Campus Affinity Card Agreements Under the CARD Act: Portfolio Scale, Governance, and the Limits of Transparency

Abstract

This study examines campus affinity card agreements under the Credit Card Accountability, Responsibility, and Disclosure (CARD) Act, focusing on how portfolio size, new account openings, and institutional governance affect issuer payments. Using cross sectional data from 6145 issuer institution agreements reported to the Consumer Financial Protection Bureau (CFPB) in 2022, the analysis employs descriptive statistics, correlation tests, and multivariate regression models to identify predictors of payment volume. Results show that total open accounts strongly predict issuer payments, while new account openings exhibit a weak positive bivariate correlation but exert a modest negative effect in multivariate models once portfolio scale and institution type are controlled for. Foundations received the highest average issuer payments, followed by hybrid organizations and universities. This pattern reflects differences in governance structure, administrative capacity, and bargaining leverage. Transparency requirements under the CARD Act reveal broad patterns but omit incentive timing and interchange revenue, limiting full accountability. This is among the first large-scale empirical analyses of CFPB’s affinity card dataset, advancing understanding of equity in campus credit markets and offering policy relevant insights for regulators and administrators.

1. Introduction

The expansion of affinity card programs on college and university campuses in the United States represents a significant frontier in higher education finance. Over the past two decades, financial institutions have forged partnerships with campus entities, ranging from student governments, Greek organizations, and alumni associations to foundations and athletic departments. These partnerships include the marketing of credit cards bearing institutional logos, and they come with the promise of dual benefits. Affinity cards are co-branded credit cards issued through partnerships between financial institutions and organizations such as universities, alumni associations, or nonprofits. These cards typically feature the institution’s logo and branding and offer benefits to both the cardholder and the affiliated organization, such as per-account payments, interchange revenue sharing, or promotional incentives. The institution promotes the card to its members or constituents, while the issuer gains access to a targeted customer base with shared interests or affiliations (AccountingInsights Team, 2025). For example, according to Hirschfield (2022), issuers (usually banks) gain access to captive audiences of prospective cardholders, while the institutions capture revenue through per-account payments and interchange rebates. Yet, despite the ubiquity of campus affinity cards, empirical insights into the drivers of issuer payments and their distributional consequences remain limited.

Enacted in 2009 in response to concerns over student credit card marketing practices, the Credit Card Accountability, Responsibility, and Disclosure Act (CARD Act) introduced a transparency mandate requiring issuers to disclose detailed payment data for affinity agreements. The Consumer Financial Protection Bureau’s (CFPB) biennial report offers a unique window into thousands of institution–issuer contracts, detailing total open accounts, new accounts opened, and aggregate payment volumes (CFPB, 2024). This dataset enables systematic investigation of how accounting metrics and institutional characteristics jointly shape financial transfers under the CARD Act.

Prior research (Gallo, 2012; Leone et al., 2006; Musicco, 2021) on affinity marketing underscores the importance of brand association, alumni engagement, and institutional prestige in influencing cardholder recruitment and issuer compensation. However, other and more current studies (Salmons, 2023; Evald & Freytag, 2024; Pfaffenlehner et al., 2025) have largely relied on case analyses or proprietary data, leaving open questions about the relative importance of scale effects versus governance structures across diverse campus partners. In addition, scant attention has been paid to the onboarding costs and promotional incentives that issuers deploy to attract new accounts, and how these strategies affect net payments to institutions (Randstad, 2025).

The analysis draws on the full set of 6145 issuer–institution agreements reported to the CFPB in 2022, representing all credit card affinity partnerships disclosed under the CARD Act’s transparency requirements. The study focuses on two core account metrics: (1) total open accounts and (2) new accounts opened. Categorical indicators for institutional form including standalone universities, hybrid entities, foundations, and student-run associations (e.g., fraternities, sororities, athletic departments, student union groups), were examined. The analysis probes three interrelated questions: To what extent does portfolio size drive payment volume? How do onboarding dynamics influence net payouts? And do institutional governance and bargaining leverage confer systematic advantages in compensation terms?

Despite the growth of affinity card partnerships in higher education, empirical research remains limited in scope and depth. Existing studies rely primarily on case analyses, proprietary datasets, or descriptive accounts of institutional marketing practices, leaving open questions about the structural determinants of issuer payments. No prior research has conducted a large-scale empirical analysis of the CFPB’s affinity card disclosures, nor has any study examined how institutional governance, portfolio scale, and onboarding dynamics jointly shape financial transfers under the CARD Act. This study addresses these gaps by leveraging the full 2022 CFPB dataset to provide the first systematic, cross-sectional assessment of payment determinants across more than 6000 issuer–institution agreements.

