 Graves and Peterson Predatory Lending and the Military: The Law and Geography of Payday Loans in Military Towns Looked at 20 states, 109 military installations, and 15,000 payday lenders Found greater concentrations of payday lenders per capita near military installations
4 Federal & State Measures Congress passes Military Lending Act in 2006 Caps interest rate at 36% Requires rights disclosure Prohibits arbitration Can t waive Service member s Civil Relief Act (2015) Service Response Varies by Service Virginia (2009) Restricted loans to one at a time per borrower Established tracking database to determine eligibility Created mandatory longer repayment times Capped interest rate at 36% Limited fees to 20% of loan May not make loans to military members, spouses or dependents $1,000 fine per violation 29.41% decrease in Payday Lenders in 2009
5 Hampton Roads
6 Goals and Objectives Determine if numbers of payday lenders have decreased since 2005 Determine if Military has continued to be a target
7 Methodology
8 Methodology: Phase I Obtained Data Background data US Census Bureau TIGER US Geological Survey ESRI ArcGIS Online Payday Lenders/Banks American Factfinder (historical numbers) Virginia State Corporation Commission Geocode FDIC
9 Methodology: Phase II Compared Raw Counts Compare historical numbers and current numbers of payday lenders and banks Accomplished by ZIP code & county Overlay 3, 6, 9 mile buffers from military installations Why? Payday lending industry wants locations w/in 3 miles of the populations they serve Counts of payday lenders, people, and banks in the zones
10 Raw count county result 2005 County/City Number Banks Number PD Chesapeake Franklin 15 2 Gloucester 15 2 Hampton Isle of Wight 6 4 James City 20 0 Newport News Norfolk Poquoson 1 1 Portsmouth Suffolk 15 5 Surry 2 0 Virginia Beach Williamsburg 14 1 York Miles 6 Miles 9 Miles Banks PayDay Lenders County/City Number Banks Change Number PD Change Chesapeake Franklin Gloucester Hampton Isle of Wight James City Newport News Norfolk Poquoson Portsmouth Suffolk Surry Virginia Beach Williamsburg York % -74% Source Data: FDIC, U.S. Census Bureau 2005 Business Pattern Survey, and Virginia State Corporation Commission
11 Phase II: Complete Hot Spot Analysis Aggregated current point data by census block group & ZIP code ZIP Code Analysis Inconclusive, created a fish net instead Identified statistically significant clusters of high and low values of payday lenders Overlaid 3, 6, 9 mile buffers from military installations
12 Fish Net Hot Spot Results PayDay Lenders Banks Hot Spot Analysis Gi_Bin Cold Spot - 99% Confidence Cold Spot - 95% Confidence Cold Spot - 90% Confidence Not Significant Hot Spot - 90% Confidence Hot Spot - 95% Confidence Hot Spot - 99% Confidence
13 Census Block Group Hot Spot Results PayDay Lenders Banks Census Blocks Hot Spots Gi_Bin Cold Spot - 99% Confidence Cold Spot - 95% Confidence Cold Spot - 90% Confidence Not Significant Hot Spot - 90% Confidence Hot Spot - 95% Confidence Hot Spot - 99% Confidence
14 Census Block Group Hot Spot Results PayDay Lenders Banks Census Blocks Hot Spots Gi_Bin Cold Spot - 99% Confidence Cold Spot - 95% Confidence Cold Spot - 90% Confidence Not Significant Hot Spot - 90% Confidence Hot Spot - 95% Confidence Hot Spot - 99% Confidence
15 Phase II: Complete Anselin Local Moran s I Analysis Aggregated current point data by census block group & ZIP code Identified any spatial clusters of features with high or low values Only tool that identified statistically significant outliers Overlay 3, 6, 9 mile buffers from military installations
16 ZIP Anselin Local Moran s I Results PayDay Lenders Banks Not Significant High-High Cluster High-Low Outlier Low-High Outlier Low-Low Cluster ZIP selection
17 Census Block Anselin Moran s I Results PayDay Lenders Banks Not Significant High-High Cluster High-Low Outlier Low-High Outlier Low-Low Cluster
