Household financial access has gained the interest of policymakers and practitioners worldwide. For example, the World Bank Group (i.e., the World Bank and International Monetary Fund) is working to facilitate household financial access for one billion people across the globe through targeted interventions by 2020 (The World Bank 2016). Research supports this wide interest; studies indicate that household financial access can lead to better outcomes for individuals and economies, including greater investment in education and businesses, as well as better heath and lower inequality (White House Council of Economic Advisers 2016).

A starting point for household financial access is the ownership and use of appropriate and safe financial products and services, such as transaction (e.g., checking account) and saving (e.g., savings account) functions (Friedline and Rauktis 2014). Increasingly, household financial access is being viewed as multi-dimensional to include ownership and use of financial products and services beyond basic functions (Demirgüc-Kunt et al. 2008; The World Bank 2017). The concept of household financial access can be expanded to include ownership of credit products (i.e., credit cards and consumer, business, and mortgage loans) and retirement and investment vehicles from formal financial institutions (i.e., banks and credit unions) (Friedline et al. 2015). Household financial access holds the potential to provide needed resources to households during times when their income is disrupted or when they experience challenges with their consumer credit record due to increased expenses. Without basic financial access to bank accounts, households are relegated to using cash or costly Alternative Financial Services (AFS) (e.g., check cashing, payday loans, and money orders) for their banking needs (FDIC 2016; Friedline and Kepple 2017).

U.S. consumer policy promotes household financial access as important to overall financial well-being. Examples include the Community Reinvestment Act’s (CRA) focus on broadening credit and service access across bank service areas, credit card regulation, and the recent creation of the myRA retirement program (although recently discontinued by the current federal administration). However, minimal evidence exists about the usefulness of household financial access when households experience financial challenges. Specifically, evidence about the relationship among household financial access, a large income drop, and credit record status is slim. The purpose of this study is to add to the literature about the usefulness of household financial access to mediate the relationship between a large income drop and credit record status in the U.S. Using the 2015 National Financial Capability Study (NFCS), this study examines the association between household financial access, a large income drop, and credit record status. In particular, the study has the following two research questions: (1) Is there an association between a large income drop and credit record status? And (2) does household financial access mediate the relationship of a large income drop and credit record status?

These research questions have important implications for consumer policy. A range of policy and practice efforts of financial institutions and public and private entities promote household financial access for several reasons, including the idea that household financial access provides a cushion when households have unexpected financial needs to be able to continue to meet their basic needs and avoid negative financial outcomes. This research that investigates the potential mediation relationship between a large income drop and credit record status informs those efforts and provides evidence about the importance of household financial access. Finding of a mediation relationship would provide support for the notion that household financial access provides an important buffer between a sudden drop in income and negative financial outcomes and provide evidence to support consumer policy that supports household financial access.

Background

Conceptual Framework—Household Financial Access

Household financial access is vital to households in several ways. First, access provides for smoothing of consumption when income drops or protecting credit record status when expenses increase by providing resources that can be utilized when needed to ensure material needs are met and debts can be paid on time (King 2014). Second, household financial access provides a mechanism for investment in human and productive capital, by providing resources that can be used for education and training, small business, and similar assets that allow for accumulation of wealth to be used for household development (Sherraden 1991). Third, household financial access allows for the management of risk of uncertainties; so, households can plan for the future with the knowledge that they can handle unknown financial challenges (King 2014).

Household financial access is facilitated by both household financial knowledge about products and services, and an enabling environment, such as having reasonable, predictable, and lower cost accounts and loans, convenience, proximity to financial institutions, and access to technology (Allen et al. 2016; FDIC 2016; Friedline and Despard 2017). Financial knowledge is gained through both financial socialization (i.e., education gained during childhood from parents or guardians), as well as from formal financial educational experiences in education and workplace settings (Sherraden 2013; Wagner and Walstad 2018).

