Auto Insurance Study

Study: Drivers in Less-White Zip Codes Pay More for Auto Insurance

Updated: October 28, 2024

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MoneyGeek's Analysis of Auto Insurance Premiums By ZIP Code

Structural inequality in America often financially penalizes communities of color. Across the country, many Black and Latino citizens pay more for services and expenses, including home loans, property taxes and even car insurance, based on location.

To learn more about how disparities in car insurance costs impact people of color, MoneyGeek analyzed 1,648 ZIP codes in 69 cities across the U.S., comparing demographics and auto insurance premiums. The study found that drivers living in predominantly white ZIP codes often pay less for car insurance than people living in the same cities in ZIP codes with a lower proportion of white residents.

Among 69 cities with more than 10 ZIP codes available for analysis, 52 (75%) have a negative correlation (stronger than -0.60) between auto premiums and the percentage of white people in a ZIP code. Much like temperatures drop as elevation increases, car insurance prices fall as the ZIP code’s proportion of white residents increases.

Key Takeaways

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Auto insurance premiums are higher in ZIP codes with fewer white residents.

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Drivers in less-white ZIP codes may pay up to $891 more annually for insurance compared to predominantly white areas.

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Cities with the strongest correlations between race and premiums: Oakland, New Orleans and Milwaukee.

MoneyGeek identified 12 cities across the country where premiums vary the greatest. Depending on the city, you could pay up to $130 more for car insurance for every 10 percentage points less white your ZIP code is.

Organizations, activists and academics have long questioned pricing variations in many industries that negatively impact consumers of color. On July 23, 2020, the National Association of Insurance Commissioners (NAIC) announced the formation of a special committee designed to examine current practices in the insurance industry that potentially disadvantage people of color. While insurance providers use a combination of factors to determine individual rates, the NAIC’s research will reveal how and if these practices negatively or disproportionately impact minorities. The committee is dedicated to making recommendations based on its findings by the end of the year.

Whiter ZIP Codes and Lower Rates Are Correlated

Auto insurers follow state specific-rules and regulations to set ZIP-code-level premiums that are based on the frequency and severity of claims, where severity refers to the cost of paying a claim. The more expensive and more frequent the claims, the higher the premium prices. MoneyGeek’s analysis compared rates across the country, utilizing a consistent driver profile to examine the pricing differences when ZIP code is the only variable changed. The demographics of each ZIP code were researched to calculate the correlation of a ZIP code’s auto insurance premium to the percentage of the ZIP code’s population that is white.

In cities across America, there is a correlation between a driver’s proximity to white populations and what they pay in car insurance. However, this correlation may be surprising for many drivers given that advertising often claims to reward safe driving and emphasizes that rates are based on good behaviors and customer loyalty.

However, in many cities across the United States, where a driver lives plays a large role in determining car insurance rates. Oakland, California, had one of the strongest negative correlations between white population percentage and annual car insurance rates among big cities (-0.925) in MoneyGeek’s study. People living in the five ZIP codes with the highest insurance rates pay an average of $360 more a year than people living in the five ZIP codes with the lowest rates, which have populations that are, on average, 42% more white.

In some cities like New Orleans, Louisiana, which has a -0.809 correlation between white population percentage and car insurance rates, the same discrepancy among ZIP codes that pay more and ones that pay less is a difference of $891 a year, on average.

Based on the analysis, ZIP codes with a smaller percentage of the population that is white tend to pay more for car insurance.

Structural Inequality and Auto Insurance

12 Cities Rank Highest for ZIP Code Premium Variations

Among all of the locations MoneyGeek analyzed, 12 cities (ranked in order of strongest negative correlation between white population percentages and car insurance rates) stand out as having extreme price variations in annual car insurance premiums based on ZIP codes.

