However, it is undeniable that in some parts of the country banks see a reason to expand their physical presence. This runs contrary to the conventional wisdom that physical bank branches were no longer relevant to consumers. It appears that in high growth metros banks find that physical locations are critical to their plans.

Three of the country’s eight regions – including the Southeast, the Southwest and the Rocky Mountain states – are adding branches, while the other five – including the Mideast and Northeast – are losing branches, with the losses being concentrated in a handful of large metro areas.

Some areas of the country are seeing growth while others continue to see branch closures

Table 1 shows the net change in bank branches across the country’s eight regions since the second quarter of 2026. It highlights the outsized role the Southeast plays in the country’s return to branch growth.

The Southeast is the clear driver of the national total, with the Southwest and the Rocky Mountain states also seeing positive branch growth. On the other hand, the Mideast –  including New York, New Jersey and Pennsylvania together with Delaware, Maryland and Washington, DC –  is losing branches faster than any other region in the country. However, it is not that simple, with Sunbelt cities in certain states outperforming every place else.

Growth concentrates in a handful of Southeast and Southwest states

Table 2 shows bank branch trends in the Southeast and Southwest regions by state. It shows that branch expansion is not spread evenly across the region as Florida and Texas account for roughly half of the combined gain alone.

Florida and Texas account for a large share of the combined growth across both regions, more than the next several gaining states put together. Georgia, the Carolinas, Alabama and Tennessee round out a cluster of Deep South and Gulf Coast states that added branches in every quarter. Virginia and West Virginia, both a part of the Southeast under this framework, saw essentially no branch growth. Outside of Texas, the rest of the Southwest experienced flat to slightly negative growth, with Arizona showing no change and New Mexico actually losing branches.

New York’s losses are a story about scale, not decline

Table 3 shows the ten metro areas with the largest net branch change over the same five quarters. It shows that both the gains and the losses are concentrated in a small number of metro areas rather than spread broadly across the country.

Dallas-Fort Worth, Atlanta, Miami, Charlotte, Austin and Nashville lead the metros that reported a net gain in branches, with more branches opening than closing. The New York metro’s branch network is by far the largest in the country, more than three times the size of Boston’s or Philadelphia’s. On a percentage basis, New York’s decline was actually smaller than Philadelphia’s or Detroit’s over the same window, and roughly in line with Boston’s. However, the concentration of losses in a handful of legacy Northeastern and Midwestern metro areas is the most notable pattern. 

Growth is happening for full-service branches, not in-store locations

Table 4 shows net branch changes by service type (full-service brick-and-mortar branches versus in-store/retail locations, such as those inside a supermarket or big-box store) and how they are split between the Southeast and Southwest regions compared to the rest of the country. It shows that growth, even in the fastest-growing markets, is happening via brick-and-mortar branches rather than in-store locations, the latter of which are shrinking everywhere.

Even in high growth markets, in-store and retail branches are also shrinking in number. Nationally, only 19 new in-store or retail branches opened over the entire five-quarter window compared with 96 that closed, a pattern that held firm in every quarter regardless of whether the broader branch count was growing or shrinking. Full-service brick-and-mortar branches account for the overwhelming majority of new openings everywhere, suggesting the in-store banking format is being wound down as a category rather than relocated to high growth markets.

Banking trade press coverage points to a straightforward explanation: in-store branches were built to provide transactional convenience for customers who were already at the store for something else. Online and mobile banking have eliminated most of the reason for that kind of interaction since routine transactions no longer require showing up in person at all. When customers do still need to visit a branch, recent reporting on bank branch strategy suggests they prefer a full-service location better suited to private conversations about banking needs rather than a retail store built for foot traffic.

The regional split lines up with where money and higher earners are moving

For banks, their branch strategy is a business decision made for many reasons that this data cannot pinpoint, but the geography trends outlined in this article line up closely with outside migration research. Demographic analysis published by Brookings Institute has tracked domestic out-migration from large coastal metro areas, including New York, Los Angeles, San Francisco, Boston and Seattle, alongside sustained in-migration to Sun Belt metro areas, such as Dallas, Tampa and Raleigh, since the early part of the pandemic. The same research found that a lot of what looked like a population rebound in big metro areas in 2023 and 2024 was driven mainly by a rise in immigration from abroad rather than a reversal of domestic migration rates. The newest available analysis on this migration found that metro population growth is declining again as immigration slows.