Consumer Credit Record and a Large Income Drop

The consumer credit record (also known as credit report) is the most commonly used tool in consumer banking and lending. The majority of Americans have a credit record, which is a record of borrowing money and paying debts, with the three nationwide credit reporting agencies (National Consumer Law Center 2016). Information in the credit record, including number of credit lines and payment history, is used in algorithms to create a credit score. To encourage timely repayment, many creditors report delinquent and non-payments on outstanding debt and monthly payments to the nationwide credit reporting agencies. Due to disruption in income, increased expenses, or other reasons, lack of payments on current debts (e.g., auto, home, student, and consumer loans) and other monthly bills (e.g., rent, utilities, and telephone bills) in a timely fashion negatively impacts household credit records (Brevoort et al. 2015; Consumer Financial Protection Bureau 2017). As a result of federal policy change, starting in 2003, consumers have free, periodic access to their credit records from the credit bureaus and can see the status of their accounts. In addition, some credit card companies are making consumer credit scores available for free. Given the access and increased consumer knowledge about credit scores, many consumers have a good sense of their credit score. Research has shown that consumer perception of their credit score is fairly a good indicator of their actual credit score (Perry 2008). Changes in credit record can also influence earned income, due to the practice of employers checking credit records when making decisions about hiring, promotion, and related decisions (Traub and Mcelwee 2016).

Household Financial Access and Credit Record

Credit records and credit scores are often used by potential lenders to gauge financial risk, make credit decisions, and set the terms of the credit (e.g., interest rate, length of loan) (Brevoort et al. 2015; Consumer Financial Protection Bureau 2015), which can impact financial access. For example, some banks and credit unions check credit records when deciding whether to open a new bank account for a prospective customer. In addition, the credit record is typically used to decide about whether to lend and the cost of credit for credit cards, small dollar consumer loans, home and auto loans, as well as home and auto insurance policies (National Consumer Law Center 2016). During periods of large income drops that negatively affects consumer’s ability to pay within 30 days of the due date, adverse information may be added to their credit record and reduce future household financial access by increasing the cost of credit and insurance. Even if income is stable, increase in expenses can negatively impact the credit record due to late or non-payment of credit obligations, which affects household financial access.

Household Financial Access and a Large Income Drop

Experiencing a significant income drop is a fairly common occurrence for many U.S. households. The 2015 FINRA Financial Capability data indicates that 22%, or nearly a quarter of Americans, experienced an unexpected “large drop in income” (self-defined) during the past year (FINRA Investor Education Foundation 2016). These income drops can occur due to reduced earnings from household changes (e.g., divorce, death, illness, and birth of a child), reduced public income (i.e., loss of eligibility or reduction in public benefits), or reduced private income (i.e., loss of financial support from friends, family, or charitable organizations) (Holt 2016; Mills and Amick 2010). During periods when income does not meet regular household expenses, households may experience material hardship through deprivation of basic needs, increase debt burden or utilize other financial resources in responding to financial needs (Bartfeld and Collins 2017; Sherraden 1991). Ideally, households have liquid assets on which to draw during these periods to pay their bills, meet their basic needs, and avoid damage to their credit through unpaid bills. Unfortunately, many households do not have adequate personal resources to buffer the effects of large income drops (Pew Charitable Trusts 2015). The typical family would need $9000 more in liquid savings to reach the level needed during an income drop (Pew Charitable Trusts 2015). Research has demonstrated that having liquid assets up to $1,999, as compared to having no liquid assets, significantly reduces the incidence of multiple hardships by 5.1% points, and larger effects are found with larger asset holdings (McKernan et al. 2009).

The majority of research in this area suggests that financial assets provide a cushion when income drops to buffer against material hardship (Gjertson 2016; McKernan et al. 2009; Mills and Amick 2010; Pew Charitable Trusts 2015) and that household financial access is the gateway for both accumulation and protection of financial assets (Friedline 2016; Friedline and Freeman 2016). For example, having access to a bank account is associated with higher amounts of savings (Friedline et al. 2014) and decrease in young-adult households’ accumulated unsecured debt (Friedline and Freeman 2016). Resources utilized by households during these times include drawing on their emergency savings (Baek and DeVaney 2010; Gjertson 2016; McKernan et al. 2009), borrowing from friends and family, increase work (Bartfeld and Collins 2017), and obtaining small dollar consumer loans from bank and non-bank sources (Baek and DeVaney 2010; Chase et al. 2011; Friedline and Freeman 2016; Lusardi et al. 2011; Rowlingson et al. 2016).