Strongest Link Between Non-White ZIP Codes and Higher Premiums

City
Correlation
Premium Increase

Oakland, CA

-0.925

$360

Milwaukee, WI

-0.916

$364

St. Louis, MO

-0.895

$439

Chicago, IL

-0.884

$257

Baltimore, MD

-0.884

$570

Atlanta, GA

-0.872

$365

Kansas City, MO

-0.861

$231

Louisville, KY

-0.858

$656

Houston, TX

-0.847

$267

Phoenix, AZ

-0.83

$344

New Orleans, LA

-0.809

$891

St. Paul, MN

-0.806

$348

These 12 cities all have pricing discrepancies greater than $230 a year, on average, when comparing the annual insurance costs of the five ZIP codes in each city charged the most versus the five ZIP codes charged the least. They represent a cross section of America, spanning the West Coast, Midwest, Southwest, South and East Coast — illustrating that the problem is not isolated to one particular region of the country.

While cities like St. Louis, Missouri; Chicago, Illinois; and Atlanta, Georgia have high levels of ZIP-code-based segregation, that difference is not always the determining factor.

A common factor between the 12 cities is at least a 34 percentage point difference in white population between the more diverse ZIP codes that pay the most and the less diverse ZIP codes that pay the least.

In ZIP codes where premiums are more expensive, drivers are charged more not because of their personal driving history, but because of a higher frequency and severity of claims in the area.

3 Cities Experience the Highest Financial Impact

Three cities — New Orleans, Louisville, and Baltimore — have the highest auto premium disparities. While other cities in the top 12 fall within the $230–400 range for pricing variations, diverse ZIP codes in the three aforementioned cities pay much higher rates. In New Orleans, Louisville and Baltimore, average annual insurance rate differences between higher and lower-paying ZIP codes are $891, $656 and $570, respectively.

In New Orleans, the ZIP codes with the lowest premiums, where whites make up about 79% of the population, pay about $2,000 annually. Three clustered ZIP codes with white populations of about 5% pay the highest premiums — around $3,200 annually.

In Louisville, people living in the lowest-paying ZIP code cluster, with white populations ranging from 75–80%, pay around $1,300 for their annual premium. The two ZIP codes with the highest premium of about $1,950 have white populations ranging from 5–10%.

In Baltimore, the ZIP code paying the lowest premium has the highest population of white residents (79%). People in this ZIP code pay an annual premium of about $1,450. The two ZIP codes charged the highest premiums of around $2,150 have populations that are less than 10% white.

Location Can Cost as Much as a Speeding Ticket or Lower Credit Score

In some cities, living in a more diverse ZIP code can weigh as negatively on your car insurance payment as having a 16–20 mile-per-hour speeding violation or a 55–60 point drop in your credit score. This means that even with a spotless driving record, people living in ZIP codes with a higher Black and Latino population are often penalized despite their personal driving record.

The following table shows the observed premium differences and compares that difference to the cost of having a speeding ticket and credit score difference.

Insurance Costs of ZIP Code vs. Driving Behavior

City
ZIP Code Penalty vs. Speeding Ticket Penalty
ZIP Code Penalty vs. Credit Score Penalty

Oakland, CA

55.7%

*

Milwaukee, WI

101.2%

176.2%

St. Louis, MO

140.6%

163.0%

Chicago, IL

80.8%

111.5%

Baltimore, MD

150.4%

125.0%

Atlanta, GA

77.4%

124.9%

Kansas City, MO

97.0%

100.1%

Louisville, KY

199.7%

152.5%

Houston, TX

173.3%

78.4%

Phoenix, AZ

103.2%

105.9%

New Orleans, LA

103.4%

115.2%

St. Paul, MN

98.2%

135.1%

*California does not allow pricing based on credit score.

In Houston, your premium may be 73% higher because of your ZIP code than a driver with a speeding ticket who happens to live in a ZIP code with a large white population. In Milwaukee, your premium may be 76% higher based on your ZIP code than a driver whose credit rating went from good to fair in a ZIP code with a higher white population.