IRS migration data, which tracks income rather than head counts, shows the steadier pattern of growth behind the population volatility. The most recent filing-year data available covering 2022 to 2023 shows Florida gaining more than $20 billion in net adjusted gross income from interstate migration and Texas gaining more than $5 billion, while California, New York, Illinois, Massachusetts and New Jersey experienced the largest net losses. This state-by-state pattern matches this article’s branch findings closely, with the same handful of states gaining income being the ones gaining bank branches. New York, despite an overall population that has recovered in recent years due to immigration, continues to lose more income to domestic migration than nearly any other state, which is consistent with its outsized share of branch closures.

A note on data revisions

The figures in this article reflect the FDIC’s BankFind Suite structural change data as of the article’s publication date. Banks sometimes file branch opening, closing and relocation records after the quarter has ended, with FDIC assigning these filings a processing date that can fall months after the effective date of the change. As a result, figures for a given quarter can shift in later reports as additional filings are processed. This article reflects the most current data available and updates the prior quarter’s figures accordingly. The five-quarter window shown here has been refreshed against the newest available data pull, which includes revisions to the third and fourth quarter of 2025 and the first quarter of 2026. Readers comparing figures across published analyses should accept small revisions to prior quarter counts as a part of normal data processing, not as corrections to the overall methodology.

Methodology note: Figures cover FDIC-insured institutions’ full-service branch locations (brick-and-mortar and staffed retail/drive-through) based on FDIC’s OSCR structural change filings for the quarter shown. Regional definitions follow the U.S. Bureau of Economic Analysis’s eight-region scheme rather than the Census Bureau’s four-region scheme.

Jason Richardson is the Senior Director of Research with NCRC’s Research team.

Photo credit: Monstera Production via Pexels.

The drop in the unemployment rate was not because more people found new employment but because over 200,000 unemployed people left the labor force last month and stopped looking for work.

The labor market remains lukewarm as job openings, layoffs and resignations remained largely unchanged in May according to BLS’ data. While the rate of unemployment remains low overall, the slow labor market is affecting one group in particular: new college graduates.

As college graduation season ends, many graduates are struggling to enter the workforce. Their topline unemployment rate, officially called the U-3 rate, rose to  5.3% in April, an increase from the January 2025 rate of  4.7%. The U-3 rate is the percentage of the labor force that is unemployed. 

The U-6 rate, commonly called the underemployment rate, includes unemployed workers plus involuntary part-time workers and discouraged workers. The U-6 rate for new college graduates has risen faster than their U-3 rate. Since January 2025, the U-6 rate increased from 8.2% to a high of 10% in April.

The chart below shows both the U-3 and U-6 rates by race:

The increase in the U-6 rate suggests that a portion of new college graduates are turning to part-time and gig work as suitable full-time work becomes harder to find. Fortune Magazine reported on new college graduates turning to gig and entrepreneurial work as entry-level job openings have declined while the number of applicants for the remaining jobs has increased. This has led some to pursue work outside of their formal areas of study. According to data from the Federal Reserve Bank of New York, 41.5% of recent college graduates work in a job that doesn’t require a college degree. 

Breaking down the data by race reveals a couple of interesting trends. First, both the U-3 and U-6 rates are higher for Black and Hispanic graduates compared to White graduates. The unemployment rate for Black graduates peaked at 12.3% in November of last year and then declined by over 5 percentage points (pp) to 6.9%, while the underemployment rate declined only 2 pp over the same period. Despite this decline, Black underemployment remains elevated compared to the beginning of 2025. Similarly, the U-6 rate for Hispanic college graduates has been steadily increasing since mid-2022.

A second important finding from the data is that not only are Black and Hispanic college graduates’ unemployment rates rising, but they are substantially higher relative to White graduates. The Black grads U-3 rate reached a low of 3.3% in March of 2024 and then experienced a spike to 6.9% in April, a 110% increase. For Hispanic grads, their U-3 rate increased by 80% from a low of 4.1% in January of 2025 to 7.3% in April. For White grads, their U-3 rate increased by only 36% from an October 2022 low of 3.18%.