Households may also use less-liquid assets to meet their consumption needs and payment and debt obligations, such as tapping into savings in retirement accounts, equity in their homes, and investments in stocks, bonds, and mutual funds. Although more difficult to access, having retirement accounts, home mortgages, and investments are the vehicles to accumulate assets that can, when needed, generate cash income to smooth consumption, pay regular bills on time, and avoid negative impact on their credit record. For example, researchers have found evidence that people also draw on their retirement or pension plans (Argento et al. 2015) and tap into other investments (Baek and DeVaney 2010). People may also utilize home equity lines of credit (Bi and Montalto 2004; Lerman and Zhang 2014), sell assets (Lusardi et al. 2011), and obtain policy loans from life insurance plans (Liebenberg et al. 2010). However, using 2008 SIPP data, Birkenmaier et al. (2016) found no evidence that financial access, measured as bank account ownership, buffered food hardship for the unemployed during the Great Recession.

Rationale for This Study

The majority of previous research on assets as a cushion during household economic stress (Friedline and Freeman 2016; Gjertson 2016; McKernan et al. 2009) suggests that household financial access could provide a cushion when income unexpectedly drops to avoid economic hardship, non-payment of bills, and a resulting poor credit record. For example, Keating (2012) found that those without assets have higher rates of material hardship during economic shocks. The strongest relationship between assets and material hardship was found for those with lowest incomes. While there was some buffering between assets and material hardship, few results were statistically significant. Lerman and Zhang (2014) found that housing status provided a buffer from material hardship during the Great Recession, a period of high unemployment. However, other evidence suggests that household financial access may not provide a buffer (Birkenmaier et al. 2016). Studying the association between a large income drop, financial access, and credit record status can provide unique insights about the role of financial access to buffer the relationship between a large income drop and credit record status.

The Current Study

Using a U.S. national dataset, this study focuses on the association between a large income drop, household financial access, and credit record status. While previous studies have found assets, including household financial access, to be important buffers during periods of negative income disruption (Friedline and Freeman 2016; Guo 2011; Lim et al. 2010; Mills and Amick 2010), most have used “banked status” as a sole indicator (Ardic et al. 2013; Birkenmaier et al. 2016; Honohan 2008; White House Council of Economic Advisers 2016). Although studies focused on non-U.S. populations have used more comprehensive measures of household financial access, such as adding insurance, mobile banking, micro credit, and consumer financial education, and other measures to bank account (Cnaan et al. 2012; Gutiérrez and Teshima 2016; Honohan 2008; Ledgerwood 2013), few have specifically used a combination of measures for U.S. household financial access, including checking, savings, retirement, mortgage, and investment accounts, and number of credit cards, nor in combination with credit record as a dependent variable (Birkenmaier et al. 2017). Using a more comprehensive measure of U.S. household financial access may provide a broader picture of the role of household financial access in periods of income drops or credit challenges. The present study fills these gaps. This study investigates the extent to which a buffering relationship exists, suggesting the usefulness of household financial access during period of financial challenge when income drops or credit challenges are present. Policy recommendations are discussed.

Methods

Sample and Measures

This study investigated the association between credit record, a large income drop, and household financial access using a nationally representative sample from the 2015 National Financial Capability Study (NFCS). The survey was funded by the Financial Investor Regulatory Authority (FINRA) Investor Education Foundation and conducted by the Applied Research and Consulting. Data was gathered via a national online survey of 27,564 American adults from the general population. Respondents were drawn using non-probability quota sampling from established online panels consisting of millions of individuals who have been recruited to join and are offered incentives in exchange for participating in online surveys. National weights were used to be representative of the national population in terms of age, gender, ethnicity, education, and Census Division according to the American Community Survey from the U.S. Census. This publicly available dataset contains individual-level data about financial knowledge and a range of financial behavior.