Expert Insight on Car Insurance Rates and Equality

MoneyGeek engaged academic thought leaders with expertise in structural inequality advocacy and economics to answer pressing questions about auto insurance. The opinions and solutions expressed below are the views of the individual subject matter experts.

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David Crockett, PhD
Professor of Marketing and Moore Research Fellow, University of...
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Kalinda Ukanwa, PhD
Assistant Professor of Marketing, Marshall School of Business,...
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Jerome D. Williams, PhD
Prudential Chair and Distinguished Professor–Marketing Department,...
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Vanessa G. Perry, PhD
MBA, Ph.D., Professor of Marketing, Strategic Management and Public,...
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Douglas Heller
Independent Consultant and Recognized Insurance Expert for the...

How does a ZIP code factor into determining risk for auto insurers? Are there more accurate options insurance providers can use to set rates?

David Crockett, PhD
David Crockett, PhD:

Insurance firms use ZIP codes as a proxy for a neighborhood. Postal codes are not an unreasonable proxy for a community, but they do come with some problems. For Black and Latinx consumers, when companies use ZIP codes, they are very likely to be incorporating several factors that probably have nothing to do with how good a person is as a driver or even their propensity to pay their bills on time.

A lot of African American neighborhoods are overpoliced. Many people understand that, but sometimes what I think gets missed is the way they are overpoliced. What we end up focusing on, and rightly so, are acts of violence. But the most common interaction that anyone has with law enforcement is traffic enforcement. When you live in a community that is overpoliced from the start, you know that you will have more interactions for traffic violations. Study after study makes this clear. It's not controversial to say that Black and brown people are ticketed more often for the same kind of behavior as white drivers.

Kalinda Ukanwa, PhD
Kalinda Ukanwa, PhD:

I cannot definitively say what insurers are doing with ZIP codes since I do not have access to their risk assessment methods. What is likely happening is that auto insurers have algorithms that use ZIP codes as one of many predictors of an applicant's insurance risk. The algorithm is probably using information about the individual (e.g., driving record, credit score, vehicle, etc.) as well as the average behavior of groups he is a member of (e.g., residence ZIP code, gender, age, etc.) to predict risks for accidents, auto theft or other damages. ZIP codes may also correlate with the demographics of the residents living in the ZIP code, which in turn can be used to predict risk.

However, what is not clear is whether higher rates of theft, vandalism, accidents or other insurance risks in some ZIP codes are because there truly are more incidents in these ZIP codes or just more reporting to insurance companies of these incidents. For example, lower-income areas may have increased reporting of incidents to insurers because they do not have the ability to pay out of their own pockets for repairs. In higher-income areas, they have that ability, so residents may not report as often to insurance companies in order to avoid higher premiums down the road. A more accurate option for insurers is to look at information about the individual, such as driving record and driving habits, regardless of what other people in his ZIP code are doing.

Do other factors used to set car insurance rates, such as driving record, credit score or vehicle type, disproportionately increase premiums for people of color? In what other ways are people of color at a disadvantage?

David Crockett, PhD
David Crockett, PhD:

Certainly they do, but these are things that are not connected to them being worse drivers or higher accident risks. Many of these things that we are talking about now are the residue of residential segregation. Many people would be astonished to know how high the level of residential segregation is in many cities across the U.S. As metropolitan areas become more diverse with a higher proportion of Black and brown people, residential segregation rises.

In the U.S., white people claim the most resource-rich space. This happens even among white people of modest means. You may be the poorest person on the block, but you live in an area with good schools and maintained roads. On the flip side, Black and brown households of even middle-class standards are often living in the worst kinds of neighborhoods. With this imbalance, you see what a lot of people describe as the "Black tax." Black and Latinx people tend to pay premiums for certain things that are a function of the neighborhood they live in that don't have anything to do with them personally.

It is my understanding that even after we control for things like driving record, credit score or vehicle type, so that we are comparing apples to apples — Sam Jones in one neighborhood and Shaquille Jones in another community — you still see racial differences in premiums. Even when comparing the same driving record, these things are largely a function of the legacy that we have left and are still living with; that is, residential segregation.