18 Census Block Anselin Moran s I Norfolk PayDay Lenders Banks Not Significant High-High Cluster High-Low Outlier Low-High Outlier Low-Low Cluster
19 Recreate Graves and Peterson Study Calculate Statewide Average of Payday Lenders Per 100K people Enables prediction of payday lenders per unit (county or ZIP code) Allows comparison of predicted numbers vs. actual numbers in any given area Data presented by ZIP Codes and Counties Rank Payday Lenders Rank Payday Lenders Per Capita
20 Recreate Graves and Peterson Study Calculate Location Quotient ZIP Code LQ = X X+Y x 100} + (X Y) County LQ = X Y x 100 LQ= Location Quotient, X and Y = Banks and Payday Lenders * Not standard LQ formula but ones developed by Graves and Peterson
21 Recreate Graves and Peterson Study Calculated Composite Index Average of Rank of Payday Lenders, Payday Lenders per Capita Rank, and Location Quotient for each county and ZIP code This creates a method for showing proximity of payday lenders to bases with a single number Created 3, 6, 9 mile buffer zones around military installations Ranked results by County and ZIP code
22 Results by County Composite Nearest Base County/City Pop Banks PD Lenders PD/100K Pop Exp PD LQ Rank LQ Rank PD Rank PC Sum of Ranks Rank Previous Statewide Rank Multiple Sites Norfolk 242, Multiple Sites Portsmouth 95, Ft. Eustis, Newport Langely AFB News 180, Suffolk 84, Langley AFB Hampton 167, Franklin 56, Isle of Wight 35, Multiple Sites Chesapeake 222, Gloucester 36, NAS Oceania, Virginia Ft Story, Others Beach 437, Cp Peary James City 67, Langley AFB Poquoson 12, Surry 7, Cp Peary Williamsburg 14, Multiple Sites York 64,
23 Top Ten Results by ZIP Code Nearby Base ZIP Town or City Chesap Payday Lenders Pop Exp PD Banks PD/100K LQ Rank PD Rank PC Rank LQ Sum of Ranks Composite Rank Previous Statewide Rank eake 3 22, Naval Base Amphibious Base Little Creek Norfolk 4 20, outh 3 25, Portsm 3 9 Multiple Portsm outh 1 11, Norfolk 2 23, Naval Base Amphibious Base Little Creek Norfolk 3 28, Newpor t News/H ampton 2 13, Norfolk 2 29, Franklin City 1 13, Portsm outh 1 14,
24 Overall Findings: Is This Still True?
25 Sources 10 VAC-200. Payday Lending (Final Regulation). The Virginia Register, 1 June Web. 15 November ArcGIS Online. USA Counties. Esri, TomTom, U.S. Department of Commerce, U.S. Census Bureau. 28 November ArcGIS Online. World Ocean Base. Esri, GEBCO, NOAA, DeLorme, HERE and other contributors. 28 November ArcGIS Online. National Geographic. National Geographic, ESRI, DeLormre, HERE, UNEP-WCMC, USGS, NASA, ESA, METI, NRCAN, GEBCO, NOAA, increment P. Corp. 27 March Department of Defense Issues Final Military Lending Act Rule Web. 11 October U.S. Department of Defense Press Release No: NR : 21 July, Graves, Steven M. and Peterson, Christopher L. Predatory Lending and the Military: The Law and Geography of Payday Loans in Military Towns. Ohio State Law Journal vol. 66, no. 4 (2005): Web. 11 October Institution Directory. Federal Deposit Insurance Corporation. Web. 15 May Notice to Virginia Payday Loan Customers. Commonwealth of Virginia State Corporation Commission. Web. 15 November U.S. Census Bureau, 2010 Census. American Factfinder. U.S. Census Bureau, n.d. Web. 22 November U.S. Census Bureau, Year American Community Survey. American Factfinder. U.S. Census Bureau, n.d Web. 22 November U.S. Census Bureau, Geography Division. Military Installations. TIGER/Line Shapefiles Web. 28 November U.S. Census Bureau, Geography Division. Military Installations. TIGER/Line Shapefiles Web. 28 November Vertiec Solutions, LLC, on behalf of the Bureau of Financial Institutions State Corporation Commission, Report on Virginia Payday Lending Activity For the Year Ending December 31, Web. 17 November 2015.
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