Household financial access indicators included whether participants had a checking account, a savings account, employer-sponsored retirement plan, mortgage or home equity loan, investment accounts other than retirement plan, and number of credit cards. A large income drop was measured by the question of “In the past 12 months, have you [has your household] experienced a large drop in income which you did not expect?” (Yes/No). Credit record was measured by the question, “How would you rate your current credit record?” (very bad, bad, about average, good, and very good). Financial socialization was measured by the question, “Did your parents or guardians teach you how to manage your finances? (Yes/No). Financial knowledge was a composite variable that is the summation of correct answers to five financial knowledge questions. The questions asked about compound interest, inflation, principles related to risk and diversification, the relationship between bond prices and interest rates, and the impact that a shorter term can have on total interest payments over the life of a mortgage. The total number of correct answers ranged from 0 to 5. Financial education was classified into the following three categories: not received financial education even it was offered by a school or college, or a workplace, received financial education offered by a school or college, or a workplace, and no financial education offered in the past. The responses to this variable were recoded as received financial education regardless of who provided, not received, or preferred not to say. Sociodemographic variables included gender, age, race, marital status, education, household income, and employment status. Age was classified into 18–24, 25–34, 35–44, 45–54, 55–64, and 65 or older. Race was classified into White and non-White. Marital status was recoded as single, married, and separated or divorced or widowed. Education was recoded as less than high school or General Educational Development (GED), high school graduates, college education, and post graduate. Income was divided into less than $15,000, $15,000–$35,000, $35,000–$50,000, $50,000–$75,000, and at least $75,000.

Statistical Analysis

Path analysis was used to examine associations among credit record, a large income drop, and financial access factors. The ordinal dependent variable of credit record was regressed on a large income drop, household financial access indicators, financial knowledge, financial education, financial socialization, and sociodemographic variables using an ordinal logistic regression. The probability of high credit record was estimated compared to that of lower credit record. In the same model, the number of credit cards was regressed on a large income drop, financial knowledge, financial education, financial socialization, and sociodemographic variables using an ordinal logistic regression. All other household financial access indicators (checking/savings account, retirement plan, mortgage or home equity loan, and investment accounts other than retirement plan) were regressed on a large income drop, financial knowledge, financial education, financial socialization, and sociodemographic variables using a binary logistic regression. A conceptual model is depicted in Figure 1.

Fig. 1
figure 1

A conceptual model of credit record predicted by large income drop, household financial access factor, and other covariates

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The two types of logistic regression models were conducted simultaneously using MPlus 7.4 (Muthén and Muthén 2015). MPlus used full-information maximum likelihood (FIML) to handle missing values on categorical independent variables from complex survey sample (Muthén and Muthén 2015). Regression coefficients and standard errors (SE) as well as odds ratios and 95% confidence intervals were reported to quantify the associations.

Results

Table 1 shows sociodemographic information and other characteristics about the sample by a large income drop. There were more women than men in the subsample with a large income drop. The age distribution was relatively younger in the group with a large income drop than the other group. Whites were more likely to be in the subsample without a large income drop. There were more participants with lower educational level and less income in the group with a large income drop. They were also more likely have a single marital status and be without a full-time job. Participants in the group with a large income drop were more likely to report their credit as very bad, bad, or about average. Participants with better financial knowledge (e.g., > 3 points) were more likely to be in the no income drop group than those who scored lower. Financial education and financial socialization were approximately equally distributed in the two groups.

Table 1 Sample characteristics
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Household Financial Access Indicators

Table 2 shows the distributions of household financial access indicators. The vast majority of the participants had checking and savings accounts. More than 50% of the participants had the employer-sponsored retirement plan. Approximately one-third of the participants had investments other than their retirement plan. Over one-third of the participants had mortgage or home equity loan. Approximately one-fifth of the participants did not have a credit card. About half of the participants had one to three credit cards. A bit over a quarter of the participants had four or more credit cards.