Kalinda Ukanwa, PhD
Kalinda Ukanwa, PhD:

Credit score is most likely to have a disproportionate impact on people of color in terms of increasing premiums. Prior research well documents that people of color have lower credit scores, on average, compared to white counterparts, even when all other financial factors are equal. Many institutions use credit scores in their algorithms to predict risk, even if the risk they are predicting has nothing to do with credit risk. It would logically follow that systematically lower credit scores for people of color will translate into disproportionate increases in premiums.

What would effective legislation to limit conscious and unconscious pricing discrimination look like? How would this legislation affect consumers?

David Crockett, PhD
David Crockett, PhD:

I want to stay in my lane because I am an inequality scholar, not a policy scholar. I do talk about policy in my work, but I do not know much about insurance policy. I can say in broader brushstrokes that a lot of this goes back to anti-discrimination policy in housing markets. It's the last thing that happened in the civil rights era, and it was the weakest kind of legislation. It caught a lot of resistance. Consider that many Black and LatinX neighborhoods are in cities that are underfunded and older inner-ring suburbs that are substantially overpoliced. I am very much in the camp of defunding the police and reallocating funds for things that contribute to the quality of life.

In many cities, Black and brown people get virtually all of the jaywalking tickets. Many of these places are infested with speeding traps. That is what those cities have to do to survive because they are underfunded from their state and federal governments. But these things raise a substantial proportion of tax revenue for many cities. But then, Black and brown people end up paying two or three times for this kind of disadvantage in increased insurance premiums. To change it, I am for strengthening anti-discrimination policy. I am less interested in seeing more people go to jail. I am more interested in policy that functions in specific ways. For example, companies should have to identify racial disparity. You have to find where racial inequality exists and do the analysis to understand underlying causes. Companies have no incentive to do that. An insurance company could say, "These things have nothing to do with us. We didn't cause any of these things to happen." It just so happens that while it disadvantages Black and brown consumers, the companies have made extra money. There has to be incentive to understand and analyze underlying causes and then to eliminate them.

Here's an anecdote of what can happen in policy and what everyday people can do. My colleague lives in a neighborhood that is several blocks of fabulous older homes. Those homes have been around for decades. They are all in pristine condition and great houses. A stone's throw from these houses is one of the poorest sections in our entire county. While we were in his home, he talked about being in negotiations with his insurance company over the premiums he was paying for being in that ZIP code. It took several rounds, but he was able to get his premium lower, based in part on what some other people in the area are paying.

Insurance companies would have you believe that their stuff is written down on tablets and carried from the mountain. Like, "This is what our algorithm said, what can we possibly do?" But all of these things are negotiable. This was not just a question of my colleague's negotiating skill, though I am sure he is skilled. In addition to these kinds of premiums, we commonly see that companies can be more attentive to white people's complaints. This is a common fact of doing business in the United States. I am working with a set of retailers right now, on these very issues, revisiting their policies. Companies must be made to be vigilant about these issues.

Kalinda Ukanwa, PhD
Kalinda Ukanwa, PhD:

Legislation that restricts the use of data about protected classes like race and ethnicity would be important. This also goes for restricted use of data that proxies for protected classes, such as ZIP codes. However, legislation should also include the requirement that companies collect data about protected classes (but not use them in their decisions) in order to enable audits of their own service decisions. This would help to detect systemic disparate impact on consumers in protected groups. Furthermore, legislation that includes a requirement for transparency in the algorithms used to make service decisions like insurance premiums would be needed. The net effect to consumers would be fairer insurance rates.

What advice do you have for residents of ZIP codes who may be subject to higher premiums? What steps can drivers take to determine if they are charged a higher premium based on their location instead of driving record?

