Locating Unregulated Financial Institutions: Demographic Comparisons

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Locating Unregulated Financial Institutions
Demographic Comparisons

• By Michael Doherty
• San Francisco State University
• For Northeast Community Federal Credit Union
• May 3, 2004

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The Northeast Community Federal Credit Union

• Chartered in 1981
• Has nearly 1,200 Members
• Made over 2,400 loans
• Planning a field of membership expansion

• Mission is both to meet the banking needs of its
  members and support economic development of the
  community

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Map of Current Branches
Source NECFCU Hot Zone Study
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The Problem

• Geocode the locations of regulated and
  unregulated financial institutions.
• Compare locations to demographic characteristics
  to see if anecdotal theories about the location
  of check cashers hold true.
• Provide data to support NECFCUs field of
  membership expansion.

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Research Sources

• SBC Yellow Pages
• CDFI Economic Development Housing Hot Zone
  Study- SFSU 2003 Senior Seminar
• Local Newspapers for immigrant communities
  (Philippine News, China Daily, El Bohemio)
• Internet Search

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Unregulated Financial Institutions

• In San Francisco there are 14 pawn shops, 34
  check cashing offices, and 2 that advertise as
  providing both services.

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Regulated Financial Institutions

• In San Francisco there are 238 bank and credit
  union branches.
• Clustered downtown and on main streets with
  transit access.

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Locations

• Green are the Unregulated Facilities
• Blue are regulated
• Services are lacking in eastern portion of the
  City

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Household Size
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Compared to Minority Areas
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Income Levels
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Results

• 98 of the locations can be explained when
  combining the minority results with income
  results.
• An unregulated financial institution is usually
  found in a neighborhood that has at least a 25
  higher minority population than the median and
  has an income level that is greater than 10
  below the median income level.

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The Asian Question

• The Sunset and Richmond areas also appear to be
  underserved by regulated financial institutions
  yet they fit the criteria explained above.

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Proximity Analysis

• Creating raster maps to identify areas that have
  a need for NECFCU to expand into using the
  following variables

• Proximity of regulated financial institution
• Median income levels
• Percent minority and percent Asian population
• Rent Burden
• Household size

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Future Research

• Is the role of check cashers and pawn shops being
  filled by culturally specific organizations that
  are not advertised?
• Is the clustering in Hispanic areas associated
  with wire transfer services?
• Does the theory hold true outside San Francisco?

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THANK YOU

• Special thanks to Michael Chan, Ayse Pamuk, and
  Mono Simione