Table 2 Proportions and counts for household financial access indicators
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Figure 2 highlights estimated logistic regression coefficients among associations of credit record, household financial access indicators, and a large income drop, after controlling for financial knowledge, financial education, financial socialization, and sociodemographic variables using a path analysis. Checking account, retirement plan, and mortgage/home equity loan were removed from the final model since those variables were not statistically significant. The remaining household financial access indicators, savings account, other investment accounts, and number of credit cards, were significantly positively associated with credit record, suggesting that greater household financial access (i.e., having a savings account, investment account, and more credit cards) was significantly associated with better credit record, after controlling for other covariates. The estimated regression coefficients ranged from 0.44 to 0.69, and they were all statistically significant (p < 0.05). A large income drop was negatively associated with a savings account (β = − 0.13, p < 0.05), suggesting that participants with a large income drop were less likely to have a savings account. A large income drop was positively associated with other investment accounts (β = 0.18, p < 0.05) and number of credit cards (β = 0.10, p < 0.05), suggesting that participants with a large income drop were more likely to have other investment accounts and more credit cards. Therefore, household financial access indicators mediated the relationship between a large income drop and credit record. The indirect effect of a large income drop on credit record through the savings account was − 0.09 (i.e., − 0.13 × 0.69). The indirect effect of a large income drop on credit record through other investment accounts was 0.12 (i.e., 0.18 × 0.68). The indirect effect of a large income drop on credit record through the savings account was 0.04 (i.e., 0.10 × 0.44). The direct effect of a large income drop was indicated by the association of a large income drop with lower credit record (β = − 0.67, p < 0.05) after controlling for other covariates. The total effect of a large income drop on the credit record is the summation of direct and indirect effects. Thus, investment accounts and having credit cards reduced the overall effect of a large income drop on the credit record and having a savings account increased the overall effect of a large income drop on the credit record when other covariates were held constant.

Fig. 2
figure 2

Cumulative logit model for the self-rated credit record predicted by a large income drop, household financial access factors, and other covariates. Note: *p < 0.05. The regression coefficients and (standards errors) are regression coefficients adjusted for all other covariates included in the logit model

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Table 3 shows the more detailed results from the final model as shown in Figure 2. Better financial knowledge was positively associated with credit record (OR = 1.09, p < 0.05) and all financial access indicators. Participants who did not participate in the financial education offered by a college, school, or workplace where they attended did not rate their credit record differently from those who participated in the financial education. However, they were positively associated with all three household financial access indicators. Participants who preferred not to say if they participated in the financial education were less likely to have other investment accounts (OR = 0.80, p < 0.05). Financial socialization was associated with a better credit record (OR = 1.45, p < 0.05) and greater household financial access.

Table 3 Logistic regression results for self-rated credit predicted by financial access factors, a large income drop, financial background, and demographic variables
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Discussion and Implications

These results suggest that household financial access provides a mediation effect in the relationship between a large income drop and credit record status. Consistent with expectations and previous research (Gjertson 2016; McKernan et al. 2009; Mills and Amick 2010; Pew Charitable Trusts 2015), household financial access, measured by use of savings, credit, and investments, buffers the relationship. Retirement plan and mortgage/home equity loan were not significant, which it may be because those were less liquid and less likely to mediate a large income shortfall. Therefore, the extent to which households have financial access while experiencing a large income drop or credit challenges appears to make a significant difference in how a large income drop and credit record status are related to one another.

Other major results are consistent with previous findings. First, household financial access is a significant and positive predictor of credit record status. Thus, consumers’ use of saving accounts, credit cards, and investment accounts significantly impacts their credit record. Second, findings suggest that a large income drop has a direct negative effect on credit record status. This finding suggests that a significant drop in income affects households’ ability to provide on-time payment for payment obligations. Third, financial education, financial knowledge, and financial socialization have positive associations with financial access, suggesting long-term benefits of household financial access to financial knowledge, education, and socialization. Financial knowledge and socialization have positive associations with credit record, suggesting the importance of building knowledge for optimal credit behavior (Wagner and Walstad 2018; Woodyard et al. 2017).