David Crockett, PhD
David Crockett, PhD:

Shop around. Insurance is one of those things where people can quote you radically different premiums for the same product. Research what you should be paying for your area and negotiate what you can. People must look to see what is going on in their areas around issues like this. One of my favorite organizations that I just became aware of since I have been doing this kind of work is a tiny voluntary association called the Funerals Consumer Alliance. That is a service that most of us do not want to think about. Consequently, people pay radically different prices for the same kind of service. It happens all the time. One of the things members do in the cities they are located in is price out a standard funeral. They print out a booklet and make that available. You can take action as an individual shopper, but we have a whole history in this country of consumer activism where people get together for some of these things we can't do on our own. Your negotiating skills are not better than the insurance company's. But maybe you can get together with other people facing the same kind of issues, and make some change.

Kalinda Ukanwa, PhD
Kalinda Ukanwa, PhD:

Contact your insurer to ask for details on how they arrived at the rate. Ask them what the rate would be with your profile if you lived in a different ZIP code. This may open the way to renegotiating your rate. Also, know your rights based on the state that you live in. For example, California proposition 103 restricts insurers from using ZIP codes in insurance decisions. Finally, consumers may want to look at insurance providers, such as Root Insurance, that offer telematics programs. Telematics programs use a small device installed in your car to report in real time on driving performance. In fact, most major insurers now have telematics programs. These programs use driving history and car usage to set insurance rates instead of predictors like ZIP code and credit score.

What impacts do practices such as charging a higher premium based on a ZIP code have on the long-term financial security of people of color and their families? How does this fit into the landscape of actions that perpetuate poverty among people of color?

David Crockett, PhD
David Crockett, PhD:

This notion of the "Black tax" appears in the cost of everything. It begins to overlap with the criminal justice system in the form of increased parking tickets, traffic tickets and jaywalking tickets. It provides entrée into the criminal justice system and mass incarceration for a lot of people. They arrive there through unpaid parking tickets and speeding violations. Then, they end up driving without a license or insurance or both. This adds up.

Remember the gentleman killed before George Floyd, Philando Castile. There were dozens and dozens of interactions with the police. Ticket after ticket after ticket, but no one drives that poorly. This is a function of the neighborhood. Beyond that, I grew up in North St. Louis. My parents lived a stone's throw from Ferguson, where Mike Brown was killed. It was a feature of everyday life. There are tons of tiny municipalities that make up St. Louis county, and many of them only exist to be speed traps. That is the only reason it's an administrative unit. They don't provide services to citizens. All they do is ticket people. It can ruin your life.

Years before Mike Brown, a guy played basketball with some of his friends at an outdoor court in Ferguson. He was sitting in his car, minding his business. The guy was perfectly legal, no problem sitting there, but he was approached by a police officer, who decided to arrest him and have him charged for making a false statement to a police officer because he reported his name as Mike and not Michael, which was on his driver's license. He was a federal contractor. He lost the federal contract. He lost his license to do federal contracting because you don't have to be convicted to lose your license; you just have to be charged. That man's life was ruined over nothing. This is the stuff that contributes to the racial wealth gap.

Right now, in the U.S., white people have 10 times the net worth of other groups. In Los Angeles, the median white household net worth is about $350,000. That's a pretty significant number. The median net worth of an African American household in Los Angeles is $3,500. The median net worth of Mexican-ancestry households in Los Angeles is $4,000. In Boston, the median net worth of African American households is functionally zero. That means half of the people in the distribution have a negative net worth. These things contribute to the cost that you pay for mortgages. They contribute to being in the criminal justice system and to the rates you pay on credit cards. If you live in a "white" neighborhood and you are just as reckless on the road, it is a near certainty that you will have fewer interactions with the police. You will pay a lower interest rate on a credit card, even when we equalize everything. These small little premiums, sometimes not so small, fit together to create a story of insane inequality.

Kalinda Ukanwa, PhD
Kalinda Ukanwa, PhD:

It has the impact of taking more dollars out of the pockets of people of color. This leaves less for other financial needs in the household. Less available dollars for other financial needs such as food, rent, transportation costs and education means people of color will not be able to purchase as many resources, dollar-for-dollar, as their white counterparts with the same income. This perpetuates poverty and slows social advancement for people of color in the long run.