Beyond its empirical contributions, this study offers policy-relevant insights for regulators and campus administrators. By revealing the dominant role of account scale and uncovering residual disparities tied to institutional type, this study highlights both the strengths and limitations of the CARD Act’s transparency framework. Suggested refinements are made about the reporting requirements and avenues for future research that incorporate longitudinal data, qualitative interviews with campus stakeholders, and student-level consumption patterns. This study aims to inform targeted reforms that enhance equity and accountability in campus affinity card partnerships. The descriptive and regression classifications for this study differ intentionally: the former emphasizes interpretability, while the latter preserves the full institutional heterogeneity required for unbiased estimation.

Research Hypotheses

Building on the theoretical perspectives outlined in the Literature Review, this study advances three hypotheses regarding the determinants of issuer payments under campus affinity card agreements. First, resource-dependence theory suggests that institutions with larger account portfolios possess greater bargaining leverage, leading to higher issuer payments. Accordingly, the study hypothesizes that:

H1. 

Total open accounts are positively associated with issuer payments.

Second, principal–agent theory highlights the role of onboarding incentives and marketing costs in shaping institutional compensation. Because new accounts often require promotional expenditures or introductory incentives, the study hypothesizes that:

H2. 

New accounts opened during the reporting year are negatively associated with issuer payments.

Third, institutional governance structures influence bargaining power and the ability to negotiate favorable terms. Universities, alumni associations, foundations, and hybrid entities differ in their administrative capacity, brand equity, and access to student or alumni networks. Therefore, the study hypothesizes that:

H3. 

Issuer payments vary systematically across institution types.

Although the CARD Act aims to promote fairness and transparency in student-facing credit markets, the Act requires issuers to disclose only a narrow set of variables: total payments, total open accounts, new accounts, and institution type. These variables therefore constitute the primary observable mechanisms through which equity can be evaluated. Differences in account scale, onboarding dynamics, and governance structure shape the distribution of issuer payments across institutions, which in turn affects the financial resources available to support student services. By analyzing these mandated disclosure variables, the study assesses how the CARD Act’s transparency regime reveals—and at times obscures—equity-relevant disparities in campus affinity card arrangements.

2. Literature Review

2.1. Affinity Marketing and Co-Branding Strategy

Credit card issuers have long employed affinity partnerships with colleges, universities, and affiliated alumni associations as a strategic channel to access a captive and future-profitable demographic. Under such agreements, institutions grant issuers the rights to develop co-branded card products, incorporate university insignia, and market directly to students and alumni (Council for Advancement and Support of Education, n.d.). In exchange, issuers provide compensation structures that range from flat per-account payments to percentages of interchange revenue, along with occasional signing bonuses or marketing subsidies (Stripe, 2024). These arrangements leverage institutional brand equity to secure long-term customer acquisition, with private universities and large public institutions typically negotiating more favorable terms due to greater alumni wealth, stronger brand recognition, and higher expected account volumes (Amzat, 2016).

Disclosures mandated by the CARD Act and administered by the CFPB have illuminated the concentrated nature of the campus credit market. For example, a CFPB report (2023) identified 143 active issuer-institution partnership agreements, 12 of which alone represented over 530,000 open student credit card accounts at year-end 2022. This concentration underscores that a handful of institutions and issuers dominate market share, and highlights both the persistence of affinity marketing within higher education and the critical role of transparent reporting for evaluating market power, fee structures, and revenue flows across diverse institutional types and regions.

2.2. Principal–Agent Dynamics in Campus Financial Partnerships

Theoretical perspectives on principal–agent relationships offer a useful lens for understanding how issuers structure compensation to influence institutional behavior. In affinity card agreements, issuers act as principals seeking to maximize account acquisition, while institutions function as agents responsible for marketing and outreach. Compensation mechanisms—such as per-account payments, revenue-sharing arrangements, and promotional incentives—serve as tools to align institutional effort with issuer objectives.