While media attention has focused on unemployment among new college graduates, and rightfully so, it is more endemic for Black and Hispanic graduates. For college graduates overall, the reason for their employment woes has been broadly attributed to a combination of broader labor market weakness and AI changing the hiring decisions of companies. 

Firms facing higher costs, due in part to tariffs, are hiring fewer workers, including recent college graduates. Some of the layoffs result from poor management decisions in the past. For example, some companies over-hired in the post-pandemic boom and have now begun layoffs. These experienced unemployed workers are sometimes competing for jobs alongside new college graduates. These broader labor market trends are negatively impacting job hiring for all workers, including for recent college graduates.

While companies, particularly tech firms, have announced tens of thousands of layoffs this year, the biggest challenge for new entrants to the labor market is the drop in entry-level hiring. Firms are adopting a wait-and-see approach to AI by holding off on hiring junior workers until they better understand the capabilities of AI systems and who they can replace. Additionally, companies that are leaning into AI investments are letting workers go to free up capital for AI spending.

For recent Black and Hispanic college graduates, AI introduces another challenge – algorithmic discrimination. A study from Stanford University found that AI screening tools systematically discriminate against Black applicants. Research from the University of Washington has found that AI resume screening tools can show bias based on an applicant’s name. The tools they reviewed recommended applicants with White-associated names 85% of the time compared to only 9% for applicants with Black-associated names. 

When an AI underwriting algorithm is primarily trained on data from a pool of mostly White applicants, it can favor white candidates to the detriment of Black and Hispanic qualified applicants. A dataset of interactions between biased bank branch loan officers and applicants seeking a small business loan might produce an algorithm that reflects biases of the loan officers. Thus, AI can amplify existing systems of discrimination.

The labor market for recent college graduates is weak not only because of structural reasons like high costs and post-pandemic over-hiring but because of the AI shock. Declining entry-level job hiring is fueled by this dynamic. For non-White college graduates, potential discrimination from AI algorithms, in addition to the AI-related job hiring freezes, is directly affecting their ability to enter the workforce. The labor market is bad for recent college graduates. For Black and Hispanic grads, it’s even worse. 

Joseph Dean is the Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Safari Consoler via Pexels.

This dataset draws on US Census data spanning multiple decades (from the 1970s through 2010s) and covering thousands of neighborhoods tracking demographic, economic and housing trends at the neighborhood (census tract) level across metropolitan areas nationwide.

Why this matters

Gentrification is one of the most debated topics in the housing and community development fields. Depending on how it’s measured, the same neighborhood can look like a success story or a displacement crisis. This dataset was built to cut through that confusion. It applies five research-tested methods for identifying gentrification so users can see how conclusions shift depending on the approach — and which methods are best supported by real-world evidence.

NCRC’s own research, published in the Journal of Urban Affairs, found that the methods included in this dataset were among the most accurate at tracking actual patterns of class change, racial turnover and housing market pressure. Using these methods, we estimate that roughly 60,000 Black residents left gentrifying neighborhoods in Washington, DC between 1990 and 2020 alone.

This new dataset has provided researchers and advocates with a more transparent and evidence-based way to understand where and how gentrification is occurring.

What’s in the dataset

The dataset includes neighborhood-level indicators over time, such as:

• Population and demographic change
• Income and poverty levels
• Housing values and market activity
• Employment and occupational shifts
• Gentrification indicators by decade

These indicators allow researchers to make consistent, decade-by-decade comparisons across thousands of neighborhoods in urban areas nationwide.

What we found

Using this dataset and our evaluation approach, we found that in Washington, DC – one of the most studied cases of gentrification – neighborhoods identified as gentrifying were also the primary sites of significant Black population loss between 1990 and 2020.

However, this does not mean every move was forced. But it does show that population changes were not random as they were concentrated in areas experiencing rapid economic and social transformation.