Do you have any additional comments, findings or thoughts on the subject?

David Crockett, PhD
David Crockett, PhD:

We are in what one of my advisors used to call a "pregnant moment." There are moments in history that you know are going to be important. This is one of those. I hope we don't squander it. A lot of organizations and people in those organizations are sincere. They know there are issues. They know their organization has been part of the problem. How can we fix this? What can we do? They are beginning to look for answers.

I am working with a set of companies right now. One of my co-ops told me that decades ago, he was one of a handful of Black employees at PepsiCo when they took over the Aunt Jemima brand. There has long been opposition to that as an icon in Black America and inside the company. For years, people tried to convince the company that they needed to retire the brand. And that finally happened recently. Things look intractable until they are not. There was a sociologist named William Gamson who said, "Activists rarely understand the probability of success," and on the whole, that is a pretty good thing.

Kalinda Ukanwa, PhD
Kalinda Ukanwa, PhD:

Algorithmic bias in service decisions such as insurance premiums can have not only long-term negative financial impact on consumers, but can also have a long-term negative financial impact on the firm. So many firms use algorithms to make service decisions because they believe the algorithms improve profits. My research suggests otherwise under certain conditions. My paper, "Algorithmic Discrimination in Service," shows that if firms used biased algorithms in service decisions, this can lead to reduced long-term demand and profits because of the word-of-mouth it generates. What is surprising is that the word-of-mouth doesn't even have to be negative, yet the firms can still lose.

What To Do If You Suspect Unfair Car Insurance Rates

Insurance and anti-discrimination laws vary widely from state to state. A University of Michigan study articulated that a “surprising number of jurisdictions do not have any laws restricting insurers’ ability to discriminate (based on) race, national origin, or religion.” This has led to premiums that are not always based solely on driving practices.

If you suspect that you live in a ZIP code with racially influenced car insurance rates, there are ways to speak up and find better rates.

  • File a complaint. In housing and lending, the federal government prohibits discrimination by race, color, national origin, gender, age, religion, marital status, and whether you receive income from public assistance. Car insurance regulation, however, is left to the states, so contacting your state insurance commissioner is the most direct way to have your claims addressed. You can also contact your local congressman or state legislator.
  • Contact the Federal Insurance Office (FIO). In 2016, the agency ruled that affordable auto insurance for low-income and minority communities should equal no more than 2% of the local median income. If you’re paying more than that, your insurance payment is considered unaffordable, which the FIO can investigate.
  • Learn how carriers determine auto insurance rates. A newer model sports car, for example, could cause your auto premiums to skyrocket. Understanding how car insurance companies set rates can help you improve your driving record and lower your premiums.
  • Shop around. The cost of the same type of auto insurance coverage may vary by thousands of dollars depending on where you live. Compare local auto insurance rates in your state, read reviews of insurance companies and ask other drivers in your area if they believe they are being charged fairly for insurance.
  • Ask your insurance agent about discounts. Finding the best rates for car insurance may include discounts for being a good student, owning a low-mileage vehicle, taking a defensive driving class, raising your deductible, bundling your homeowners and auto insurance and, of course, having a good driving record.

Equity in Car Insurance and Beyond

Data is a vital tool to promote social and financial equality. Car insurance keeps society accountable and reduces risk, and as such, insurance payments based on individual risk and driving history can help keep drivers safe and covered in the event of an accident. The NAIC’s formation of a committee dedicated to researching and promoting equality is one of many steps being taken to examine and improve structural discrepancies across the country.

As more communities and companies confront unequal structures that financially impact communities of color, leveraging comprehensive data can serve as a catalyst for change that promotes equality and safety for all drivers.

Full Data Set

The following table summarizes the key data of all 69 cities where the data set included 10 or more ZIP codes.