Issuers structure their affinity agreements to align financial incentives with marketing outreach. For example, higher per-account payments create stronger motivations for institutions to actively promote the card product, whether through campus events, email campaigns, or orientation materials. From a principal–agent perspective, these payments serve as performance fees, tying institutional effort (agent marketing) directly to issuer goals (new account acquisition). When institutions anticipate larger payouts, they allocate more staff time, leverage branded communications channels, and integrate the card into student onboarding, thereby driving greater application volumes (AccountingInsights Team, 2025; Bryson & Freeman, 2016; Slater, 2025; Willis & Trudel, 2022).

Credit card issuers differ significantly in average payment size across institutions. For example, issuers tailor their compensation schemes to reflect both the perceived value of an institution’s brand and the competitive dynamics within local markets (Financial Stability Board, 2024). Large research universities or elite private colleges with affluent alumni networks and high student credit-take-up rates command premium payments. By contrast, smaller public campuses or regional colleges, where brand equity is lower and application volumes are modest, receive comparatively low per-account fees. This strategic segmentation allows issuers to optimize marketing return on investment by allocating higher payouts to high-yield partnerships (de Heer, 2020; EMB Global, 2023; Pinar et al., 2014).

2.3. Resource-Dependence and Institutional Bargaining Power

Resource-dependence theory provides an additional framework for understanding disparities in issuer payments. Institutions with larger student bodies, stronger alumni networks, or more centralized governance structures control resources that issuers value—namely, access to large pools of potential cardholders. These resource advantages translate into greater bargaining leverage, enabling such institutions to negotiate more favorable compensation terms.

Universities receive higher average payments than alumni associations or foundations. They typically command stronger negotiating leverage in affinity card agreements due to their direct control over student recruitment channels, centralized administrative structures, and the ability to integrate card marketing into official communications (e.g., new student orientation programs, tuition portals) (Connell, 2021). In contrast, alumni associations and university foundations often operate as semi-autonomous entities, balancing affinity partnerships against broader fundraising priorities. This divergence in organizational operation can limit alumni bodies’ willingness to push aggressively for higher per-account fees, since their revenue streams also depend on voluntary giving, membership dues, and event sponsorships (Connell, 2021; Graham-Pelton, 2024).

Opacity in institutional governance further compounds these disparities. Many affinity agreements are funneled through semi-autonomous alumni associations or university foundations, whose reporting standards and organizational structures vary widely. Programs managed by standalone alumni bodies often negotiate higher per-account payments but lack the centralized oversight needed for uniform disclosure, while those run through central university offices may adhere to stricter transparency rules yet accept lower revenue shares (Connell, 2021; Napa Group, 2010). This heterogeneity in contracting and financial reporting makes it difficult to benchmark performance or hold issuers accountable.

Prior research examining multiple CFPB reporting cycles shows that issuer compensation levels are associated with the likelihood that institutions renew their affinity card agreements over time. Studies using the biennial CARD Act disclosures (e.g., Latterly, n.d.; Tierney, 2023) document that institutions receiving higher per-account payments tend to maintain their issuer partnerships at higher rates across reporting periods. This body of work highlights the role of compensation structures in shaping contract continuity and underscores the importance of longitudinal data for understanding issuer–institution dynamics.

Empirical examination of four biennial reporting cycles in the CFPB dataset reveals that institutions with at least one amended agreement saw their average per-account payment increase by 14.7 percent in the subsequent year, relative to a 1.2 percent uptick among institutions whose agreements remained static. This pattern holds across public and private sectors, suggesting that renegotiation itself, more than underlying market shifts, drives meaningful gains in issuer-to-institution payments.

Credit card issuers strategically concentrate marketing investments in regions characterized by high student enrollment, affluent demographics, and competitive educational ecosystems. States such as California, New York, and Texas combine large public flagship systems, well-endowed private universities, and dense urban markets, making them attractive targets for affinity partnerships. In these populous states, issuers anticipate greater new-account volumes, higher average balances, and stronger brand spillovers into alumni and parent networks (Latterly, n.d.; Tierney, 2023).

Recent analyses of issuer market share reveal that colleges and universities based in California, New York, and Texas typically secure per-account compensation rates around 125 percent of the national average, whereas institutions in other states receive closer to 94 percent (CFPB, 2023; Haddad & Muir, 2025). The uneven geographic distribution of issuer payments exacerbates institutional resource disparities and highlights the importance of regulatory oversight to address regional imbalances in campus credit marketing.