The evidence that household financial access buffers the relationship between a large income drop and credit record suggests that some aspects of household financial access act as a strong financial cushion to interrupt the negative impact of a large income drop on credit record and credit record challenges on an income drop. Households use savings accounts, credit cards, and investment vehicles during income or credit challenges. Savings accounts are the most liquid and have a strong, positive effect on the credit record. However, people with a large income drop were less likely to have a savings account. Thus, the buffering effect of this financial service is less likely to be used. They may also have little in the account; using recent Survey of Consumer Finances (SCF) data on a U.S. sample, the White House Council of Economic Advisers (2016) found that the median value of bank accounts, adjusted for inflation, has on net been flat since 1989. The use of credit cards is also highly liquid and has a strong positive effect on credit record. Investments are less liquid and have a strong positive effect on credit record. As noted, checking accounts, retirement plans, and mortgage and home equity loans were not significant in the model, suggesting that consumers do not find them as useful in situations of large income drop. It can be difficult and sometimes expensive to access cash from retirement savings and home equity loans. Time, fees, and penalties may present a barrier to accessing funds in a timely manner, and households may opt to utilize savings account, credit cards, and investments rather than use these other options, in hopes that they may recover rather quickly.

It should also be noted that consumers may tap into other buffering mechanisms, such as government tax credits, unemployment and other income support benefits, as well as friends and family, to buffer against negative impacts. For example, in the U.S., during the Great Recession of 2008–2009, increases were seen in the use of unemployment benefits (Vroman 2011), the Earned Income Tax Credit (Mattingly and Kneebone 2012), and nutrition program (SNAP program) benefits (Zedlewski 2011). Thirdly, consumers may borrow at higher rates from lenders, such as Alternative Financial Services (AFS) providers, during periods of income drop. The use of AFS providers has grown significantly in recent years, as consumers are attracted to more convenient service, a product mix that often meets their need, and more predictable costs (Mills and Monson 2013; Servon 2017).

Practice Implications

Practice innovations are underway by the private and public sectors to improve household financial access toward making it more meaningful and relevant to populations experiencing income drops and credit challenges. For example, there are several different efforts underway to make bank savings and checking accounts more accessible and useful. First, innovative U.S. banks and credit unions are offering several products to appeal to their low-income customers and communities. Some offer “second chance” bank accounts with low and transparent fees for those who have had account trouble in the past (Rengert and Rhine 2016). Others offer low- or no-fee transaction accounts, no- or low-fee general purpose reloadable prepaid cards, and affordable short-term consumer loans with lower interest rates (Rengert and Rhine 2016). Innovative firms are creating different credit-scoring models that take into account a wider range of information about payment behavior and could help low-income households gain easy access to more affordable credit. New credit cards are being marketed to households with poor credit and in need of short-term consumer loans that provide information about pricing upfront, rather than having hidden fees (Servon 2017).

In addition, some nonprofit organizations, such as the Mission Asset Fund based in San Francisco California, are piloting ways to improve consumer credit through reporting payments made in “lending circles,” consumer-driven approaches to creating accessible loan funds by leveraging social capital and small amounts of consumer savings (Mission Asset Fund 2014). A national foundation, Cities for Financial Empowerment, is promoting household financial access through the promotion of municipal government involvement in financial access efforts, such as providing local government-sponsored offices that offer free financial advice and access to relevant financial products. They also promote the Bank On efforts across the country, which are local coalitions to promote bank accounts that meet specific standards for safe and affordable accounts for the un- and underbanked populations (Cities for Financial Empowerment 2015).