City
# ZIPs
Correlation
Premium Increase
Premium % Increase
ZIP Code vs. Speeding Ticket
ZIP Code vs. Credit Score

Baton Rouge, LA

12

-0.963

$195

9.60%

30.9%

**

Birmingham, AL

13

-0.942

$64

5.60%

24.4%

23.4%

Stockton, CA

10

-0.937

$99

7.50%

16.3%

*

Oakland, CA

12

-0.925

$360

28.70%

55.7%

*

Milwaukee, WI

25

-0.916

$364

43.60%

101.2%

176.2%

Arlington, TX

12

-0.909

$106

10.60%

78.6%

**

St. Louis, MO

27

-0.895

$439

43.70%

140.6%

163.0%

Omaha, NE

18

-0.892

$176

23.20%

123.4%

**

Chicago, IL

49

-0.884

$257

26.30%

80.8%

111.5%

Baltimore, MD

19

-0.884

$570

37.70%

150.4%

125.0%

Albuquerque, NM

15

-0.876

$106

9.30%

48.4%

48.8%

Atlanta, GA

29

-0.872

$365

30.60%

77.4%

124.9%

Tacoma, WA

10

-0.867

$48

4.40%

17.8%

**

Kansas City, MO

16

-0.861

$231

24.90%

97.0%

100.1%

Louisville, KY

24

-0.858

$656

51.70%

199.7%

152.5%

Columbus, OH

23

-0.855

$70

10.50%

34.8%

49.0%

Houston, TX

86

-0.847

$267

25.40%

173.3%

78.4%

Cleveland, OH

24

-0.833

$162

27.10%

81.1%

135.2%

Phoenix, AZ

35

-0.830

$344

33.50%

103.2%

105.9%

Colorado Springs, CO

16

-0.829

$61

6.00%

25.1%

24.4%

Tucson, AZ

27

-0.827

$114

12.80%

42.8%

38.8%

Pittsburgh, PA

18

-0.824

$93

12.00%

57.9%

51.3%

Seattle, WA

28

-0.819

$148

15.30%

53.7%

68.8%

Fort Worth, TX

26

-0.813

$87

9.00%

67.6%

31.3%

Salt Lake City, UT

19

-0.812

$108

11.80%

40.6%

36.4%

New Orleans, LA

14

-0.809

$891

38.40%

103.4%

115.2%

Richmond, VA

11

-0.806

$74

10.30%

38.3%

**

St. Paul, MN

21

-0.806

$348

35.50%

98.2%

135.1%

Philadelphia, PA

37

-0.800

$479

31.00%

124.5%

99.0%

San Francisco, CA

20

-0.792

$254

19.10%

39.4%

*

Long Beach, CA

11

-0.785

$284

20.70%

39.7%

*

Las Vegas, NV

36

-0.771

$398

26.50%

74.6%

108.5%

Austin, TX

30

-0.766

$116

12.70%

93.4%

41.7%

Fort Wayne, IN

11

-0.766

$29

4.40%

15.6%

20.4%

Toledo, OH

11

-0.765

$30

4.10%

14.0%

21.6%

Tampa, FL

23

-0.764

$447

21.90%

56.0%

79.8%

Charlotte, NC

19

-0.758

$193

24.40%

48.4%

272.6%

Minneapolis, MN

35

-0.753

$349

36.30%

96.0%

144.6%

Orlando, FL

25

-0.743

$293

18.60%

49.9%

65.8%

Buffalo, NY

17

-0.739

$260

19.70%

68.7%

**

Mesa, AZ

13

-0.738

$120

12.30%

42.1%

36.5%

Tulsa, OK

16

-0.720

$68

6.80%

18.5%

29.5%

Raleigh, NC

12

-0.716

$76

10.70%

21.7%

98.2%

Fresno, CA

13

-0.695

$96

7.70%

16.6%

*

Memphis, TN

21

-0.692

$132

13.70%

51.4%

52.0%

Portland, OR

25

-0.682

$264

25.50%

73.4%

144.1%

Dallas, TX

37

-0.663

$225

21.50%

151.3%

65.1%

Indianapolis, IN

29

-0.653

$79

11.20%

36.8%

48.1%

Nashville, TN

12

-0.643

$64

8.30%

37.4%

35.5%

Miami, FL

45

-0.642

$502

24.20%

62.0%

81.2%

San Jose, CA

24

-0.642

$206

17.60%

35.7%

*

Corpus Christi, TX

10

-0.619

$63

6.20%

48.4%

20.1%

Jacksonville, FL

21

-0.573

$96

6.40%

17.5%

21.5%

San Antonio, TX

40

-0.569

$90

8.90%

67.8%

29.7%

Wichita, KS

14

-0.568

$43

5.20%

