Analysis of Bank Branches in the Greater Los Angeles Region

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1 Analysis of Bank Branches in the Greater Los Angeles Region Brian Moore Introduction The Community Reinvestment Act, passed by Congress in 1977, was written to address redlining by financial institutions. Since then, the nature of banking and services they offer have changed significantly. Most literature deals with the Community Reinvestment Act in terms of mortgage lending because this most easily measured of the factors that go into the CRA rating. This paper attempts to begin the process of capturing the harder to quantify service section of the CRA ratings, as suggested by Stegman, Cochran, and Faris (2002). Within the service category, this will address access to bank branches and establish potential locations that are in need of new bank branches. This more generalized focus is warranted as much research shows that individuals who are low-to-moderate income levels tend to rely on either public transportation or other non-automobile focused modes of transportation. While the CRA policy targets low-to-moderate income individuals, banks currently frame the requirements in terms of either banked or unbanked customers. So, this more general framework includes potential for CRA credits, as well as the expansion of current market share. The attention to unbanked customers, includes individuals who are in LMI categories, as well as non-citizens, or other marginalized groups, who for a variety of reasons choose not to bank. The approach presented in this paper attempts to capture neighborhood need for fincaial services, using data from the 2000 census, FDIC summary of deposits, ESRItiger shapefiles, and land use designations from the Southern California Association of Governments year 2000 general plan. The scope of this research includes all of Los Angeles County, but focuses on the majority of the population in the more densely populated southern ½ of the County. The goal of

2 this research is to start a body of research that will reshape the assumptions used in current suitability analysis for locating new banks. Hopefully, this combined with case studies of new bank branches opened in cooperation with Emerging Markets, Inc. shows that it is profitable to serve areas that are marked by lower per-capita incomes, and higher populations of minorities and ethnic groups. Literature Review My primary source for this framework is an article published by the Brookings Institute in Stegman, Cochran, and Faris call for a new method of scoring for the CRA Service Test. The method essentially incorporates methods of spatial analysis that are only recently available thanks to improved technologies. They suggest the geocoding of not just bank locations to track service and access, but also the geocoding of deposit accounts to quantify and qualify the expansion of access to low and moderate income customers. Including the geography of bank accounts improves the quality of the research, particularly because of the expansion of access points to bank services, ATMs, phone and online banking, etc. Access to deposit geocoding would enable a more accurate assessment of the role of proximity in financial services. Much of the research regarding the CRA is related to mortgage lending, primarily because it is easier to monitor because the Fair Housing and Home Mortgage Disclosure Acts require more specific record to be taken regarding lending for home purchases. There seems to be a general consensus that the CRA has in fact expanded access to loans for low and moderate income barrowers. This is important because there are significant wealth effects from housing equity on consumption; being able to purchase a home increases wealth, which in turn increases an individual s ability to provide for themselves and those around them. This paper does not

3 directly address the issues of mortgage lending and wealth associated with access to financial services. Methodology for Non-Spatial Bank Access Using correlation, linear regression, and Exploratory Spatial Data Analysis, this research suggests is in conclusive in terms of determining a consistent relationship between the concentration of banks, or distance to banks and any of the demographic variables. Correlations in aggregate data for the County of Los Angeles were as inconclusive as selecting only tracts with banks, or tracts without banks. While a number of variables proved significant, they were often so close to zero that the correlations were only slightly positive or slightly negative in all three cases. This suggests that the banking industry as a whole is expanding evenly across the geography. Figure 1 shows the distribution of banks, along with spatial graphs of non-hispanic whites, aggregate income, and bank deposits. For note, figure 2 shows the top 10 ranking in total bank deposits, and bank deposits per capita. The determination for this section is that the chosen variables are inadequate to determine the methods the industry uses to open new branches. The ability to geocode bank accounts, and relate accounts to specific branches might yield different results. Location Theory of Competition Currently, there is much debate over how and when proximity and location play a key role in competitive advantage. The financial sector in general is often cited as an industry where proximity and agglomeration are vital to the success of a firm, and locations like New York, London, and Tokyo are prime examples of the density competition creates. However, not all financial services can, or should locate with in this kind of geography. Particularly at the level of branch access, the location needs for existing, or new branches varies depending on the