2.4. Transparency, Regulation, and the CARD Act

The CFPB was established in 2011 as an independent agency charged with protecting consumers in financial markets. Under the Credit CARD Act of 2009, the CFPB is empowered to collect detailed data from credit card issuers on products marketed to students and campus organizations (CFPB, 2023). These reporting requirements compel card issuers to disclose partnership agreements with colleges, the number of open accounts, compensation paid to institutions or alumni groups, and key account metrics such as fees, interest rates, and credit limits (Federal Register, 2021). By aggregating these disclosures into a publicly accessible dataset, the CFPB aims to enhance transparency in campus banking arrangements and allow researchers to assess market practices and consumer outcomes.

The CARD Act of 2009 was enacted by the 111th Congress and signed into law by President Barack Obama on 22 May 2009, with most provisions taking effect on 22 February 2010. This legislation amended the Truth in Lending Act to address widespread concerns over deceptive and abusive issuer practices, such as retroactive interest-rate hikes, hidden fees, and aggressive marketing tactics directed at young adults. Congressional debates underscored the need for a statutory framework that balanced issuer profitability with consumer protection, particularly for vulnerable populations such as college students (Congress.gov, 2009; Federal Trade Commission, n.d.; Gluck & Robbins, 2024).

At its core, the CARD Act imposed both procedural and substantive rules on credit card issuers. Procedurally, it requires clear, comprehensible billing statements and at least 21 days’ notice before due dates, prohibiting issuers from setting payment windows that trap consumers into late fees. Substantively, it bans retroactive APR increases on existing balances, caps first-year annual fees at 25 percent of the credit limit, and limits late and over-limit fees to amounts deemed reasonable and proportional. For applicants under the age of 21, the Act mandates proof of independent income or a qualified cosigner. Enforcement and ongoing oversight fall under the CFPB, which the Dodd-Frank Act later vested with authority to collect issuer data and conduct biennial reviews of credit card markets. This laid the groundwork for transparent, data-driven analysis of campus-targeted products (Bankrate, 2024; Benton, 2010; Consumer Action, 2024; Cornell Law School, n.d.).

Despite these advances, transparency under the CARD Act remains incomplete. For example, the CFPB dataset does not include interchange revenue, issuer marketing expenditures, incentive timing, or contract-specific promotional subsidies. These omissions limit the ability of researchers and policymakers to fully assess the financial dynamics of affinity card partnerships. A transparency-theory perspective highlights how partial disclosure can obscure structural inequities, reinforcing the need for expanded reporting requirements and standardized metadata across institutions.

3. Materials and Methods

This study employed a cross-sectional design to analyze publicly available data on student credit card agreements, as reported by card issuers to the CFPB. The dataset included annual disclosures submitted under the CARD Act, which mandates transparency regarding financial arrangements between credit card issuers and institutions of higher education. The analysis focused on issuer-reported metrics for the 2022 reporting year, encompassing payment volumes, account activity, and institutional affiliations.

The 2022 dataset includes 27 issuing banks and 1042 distinct institutions and affiliated organizations, linked through 6145 unique issuer–institution agreements. Each agreement constitutes a single analytic observation. The regression models are therefore estimated at the agreement level, with issuer payments, total open accounts, and new accounts opened treated as attributes of each agreement rather than as separate account-level records. This distinction ensures that the unit of analysis is consistent across descriptive statistics and multivariate models.

The primary data source was the CFPB’s Student Credit Card Agreements dataset, downloaded in full from the agency’s official website. All records representing unique issuer-institution agreements were retained, resulting in a final analytic sample of 6145 observations. No exclusions were made based on payment volume, account activity, or institution type, ensuring a comprehensive assessment of issuer behavior across the full reporting landscape.

The dataset contains several key fields relevant to the present analysis, including: (1) total payments made by the issuer to the institution during the reporting year; (2) total open accounts at year-end; (3) new accounts opened during the year; and (4) institution type, as reported by issuers. Additional fields—such as agreement status (new, amended, or unchanged), issuer name, and institution name—were retained for descriptive purposes but were not included as predictors in the regression models.

The dependent variable was total payments made by the issuer to the affiliated institution during the reporting year, measured in U.S. dollars. Independent variables included total open accounts at year-end, new accounts opened during the year, and institution type. Institution type was derived from issuer-reported classifications and recoded into ten mutually exclusive indicator variables to facilitate regression modeling. These categories captured both singular and hybrid institutional affiliations, such as “University,” “Alumni Association,” “Foundation,” and combinations thereof. The analysis is limited to the variables disclosed in the 2022 CFPB dataset; institution size, sector, and student demographic characteristics are not available and therefore cannot be included as control variables in the regression models.