How this helps communities

This dataset is designed to support:

• Better public understanding of neighborhood change;
• More informed policy decisions, including tenant protections and anti-displacement strategies;
• Targeted investment by focusing resources where pressures are greatest; and allows for more
• Local analysis, allowing cities to apply consistent evaluation methods to their own communities.

A tool for action

By grounding the measurement of gentrification in real-world indicators, this dataset helps move the conversation beyond competing definitions and toward practical solutions.

When we can clearly identify where change is happening — and who is affected — we are better equipped to protect communities and promote equitable development.

To access the dataset and learn more about the evaluation methods, please see the following resources: 

• https://www.openicpsr.org/openicpsr/project/250783/version/V1/view
• https://www.tandfonline.com/doi/full/10.1080/07352166.2026.2621717

Funding Sources 

National Institutes of Health’s National Institute on Aging (R01AG080401)

Bruce C. Mitchell with the Principal Researcher with NCRC’s Research team.

Photo credit: Erik McLean via Pexels.

Despite the positives in the April jobs report released by the Bureau of Labor Statistics (BLS), closer scrutiny of the data reveals ongoing weaknesses in the labor market. An examination of the employment situation facing Black men helps elucidate these negative trends, including their falling labor force participation rates, sluggish job growth and rising long-term unemployment. 

The BLS defines a worker as unemployed if they have actively looked for a job within the previous four weeks. A more expansive definition of unemployment includes part-time workers who seek but can’t find full-time work and those who want a job but have not actively looked for work because they believe no quality positions exist. The BLS also tracks this expanded definition of unemployment, formerly called the U-6 rate or underemployment rate. 

The chart below shows the underemployment rate by race and sex from 2022 to the present:

The underemployment rate increased throughout the first 3 quarters of 2025, then declined during the 4th quarter of 2025 and during the 1st quarter of 2026. One would assume that more people are moving from underemployment to employment. 

Unfortunately, this assumption is not true for Black men, with the labor force participation rate shown below explaining the reasons behind this trend:

While the number of unemployed Black men declined, so did the number of Black men in the labor force. We can see this in the chart above which shows that their labor force participation rate also declined over this same period. This suggests that, rather than more Black men finding employment, many are simply leaving the labor market entirely.

Given that these were working-age men, one could assume they are not leaving the labor force due to retirement but rather due to feelings of discouragement or an inability to find work. In fact, the number of employed Black men over 20 years old has declined by roughly 650,000 since November 2025.

This pattern of declining labor force participation and underemployment is unique among Black men. The labor force participation rate for all other groups held constant or increased, while the Black male labor force participation rate declined over 2025 and early 2026.

One explanation for why increasing numbers of working age Black men are leaving the labor force could be that their largest sectoral employer, logistics, is experiencing a multi-year slump. Due to changes in freight demand, tariffs and rising costs, the logistics sector has seen virtually no job growth since the summer of 2022. Furthermore, just one year since President Trump announced his tariff/trade war, the transportation and warehousing sector has lost almost 90,000 jobs, including 22,000 truck drivers and 50,000 warehouse positions.

These job losses will only worsen as the energy crunch from the Iran war continues to spike fuel prices globally. The jet fuel shortage has already led to the closure of Spirit Airlines. The transportation sector will experience more job losses and bankruptcies if the situation doesn’t change, with many of the losses impacting Black men. 

One area where these job losses are showing up is in the rise of the long-term unemployed as shown in the chart below: 

The share of the unemployed who have been jobless for longer than 27 weeks is now over 26% and continues to rise as illustrated by the chart above. This has pushed the average number of weeks people are unemployed to roughly 25 weeks. Among the number of unemployed Black men, 30% have been jobless for longer than 27 weeks, the highest of any racial/ethnic group.

The employment situation of Black men highlights several growing issues facing workers overall, such as rising long-term unemployment rates and heavy job losses across multiple sectors. While policies that uplift Black men specifically have become politically toxic, measures like ending the tariff/trade war and expanding unemployment benefits (which was done during the COVID-19 pandemic) can help all workers, including Black men.

Joseph Dean is the Racial Economic Research Specialist with NCRC’s Research team.

Photo credit: Mukhtar Stuaib Mukhtar via Pexels.