20.8%

23.6%

New York, NY

136

-0.566

$1,816

96.90%

176.0%

145.0%

Bakersfield, CA

10

-0.566

$81

6.40%

14.2%

*

Sacramento, CA

22

-0.553

$285

22.00%

45.2%

*

Oklahoma City, OK

19

-0.541

$45

4.50%

12.9%

20.2%

Cincinnati, OH

24

-0.540

$80

12.40%

39.7%

55.6%

San Diego, CA

29

-0.479

$201

17.40%

36.8%

*

El Paso, TX

17

-0.447

$35

3.70%

29.6%

12.8%

St. Petersburg, FL

14

-0.438

$39

2.00%

5.5%

7.2%

Denver, CO

32

-0.350

$146

14.20%

58.4%

51.0%

Detroit, MI

18

-0.294

$710

19.00%

23.2%

43.6%

Spokane, WA

11

-0.175

$27

3.30%

12.9%

**

Honolulu, HI

11

0.000

$0

0.00%

0.0%

*

Lexington, KY

10

0.052

$9

0.80%

4.1%

3.3%

Los Angeles, CA

49

0.128

$699

43.80%

80.5%

*

Data Description

Correlation: ZIP code demographics vs. car insurance premiums.

Premium Increase: 5 most expensive ZIP codes vs. 5 least expensive ZIP Codes.

Premium % Increase: 5 most expensive ZIP codes vs. 5 least expensive ZIP codes.

ZIP Code vs. Speeding Ticket Penalty: The premium increase as a percentage of the increased premium associated with a speeding ticket. A 100% value means that the two are equivalent.

ZIP Code vs. Credit Score Penalty: The premium increase as a percentage of the increased premium associated with a credit score 55–60 points lower. A 100% value means that the two are equivalent.

*Indicates states where credit scores are not allowed to be utilized as a rating factor in setting car insurance premiums.

**Indicates cities where insufficient data was available to calculate the impact.

Methodology

Using data received from Quadrant, MoneyGeek analyzed 2,000 ZIP codes in 126 cities across America comparing a ZIP code’s white population and auto insurance premiums. The analysis reviewed premiums holding all other factors equal. Each ZIP code was analyzed using the scenario of a 40-year-old male with a 2010 Toyota Camry and full auto coverage (100/300/100 comprehensive and collision with a $1,000 deductible).

MoneyGeek also used data from Quadrant to analyze the increased premium costs associated with a credit score decrease or a speeding ticket for the same driver profile in these cities.

MoneyGeek utilized the most recent five-year population estimates, including demographic data by ZIP code from the U.S. Census Bureau (census.gov).

About Poonum Desai


Poonum Desai headshot

Poonum Desai is a former economics professor now turned video journalist and author. She is the author of Sincerely, Life: A Conversation to Find Yourself and the host of multiple Instagram Live series. Before she was an economics professor, she was a personal financial literacy coach at The University of Texas at Dallas (UT Dallas). During her time at UT Dallas, she was an Archer Fellow, a Graduate seminar instructor, and worked on Capitol Hill for Congresswoman Eddie Bernice Johnson's office. In her free time, Poonum loves to work out, go to concerts (when it is safe again to do so), and spending time with family.


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