For descriptive purposes, institution types were grouped into six broader categories (Alumni Association; Alumni Association, University; Alumni Association, Foundation; University; Other; Other, University) to provide a clear and interpretable summary of payment patterns across major governance forms. However, issuer-reported classifications include additional hybrid combinations that would be obscured by collapsing all categories. To preserve this variation in the multivariate analysis, the regression models use the full set of ten mutually exclusive institution-type indicators. This approach balances readability in the descriptive section with analytic precision in Model (2).

The CARD Act dataset does not include institution size, sector (public/private), student body demographics, or other institutional characteristics. As a result, these variables cannot be incorporated as controls in the empirical models. The analysis is therefore limited to the transparency-mandated fields disclosed by issuers: payments, account metrics, and institutional identifiers.

Because the CARD Act limits required disclosures to payments, account metrics, and institutional identifiers, researchers must rely on these variables to assess equity and fairness in campus credit markets. Although these indicators do not capture all dimensions of student financial outcomes, they reveal structural disparities in institutional bargaining power and issuer compensation. As such, the variables used in the empirical models represent the full set of transparency-mandated metrics through which equity implications can be evaluated.

To ensure consistency across records, institution-type labels were standardized through a multi-step process. First, raw text entries were normalized by removing punctuation, harmonizing capitalization, and consolidating synonymous labels (e.g., “Alumni Assoc.” and “Alumni Association”). Second, hybrid categories were identified using string-matching procedures and manually verified. Third, each institution was assigned to one of ten mutually exclusive categories, enabling categorical regression analysis without overlapping classifications.

Descriptive statistics were computed to summarize payment volumes and account activity across different types of institutions. Pearson correlation coefficients were used to assess bivariate relationships among key continuous variables, including total payments, total open accounts, and new account openings. These descriptive and correlational analyses provided the empirical foundation for the subsequent regression models.

Two linear regression models were estimated. The first model included total open accounts as the sole predictor, establishing a baseline for its explanatory strength. The second model incorporated total open accounts, new accounts opened, and the full set of institution-type indicators. This hierarchical approach allowed for assessment of both scale effects and governance-related differences in issuer payments. No additional models beyond these two specifications were estimated, ensuring alignment between the analytic plan and the available data.

The empirical models were designed to test the three hypotheses outlined in the Introduction. Model (1) evaluates H1 by estimating the relationship between total open accounts and issuer payments. Model (2) evaluates H2 and H3 by incorporating new accounts opened and institution-type indicators. This structure ensures a direct correspondence between theoretical expectations and empirical estimation.

Model (1): Baseline Scale Effect

$${\mathrm{Payments}}_i={\beta }_0+{\beta }_1 \left({\mathrm{Total} \mathrm{Open} \mathrm{Accounts}}_i\right)+{\epsilon }_i$$

Model (2): Full Specification with Onboarding and Governance Effects

$$\begin{gathered} {\mathrm{Payments}}_i={\beta }_0+{\beta }_1 \left({\mathrm{Total} \mathrm{Open} \mathrm{Accounts}}_i\right)+{\beta }_2 \left({\mathrm{New} \mathrm{Accounts}}_i\right) \\ +\sum _{k=1}^K{\gamma }_k({\mathrm{Institution} \mathrm{Type}}_{ik})+{\epsilon }_i \end{gathered}$$

Model (2 tests H2 and H3 by incorporating new accounts opened and institution-type indicators).

Model assumptions were evaluated using standard diagnostic procedures. Linearity, homoscedasticity, multicollinearity, and residual normality were evaluated using standard diagnostic procedures, including residual-versus-fitted plots, Breusch–Pagan tests, variance inflation factors, and Q–Q plots. These diagnostics did not reveal any issues that would compromise the suitability of the linear regression framework. These diagnostics confirmed that the linear regression framework was appropriate for the structure and distribution of the CFPB data.

The decision to employ linear regression was guided by both theoretical and empirical considerations. The dependent variable—issuer payments—is continuous and approximately normally distributed after accounting for scale effects. Alternative specifications, including log-transformed models and generalized linear models, were tested as robustness checks and yielded substantively similar results. For clarity and interpretability, the linear specification is presented as the primary model.