The national bank branch network grew for the second consecutive quarter in the first three months of 2026, marking the first back-to-back expansion since 2010. 267 full-service branches were opened between January and March while 217 branches were closed, producing a net gain of 50 locations. This follows the fourth quarter trend that occurred in 2025 when the network grew by 71 branches, breaking a 15-year streak of uninterrupted contraction. In 65 quarters of data tracking going back to 2010, only four have been positive and only two have occurred consecutively.

The reversal is striking in the context of the industry’s recent history. In 2022, NCRC documented in its The Great Consolidation of Banks and Acceleration of Branch Closures Across America report the ways in which the pandemic had doubled the pace of branch closures, from roughly 99 per month in the decade before COVID-19 to more than 200 per month thereafter. That report also found that two-thirds of all banking institutions had disappeared since the early 1980s and that 9% of all branches closed between 2017 and 2021.

One in three of those closures was in a low- to moderate-income or majority-minority neighborhood. Four years later, the closure wave has subsided and the network is growing again. The growth is concentrated entirely in traditional standalone branches, while in-store retail locations are closing at three times the rate and virtually no new branches are opening in their place.

That growth, however, is not happening everywhere. 67 new branches were added in the Southern region of the US during this quarter, with Texas and Florida seeing the largest gains. The Midwest flipped from contraction to growth. But, the Northeast continued to lose branches, with the closures that did occur remaining heavily concentrated among a small number of large institutions. The geographic pattern of branch expansion closely tracks where the country’s population is growing, particularly in metros attracting younger and more diverse communities.

For a more detailed look at bank branch changes in your community, contact NCRC’s research team at research@ncrc.org.

Where branches opened and closed

The following map shows every full-service branch that opened or closed during the first quarter of 2026. Yellow markers indicate openings and red markers indicate closures. Click any marker for the bank name, branch name and address or use the dropdown to filter by bank name.

Bank branch openings and closures, Q1 2026

267 branches opened and 217 closed between January and March 2026. Click any marker for details.

The map reveals the geographic concentration of the quarter’s activity. Branch openings tend to cluster in the Sun Belt, particularly across Texas, Florida and the Southeast, while closures are more dispersed across the Northeast and California. Several of the largest closure clusters correspond to individual corporate decisions by TD Bank and Bank of America rather than a broad market retreat from those communities.

The national picture

The following chart compares branch openings and closures across the five most recent quarters, showing how the balance between the two has shifted from sustained contraction to consecutive growth:

While the chart tells the story of what happened, the why matters even more. The turnaround came almost entirely from the closure side: banks sharply reduced the number of branches they shut down, while the pace of new openings held roughly steady. That means the industry did not suddenly accelerate its expansion but in fact reduced closures. Whether this reflects a deliberate strategic shift or simply the lack of easy closure targets after years of aggressive consolidation is a question the coming quarters will help answer.

The growth is not evenly distributed across branch types. There are full service, brick and mortar locations, which often have full service features like drive through tellers, parking and ATMs. There are also in-store locations mostly in grocery stores or large retailers.

The following chart compares the quarterly closure rate for each branch type as a percentage of its baseline by putting the two on equal footing despite their very different network sizes:

The chart shows the gap clearly: banks are abandoning the in-store model. The branches inside grocery stores and retail locations that were prevalent in the 1990s and 2000s are being systematically wound down, while traditional standalone branches are the only bank type showing growth. For communities that relied on an in-store branch as their primary access point to banking services, this shift may effectively function as a closure even if the bank maintains a traditional location elsewhere in the metro area.

82 branches were relocated during the quarter. Most moved less than a quarter of a mile from its original location. However, relocations did not change the total number of branches and were excluded from the final opening and closing counts. The nation’s bank branch network currently stands at 74,511 full-service locations.

Where the banking industry is investing

The following chart shows the five metropolitan areas with the largest net branch gains during the first quarter alongside their performance in the same quarter one year ago:

Dallas-Fort Worth, Texas saw the highest net gain out of all of the metros during the first quarter with six branches, representing the biggest year-over-year increase for any market in the country at +15. One year ago, Dallas-Fort Worth lost nine branches. Nashville, Tennessee added five net branches, with Pittsburgh, Pennsylvania gaining four with zero closures after posting losses in the prior quarter.