4 saturation level of the neighborhood and surrounding region. In some neighborhoods, it is good to open in a new location, far from other bank branches. In other neighborhoods, it is vital to open as close to existing banks as possible in order to be competitive. This paper begins to sort some of these issues out for the Los Angeles region. Methodology for Suitability Analysis By strictly limiting the number of variables, this simple suitability analysis shows ideal locations for new retail bank branches at two scales, neighborhood and regional. The suitability analysis is compromised of three rasters combined with different weights (weighted reclassification). Each raster uses a uniform cell size of 100. The first raster is the Inverse Distance Weighted surface. This surface uses inverse distance weighted interpolation with a variable search radius and a search count of 12 (points). The population field is branch deposits. The generated surface shows neighborhood clusters of banks weighted by the size of the deposits. Weighting the surface by deposits accounts for the size of the bank, and in turn influence range of the neighborhood cluster (limited to 12 banks). To bring this surface into the analysis, the values classified by 10 quantiles, then reclassified into reverse quantile rank. Least dense receiving a 10, most dense receiving a 1. Finally, this surface received a 20% weight in the regional suitability analysis and a 50% weight in the neighborhood analysis, because of its limited geographic range. The second raster is kernel density of banks, by deposit size. Similar to the IDW surface, this shows regional clusters of banks, and contains a much smoother surface, ignoring local variations in favor of larger clusters. For this raster, the search radius was set to 4828 meters, roughly three miles. It was also classified by 10 quantiles then converted to inverse rank, 1 10, one being the most dense 10 being the least. In the regional analysis this surface received a 50% weight, in the neighborhood, it received a 20%. Both of these weights were

5 because of this surface s smoother surface over a larger geography. The two surfaces that account for existing bank branches, thus access to service, received a combined weight of 70% for each analysis. This heavy weight is given to existing banks because the goal is to target locations for new branch openings, rather than changes to existing branches. The third raster used in the analyses represents a calculation of income and total population by census tract. In attempt to control for large variances in tract size, and to give weight to tracts that may have low per-capita income but large aggregate income, the analysis uses aggregate income divided by the product of population and square mile area. This method decreases the negative impact of using only per-capita income by penalizing tracts with high per-capita income using density. Thus, the calculation produces income per person-square mile. This shapefile was then classified into 10 quartiles, which were recorded to be used as the class boundaries for the converted raster. This is necessary because classifying the raster surface yields skewed classes because n is the number of cells, rather than the number of census tracts, and inaccurately represents the distribution of income per person-mi 2. After the feature was converted to a raster, the correct class boundaries were applied. In the analyses, this feature received 30% for both neighborhood and region. The final surface analyses show the best locations for new bank branches in the LA region. Figures 3 5 show the neighborhood suitability analysis alone, with census tracts that qualify for CRA (less than 80% median income for the region), and with commercial land use zoning respectively. Figure 6 shows the regional land use analysis, it should be noted that this particular analysis places such a significant emphasis on existing banks that very low density areas with few banks also score fairly high on this scale.

6 Summary of Key Findings This paper draws on readily available data from the FDIC and the U.S. Census to lay the groundwork for the process of scoring the CRA Service Test as proposed by Stegman, Cochran, and Faris, but does so for the industry as a whole, rather than on an institutional basis. Using key variables such as distance from bank branches, income levels, total population and density, ethnicities, branch deposit sum, number of banks per tract, and aggregate tract deposit sum, this paper finds that traditional ideas of redlining are, for the most part, no longer accurate. However, this does not mean that there is equal access to branches for everyone, or that banks do not need to open new branches in the Los Angeles region. This body of work suggests the opposite, that even though access is expanding, the location of new branches is even more important than before in capturing new accounts.

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13 References Apgar, William and Mark Duda. The Twenty-Fifth Anniversary of the Community Reinvestment Act: Past Accomplishments and Future Regulatory Challenges. FRBNY Economic Policy Review. Federal Reserve Bank of New York. New York, NY , June Belsky, Eric, Matthew Lambert, Alexander von Hoffman. Moderated by Nicolas Retsinas. Insights Into the Practice of Community Reinvestment Act Lending, A Synthesis of CRA Discussion Groups. Joint Center for Housing Studies, Harvard University. Cambridge, MA. CRA00-1, August Belsky, Eric and Joel Prakken. Housing Wealth Effcts: Housing s Impact on Wealth Accumulation, Wealth Distribution and Consumer Spending. Joint Center for Housing Studies, Harvard University. Cambridge, MA. W04-13, December ESRI. Census 2000 TIGER/Line Data. Accessed April, GeoLytics, Inc. Census CD 2000 SF3. East Brunswick, NJ Ladderman, Liz. Has the CRA Increased Lending for Low-Income Home Purchases? FRBSF Economic Letter. The Federal Reserve Bank of San Francisco. San Francisco, CA. Number , June 25, Stegman, Michael, Kelly Cochran, and Robert Faris. Creating a Scorecard for the CRA Service Test, Policy Brief. The Brookings Institution. Washington, D.C. No 96, March 2002.