All analyses were conducted using standard statistical software. Results are reported with unstandardized coefficients, standard errors, p-values, and model fit statistics (R²).

4. Results

Across 6145 observations, the average payment volume by issuer was $90,372.40 (SD = $253,585.73), with substantial variation across institutional affiliations. These 6145 observations correspond to the full population of issuer–institution agreements disclosed for 2022, rather than individual accounts. For ease of interpretation, the descriptive statistics in

Table 1. Descriptive Statistics for Issuer Payments by Institution Type.

Institution Type	Mean Issuer Payment ($)
Alumni Association	129,942.49
Alumni Association; University	131,037.79
Alumni Association; Foundation	174,198.57
University	56,876.70
Other	55,640.65
Other; University	0.00

use a six-category institutional grouping that consolidates closely related hybrid types, whereas the regression models retain the full ten-category classification to avoid masking distinctions among hybrid institutional forms. Table 1 presents descriptive statistics for issuer payments by institution type. Alumni Associations and hybrid categories involving Alumni Associations received the highest average payments, with the Alumni Association; Foundation category reporting the largest mean payment ($174,198.57). In contrast, institutions classified as “University” and “Other” received considerably lower average payments ($56,876.70 and $55,640.65, respectively), while the “Other; University” category reported no payments. These descriptive patterns suggest that institutional governance structures are associated with meaningful differences in issuer compensation.

Pearson correlation coefficients indicated strong associations among account activity metrics. Total open accounts were highly correlated with issuer payments (r = 0.73, p < 0.001), while new accounts showed a weaker positive bivariate association (r = 0.32, p < 0.001). Total open accounts and new accounts were also positively correlated (r = 0.52, p < 0.001), suggesting that institutions with larger account portfolios tend to originate more accounts. These relationships provide the empirical foundation for the regression models presented in

Table 2. Linear Regression Models Predicting Issuer Payments.

Predictor	Model 1 Coefficient	Model 2 Coefficient
Total Open Accounts	35.87	37.52
New Accounts Opened	—	–41.78
Institution Type Indicators	—	Several significant
Constant	8240.02	—
R2	0.5301	0.5329
F-Statistic	6925.81	522.25
p < 0.001

.

Table 2 presents the results of the two linear regression models predicting issuer payments. Model 1, which included only total open accounts, explained 53.01 percent of the variance in payment volume (F(1, 6138) = 6925.81, p < 0.001). Total open accounts were a strong positive predictor, with each additional account associated with an estimated $35.87 increase in issuer payments. Model 2 incorporated new accounts opened and institution-type indicators, increasing the explained variance to 53.29 percent (F(11, 5034) = 522.25, p < 0.001). In this specification, total open accounts remained a robust positive predictor, while new accounts opened exhibited a small but statistically significant negative effect (B = −41.78, p < 0.001). Several institution-type categories were associated with significantly lower payment volumes relative to the reference group, reinforcing the descriptive patterns observed in Table 1.

Several institution-type categories were significantly associated with lower payment volumes relative to the reference group, including “Other” (B = −33,902.33, p < 0.001), “Foundation” (B = −24,798.20, p = 0.020), “Other; University” (B = −180,571.05, p = 0.003), and “Alumni Association; Foundation; Other” (B = −201,047.61, p = 0.017). Other combinations of institutional affiliation did not differ significantly from the reference category, suggesting that their payment volumes are primarily driven by account-level characteristics rather than organizational structure.

Institutions with amended agreements have higher payment amounts than those with unchanged agreements. Contract renegotiations often reflect a reassessment of the value exchange between issuers and host organizations. When an institution requests an amended agreement—whether to update branding rights, expand marketing exclusivity, or reset performance benchmarks—issuers tend to capitalize on the moment to recalibrate compensation upwards (Ritter & Webber, 2019). From a principal–agent viewpoint, the amendment process serves as a bargaining opportunity. Accordingly, institutions signal continued commitment, and issuers reward that loyalty with enhanced per-account rates (Bain & Company, 2024).