Out of the five metros with biggest net gain in branches two are in Texas and two are in the Southeast region. Four of the five are among the fastest-growing metropolitan areas in the country by population. Pittsburgh is the exception, posting branch gains despite a flat regional population, suggesting bank investment there is driven by market repositioning rather than demographic growth. St. Louis and Seattle both went from negative losses to positive growth year-over-year. Texas accounted for three metros that ranked in the national top 15 for branch growth.

Where branch networks are contracting

The following chart shows the five metropolitan areas with the largest net branch losses during the first quarter alongside their performance in the same quarter one year ago:

No metropolitan area lost more than six branches during the first quarter. This represents a significant improvement from one year ago, when several major metros posted double-digit losses. New York remains the market with the largest net contraction, though its losses improved from nine to six year-over-year. San Francisco showed the most dramatic improvement of any major metro nationally, going from 12 net closures in the first quarter of 2025 to just three in the first quarter of 2026.

Chicago also improved substantially, from 10 closures a year ago to four. Washington, DC and Minneapolis were the only major metros with the steepest net declines that performed worse than one year ago. California continues to have multiple metros experiencing contraction, with Los Angeles, San Francisco and Sacramento, CA all posting net losses.

Regional patterns

The following chart compares each census region’s net branch change in the first quarter of 2026 to changes shown in the same quarter one year ago, showing where the reversal is concentrated:

The South is driving the national growth story. The states gaining branches are the same states gaining population, particularly through the growth of Hispanic, Black and Asian communities. The Census Bureau estimates show that Texas, Florida, North Carolina, Georgia and Arizona attracted the most immigrant populations between 2020 and 2023, with branch expansion  following those same migration patterns. However, reversals in immigration and the threat of an executive order targeting banks that serve immigrant depositors threaten to reverse this trend.

The Midwest posted the biggest regional reversal, shifting from a net loss of 46 branches in the first quarter of 2025 to a gain of nine in 2026. The Western region of the country improved substantially, though California’s ongoing consolidation kept the region in negative territory. The Northeast was the only region that showed no improvement, reflecting both its population decline and the concentrated closures by TD Bank and other large institutions headquartered in the corridor.

California and New Jersey continue to lead when it comes to state-level contraction. New Jersey’s persistent presence at the top of that list reflects structural consolidation in a mature, densely branched market rather than a sudden retreat.

Which banks are driving the changes

More than 200 banks had at least one branch opening or closing during the first quarter. But, the activity is not evenly distributed, with the pattern differing sharply between openings and closures.

Branch closures are heavily concentrated among a small number of large institutions. Three banks (TD Bank, Bank of America and JPMorgan Chase) accounted for nearly half of all closures during the quarter. TD Bank was responsible for nearly a quarter of all closures nationwide, shuttering 51 branches with zero openings in the Northeast region. Without TD Bank’s closures, the national net gain would have been 101 branches.

The following chart shows the 10 banks with the most branch closures during the quarter:

Branch openings are far less concentrated. JPMorgan Chase leads with 36, followed by Fifth Third Bank with 19 and Bank of America with 16. However, 26 different banks account for half of all openings. By contrast, just three banks account for nearly half of all closures. In other words, while some banks are still closing large numbers of their branches, many more banks are seeing a gradual expansion of their networks.

The following chart shows the 10 banks with the most branch openings during the quarter:

Community and regional banks are a significant part of the story. Of the 208 banks with any branch activity during the quarter, 164 had exactly one opening or one closing. These single-event institutions represent nearly 80% of all active banks and collectively account for a third of all branch activity nationwide.

Fifth Third Bank had the largest single-quarter net gain of any institution, adding 18 net branches on 19 openings with just one closure. Wells Fargo opened seven branches and closed none, its first positive quarter after five consecutive quarters of contraction. Whether this signals a strategic shift remains to be seen. JPMorgan Chase remains the dominant force when it comes to expansion, with a cumulative net gain of 128 branches over five quarters.