Policy Implications

These results are important on a broad scale to consumer policy related to financial access. Governments across the world are grappling with widening poverty as well as growing income and wealth inequality. Policy efforts to promote and facilitate household financial access toward the goal of financially inclusive societies are one response to these challenges. Due to the complexity of the financial system and plethora of actors, a coordinated and sustained effort is needed to promote household financial access at the national level. Since 2010, over 55 countries have committed to financial access for their citizens and over 30 have launched or are developing a national strategy for financial access (The World Bank 2017). These national strategies help to systematically accelerate the level of household financial access through measurable goals, implementation strategies, and timetables (Fernando and Newnham 2015). Development of a U.S. strategy for financial access could promote valuable ideas and needed resources to expand access to safe and affordable financial products that serve as cushions when income drops or credit challenges appear. Under the Obama administration, the U.S. Treasury participated in several efforts to promote national household financial access (White House Council of Economic Advisers 2016). Continuation and deepening of a government commitment to financial access could well serve both households and the national economy.

Another area of consumer policy related to financial access is the interaction with the financial technology (“fintech”) sector. This rapidly growing sector is developing new approaches to products and services using technology platforms and smartphone technology (White House Council of Economic Advisers 2016). Thousands of these technology-driven nonbank companies are using technology, such as through the use of applications (“apps”) on smart phones, to provide easy ways to pay for goods and services and move money. While these applications do not directly impact household financial access yet, the field is growing so rapidly that the U.S. federal government is considering creating a new type of charter, a special purpose national bank charter, to allow fintech companies to operate independently of banks (Office of the Comptroller of the Currency 2016) to allow even more rapid research and development to deliver products and services to the marketplace. These technologies are in the early stages of testing and use here in the U.S., but they hold promise for the future, given the high rate of smartphone usage, even among lower-income consumers (Larrimore et al. 2015).

Other important work that impacts the relationship between income drop and credit record includes policy work to limit the use of credit records for employment purposes. Recent evidence suggests that about half of U.S. employers use credit checks in hiring decisions, which can create barriers to employment opportunities, exacerbate racial discrimination, and lead to invasions of privacy (O’Brien and Kiviat 2018; Traub and Mcelwee 2016). Eleven U.S. states and many cities have passed laws limiting the use of employment credit checks, which has led to increasing employment among job applicants with poor credit (Clifford and Shoag 2016). Many states have introduced similar legislation. However, for those with such laws, fewer exemptions, more vigorous enforcement, and public education about the laws would render the laws more effective (Traub and Mcelwee 2016).

Also, at the federal level, the Consumer Financial Protection Bureau (CFPB) is leading the way to promote meaningful financial access through regulation and oversight. In recent years, the CFPB has been moving forward to provide additional oversight of a variety of AFS with new rules applicable to prepaid debit cards (Silberman 2016a), payday lending (Silberman 2016b), and international remittance transfers (Consumer Financial Protection Bureau 2013). If enacted and enforced, these federal developments will assist in efforts to widen household financial access through safe, more affordable products.

Limitations

The findings of this study mainly show correlational association. Using cross-sectional data, we may not claim the causal impacts of household financial access and credit record status. More research is needed with longitudinal data to confirm these findings. However, the survey question asks about a large income drop that occurs within the past 12 months, and the respondent is asked about current credit record status; therefore, a large income drop precedes the assessment of the credit record. The respondent has provided their perception of their credit record, based on their payment history. Secondly, the dynamics of household financial access could be more complicated than was measured in the study. We were not able to include the cost of investment, bank accounts, or other types of financial assets. Some important predictors that could be tied to both a large income drop and household financial access, such as mental health status, are not included. Thirdly, other models may more accurately portray the relationship among the variables.

Conclusion

This study concluded that household financial access and a large income drop impact credit record status for the U.S. general population. Additionally, household financial access mediates the relationship between a large income drop and credit record status. Evidence from this study provides support for policy-making efforts to make household financial access more meaningful for all consumers, given that it is associated with credit record status. Future efforts should consider ways to further increase the relevancy of household financial access, especially more liquid products, such as savings in bank accounts. While innovation is important to create financial products and services that meet the consumer needs, regulation and oversight are needed to promote the usefulness of available products and services. Further policy and practice work are needed to make household financial access (i.e., savings and checking accounts, investments, credit cards, mortgage, and retirement accounts) even more responsive to the needs of households experiencing financial challenges.