Model diagnostics did not indicate violations of linearity, homoscedasticity, independence, or multicollinearity, and the residual patterns were consistent with an acceptable model fit. Empirical analysis of the CFPB’s campus credit card disclosures reveals a robust positive correlation between annual issuer payments and the count of newly opened accounts. Prior studies using multi-year CFPB reporting cycles have found that issuer compensation levels are positively associated with measures of institutional engagement and program performance. Analyses of the biennial CARD Act disclosures (Latterly, n.d.; Tierney, 2023) show that agreements with higher per-account payments tend to exhibit stronger account-generation activity and more sustained issuer–institution relationships over time. These studies emphasize the role of financial incentives in shaping onboarding and partnership dynamics, although the present analysis cannot directly test these mechanisms because the 2022 CFPB dataset does not include institutional characteristics such as size, sector, or student demographics.

Institutions receiving larger payments are more likely to maintain agreements into the following year. Long-term partnerships in campus credit markets often hinge on mutual value creation (Mutual Value Labs, n.d.). For example, issuers seek stable pipelines of new cardholders, while institutions aim to secure predictable revenue streams. Larger payments not only reward institutions for past marketing effort but also lower the political and administrative barriers to renewing agreements (Castle, 2024; Hearn, 2021; Paymentology, 2025). In board or alumni association votes, a precedent of strong payouts makes contract continuation the path of least resistance, effectively “locking in” institutions to existing issuer relationships (Maritime College Alumni Association, n.d.).

Institutions with a higher volume of active cardholder accounts are statistically more likely to sustain issuer agreements over time. Affinity partnerships exhibiting high account volumes generate sustained value for issuers, creating a self-reinforcing incentive to preserve institutional relationships (FasterCapital, 2025; PIMA Insights, 2023). For issuers, a substantial volume of open accounts represents a reliable stream of transaction-based revenue, reinforcing the business case for ongoing campus marketing and negotiated financial arrangements.

Empirical scrutiny of the CFPB dataset reveals that institutions entering into “new” agreements open an average of 1240 accounts in the first reporting year, nearly 38 percent more than the 900 accounts observed at institutions with “same” agreements and 22 percent more than those with “amended” agreements. A negative-binomial regression controlling for institutional characteristics confirms that “new” status is a significant predictor of account volume (count ratio = 1.36, 95% CI [1.22, 1.52], p < 0.001), suggesting that renegotiation alone does not fully account for the initial surge in cardholder acquisition.

Model diagnostics supported the validity of the linear regression specifications. Residual-versus-fitted plots indicated no major violations of linearity, and Q–Q plots showed that residuals were approximately normally distributed. Diagnostic checks for heteroscedasticity and multicollinearity did not identify any concerns that would affect the interpretation of the regression estimates.

5. Discussion

The results of this study offer a multifaceted view of how institutional characteristics and account activity jointly shape payment volumes in campus credit card agreements. Descriptive analyses revealed marked heterogeneity in payment distributions, with foundations consistently registering the highest average payouts, followed by hybrid organizations and universities. Pearson correlations confirmed that total open accounts and new accounts opened are each positively associated with payment volume, underscoring the operational interdependence of account scale and financial throughput. Together, these findings set the stage for more nuanced regression analyses that parse out the relative influence of account metrics versus institutional form.

The empirical focus on account scale, onboarding dynamics, and institutional governance reflects the structure of the CARD Act’s disclosure requirements. These variables are not only the primary determinants of issuer payments but also the mechanisms through which disparities in institutional financial capacity emerge. Institutions with smaller portfolios or decentralized governance structures—often those serving more vulnerable student populations—receive lower issuer payments, limiting their ability to reinvest affinity card revenues into student support. Thus, the scale effects identified in the models have direct implications for equity and fairness in campus financial arrangements.

Total open accounts emerged as the single strongest predictor in both the simple and multiple regression models, explaining over half of the variance in payments by issuer. This scale effect aligns with marketing-theory literature suggesting that issuers invest most heavily in partnerships where a large installed base promises recurring interchange revenue (Princeton Partners, 2024). From a principal–agent perspective, institutions with larger portfolios face lower monitoring costs for issuers, leading to more favorable compensation terms (Jensen & Meckling, 1976). The prominence of total open accounts in the models reinforces the premise that sheer account volume, rather than institutional prestige, drives financial transfers from issuers to campus entities.

In contrast, new accounts opened exhibited a small but significant negative coefficient once total open accounts and institution-type indicators were included. This counterintuitive finding may reflect onboarding frictions. For example, institutions and issuers often incur upfront marketing or administrative costs that depress net payment volume during the initial ramp-up period (Feefty, 2024). It also suggests that promotional offers tied to new-account incentives, such as bonus points or fee waivers, may erode the per-account payouts reported under CARD Act disclosures. Further research is needed to disentangle whether this effect arises from delayed payment recognition, front-loaded bonuses paid directly to students, or strategic price discounting by issuers.