Counties at risk

Despite the overall positive trend, 209 counties nationwide currently have just one full-service bank branch. Texas has 22 single-branch counties, Montana has 15, Georgia has 14 and Colorado has 11. When a county’s last branch closes, residents must travel to a neighboring county for basic banking services, a round trip that can exceed 30 miles in rural areas.

What this means for communities

The geographic alignment between branch network changes and population trends is consistent and persistent. Branches are opening where people are moving and where Hispanic, Asian and Black communities are growing. They are closing where populations are aging and shrinking. The Census Bureau population estimates show that communities of color drove essentially all of the nation’s population growth between 2020 and 2023, with the nation’s population under age 18 already being majority-minority. The banking industry’s physical infrastructure is following these demographic currents.

The metros gaining the most branches are also among those most dependent on immigration-driven population growth. The Census Bureau projections indicate that without sustained immigration, the nation’s working-age population would begin to decline within the next two decades. Significant reductions in immigration levels could slow population growth in the Sun Belt metros where branch expansion is concentrated, potentially undermining the economic conditions that are attracting bank investment in the first place. For communities that have only recently gained banking access as their populations grew, that reversal would compound an already fragile situation.

This raises questions that the branch counts alone cannot answer. Are new branches in growing metros reaching the low- and moderate-income neighborhoods and majority-minority census tracts where population growth is concentrated or are they clustering in higher-income corridors? Under the 1995 Community Reinvestment Act (CRA) rules, which remain in effect after the withdrawal of the 2023 CRA modernization rule, a bank’s community development obligations are tied to the geographic areas where it operates physical branches. As the branch network shifts, so do the areas where regulators evaluate whether banks are meeting community needs.

Community organizations and regulators should examine whether branch openings in high-growth metros are serving the communities responsible for that growth. NCRC members can access this data by contacting the NCRC research team.

Methodology

This analysis uses data from the Federal Deposit Insurance Corporation (FDIC) BankFind Suite, which tracks individual branch openings and closures as they are filed. Branch openings are identified by FDIC change code 711 and closures by change code 721. Only full-service branches are included, which would be classified as either service type 11 (brick-and-mortar) and service type 12 (retail). Quarters are assigned by the FDIC processing date. Branch relocations, mergers and acquisitions are excluded from opening and closing counts to avoid double-counting.

The FDIC provides two separate datasets for tracking bank branch networks. The BankFind Suite tracks individual branch openings and closures as they are filed, making it the preferred source for quarterly trend analyses. The Summary of Deposits provides an annual snapshot of all branches as of June 30 of each year, including deposit volumes and census tract mappings. Branch counts may differ between the two datasets due to different inclusion criteria and reporting timelines.

Regional classifications follow the US Census Bureau definitions. Metropolitan area definitions follow the Office of Management and Budget’s Core Based Statistical Area (CBSA) boundaries. This report uses common metropolitan names in tables and text. Full CBSA definitions with component counties are listed below.

The population and demographic data cited in this report are drawn from the US Census Bureau population estimates covering April 2020 through July 2023. The data is current through March 31, 2026.

Metropolitan area definitions

Atlanta — Barrow, Bartow, Butts, Carroll, Cherokee, Clayton, Cobb, Coweta, Dawson, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Haralson, Heard, Henry, Jasper, Lamar, Meriwether, Morgan, Newton, Paulding, Pickens, Pike, Rockdale, Spalding and Walton counties in Georgia.

Austin — Bastrop, Caldwell, Hays, Travis and Williamson counties in Texas.

Boston — Essex, Middlesex, Norfolk, Plymouth and Suffolk counties in Massachusetts; Rockingham and Strafford counties in New Hampshire.

Chicago — Cook, DeKalb, DuPage, Grundy, Kane, Kendall, Lake, McHenry and Will counties in Illinois; Jasper, Lake, Newton and Porter counties in Indiana; Kenosha County in Wisconsin.

Dallas-Fort Worth — Collin, Dallas, Denton, Ellis, Hunt, Johnson, Kaufman, Parker, Rockwall, Tarrant and Wise counties in Texas.

Los Angeles — Los Angeles and Orange counties in California.

Minneapolis — Anoka, Carver, Chisago, Dakota, Hennepin, Isanti, Le Sueur, Mille Lacs, Ramsey, Scott, Sherburne, Washington and Wright counties in Minnesota; Pierce and St. Croix counties in Wisconsin.

Nashville — Cannon, Cheatham, Davidson, Dickson, Macon, Maury, Robertson, Rutherford, Smith, Sumner, Trousdale, Williamson and Wilson counties in Tennessee.

New York — Bergen, Essex, Hudson, Hunterdon, Middlesex, Monmouth, Morris, Ocean, Passaic, Somerset, Sussex and Union counties in New Jersey; Bronx, Kings, Nassau, New York, Putnam, Queens, Richmond, Rockland, Suffolk and Westchester counties in New York; Pike County in Pennsylvania.

Pittsburgh — Allegheny, Armstrong, Beaver, Butler, Fayette, Washington and Westmoreland counties in Pennsylvania.

San Diego — San Diego County in California.

San Francisco — Alameda, Contra Costa, Marin, San Francisco and San Mateo counties in California.

Washington, DC — District of Columbia; Calvert, Charles, Frederick, Montgomery and Prince George’s counties in Maryland; Arlington, Clarke, Culpeper, Fairfax, Fauquier, Loudoun, Madison, Prince William, Rappahannock, Spotsylvania, Stafford and Warren counties and the independent cities of Alexandria, Fairfax, Falls Church, Fredericksburg, Manassas and Manassas Park in Virginia; Jefferson County in West Virginia.

A large body of research links these kinds of exposures to a wide range of health concerns. Air pollution is associated with millions of premature deaths globally each year alone and is tied to heart and lung disease, especially in communities located near industrial activity and heavy traffic. Researchers are also increasingly documenting links between environmental conditions and mental health. 

Long-term exposure to air pollution has been associated with depression and anxiety, while environmental noise from traffic and industrial infrastructure have been linked to stress and anxiety symptoms. More broadly, environmental pollution is now understood to affect a person’s physical and mental well-being, with evidence linking it to cognitive decline, psychological distress and worsening mental health over time.

The health burdens of LULUs are not distributed evenly. Decades of environmental justice research have shown that those patterns reflect long-standing inequalities in political power, land use decision-making and access to resources.

One of the clearest historical frameworks for understanding these patterns is residential segregation and its relationship to redlining. From the 1930s until the 1960s, the federal government graded neighborhoods based in part on race and ethnicity, with many Black and immigrant communities being redlined – or labeled as high-risk for investment. Redlining did not create segregation on its own, but it formalized and reinforced patterns of disinvestment that shaped neighborhoods.

A growing body of research finds that neighborhoods with a history of redlining also tend to have higher concentrations of environmental burdens, including industrial land uses, heavily trafficked transportation arteries and other LULUs. These same neighborhoods often continue to face socioeconomic disadvantages and elevated exposure to environmental stressors. A recent study conducted by researchers at the University of Michigan, the Ohio State University and the National Community Reinvestment Coalition (NCRC) reflects these broader patterns in Chicago. 

“We found that neighborhoods with higher levels of historical redlining also tended to have greater concentrations of certain LULUs, especially industrial land uses, vacant land or construction sites,” said University of Michigan lead researcher Dr. Liang Chen.

These neighborhoods also tended to report higher levels of self-rated poor mental health. In our analysis, industrial land, construction sites and vacant land were especially important in understanding how redlining, neighborhood conditions and mental health are patterned together across the city.

These findings suggest that the geography of LULUs today overlaps closely with the geography of historical housing discrimination defined by redlining. In Chicago, as in many US cities, neighborhoods that suffered decades of disinvestment continue to bear heavier environmental burdens and worse health outcomes. This illustrates how the legacies of segregation and land use continue to shape mental health outcomes today.

Addressing these patterns requires intentional policy action. Tools such as the Community Reinvestment Act (CRA) can help by encouraging investment in historically underserved neighborhoods, supporting affordable housing, community facilities and redevelopment efforts that improve neighborhood conditions and expand access to resources that promote community health.

Bruce C. Mitchell, PhD. is the Principal Researcher with NCRC’s Research team.

Photo credit: Chait Goli via Pexels.