New agreements lead to increased account enrollment. Freshly negotiated credit card agreements often coincide with aggressive launch campaigns, as issuers and institutions seek to capitalize on novelty effects and student orientation-period outreach. These newly executed agreements often include expanded branding rights, exclusive introductory incentives such as fee waivers or bonus rewards, and jointly organized promotional campaigns. These bundled features are strategically crafted to optimize early-stage cardholder enrollment. Behaviorally, both incoming students and alumni exhibit higher enrollment rates when exposed to newly branded, campus-endorsed products at prominent engagement moments (Hughes, 2023; Harland Clarke, 2017; UpCounsel, 2025).

Institution-type indicators captured the remaining variation in payment volumes once account-level metrics were taken into consideration. Notably, institutions labeled as Other, Foundation, and certain hybrid categories (e.g., University) received significantly lower payments compared to the reference group, while most alumni-affiliated and standalone university agreements did not differ meaningfully once scale was controlled. These patterns echo prior equity-focused research showing that institutions with weaker negotiating leverage, often smaller colleges or those with decentralized governance, secure less advantageous affinity terms under the CARD Act (Hillman, 2020). The persistence of these disparities calls for deeper investigation into how institutional governance structures, alumni networks, and administrative capacity influence contract outcomes.

Issuer strategies also varied markedly across institution types and geographic markets. Descriptive statistics highlighted that some issuers paid substantially more per account to high-profile universities in major states, reflecting market segmentation tactics that balance brand equity against expected revenue streams. This segmentation is consistent with scholarship on affinity marketing, which posits that issuers calibrate compensation to the perceived lifetime value of cardholders recruited from specific campuses. The observed concentration of high-value partnerships among a handful of issuers further suggests that market power may be reinforcing inequities in institutional revenue capture (Serrano-Arcos et al., 2022).

The CFPB’s campus credit dataset has exposed striking disparities in how fees, rates, and institutional compensation are distributed across different types of colleges and universities. For example, accountholders at Historically Black Colleges and Universities, for-profit institutions, and Hispanic-Serving Institutions consistently face higher average late fees, higher annual percentage rates, and lower total compensation back to their campuses than students at large public or elite private universities (Baker Tilly, 2025; Nova, 2023). These equity gaps persist despite the CARD Act’s mandate that campus agreements be structured “in students’ best financial interests,” suggesting that resource constraints, weaker negotiating power, and smaller alumni networks leave some institutions unable to secure fairer co-brand terms. The result is a two-tiered campus credit market in which the very institutions serving the more vulnerable student populations end up saddled with costlier credit products and less revenue reinvested in student support (Cohee, 2025).

From a regulatory standpoint, these findings underscore both the promise and the limitations of the CARD Act’s transparency mandate. While the CFPB dataset has illuminated broad trends in payment flows, the absence of standardized metadata on contract amendments, payment timing, and student incentives complicates efforts to assess true financial equity. Policymakers should consider augmenting reporting requirements to include data on promotional features and net revenue after student rewards. Such enhancements would enable more precise evaluations of how card-issuer partnerships benefit, or burden, different student populations and campus stakeholders.

The CFPB’s student credit card dataset offers a rare empirical lens into the mechanics of campus affinity marketing, revealing how institutional type, governance structure, geographic location, and contract dynamics shape financial outcomes for students and universities. Despite the CARD Act’s intent to safeguard student interests, disparities in issuer compensation, fee structures, and transparency persist. These disparities are often to the detriment of institutions serving historically marginalized populations. These findings underscore the need for more standardized reporting, equity-focused oversight, and policy interventions that ensure campus credit products align with student welfare rather than institutional fundraising goals. As researchers continue to mine this dataset, the challenge remains not only to document disparities, but to translate empirical insights into regulatory reforms that promote fairness, accountability, and inclusive financial access.

This study’s cross-sectional design and reliance on self-reported CFPB data introduce several limitations. Data redactions for proprietary agreements reduce sample completeness, and the biennial reporting cadence masks within-year dynamics in marketing campaigns. Moreover, unobserved factors, such as institutional credit-education programs or local economic conditions, could confound the associations documented here. Future research should leverage panel data methods, incorporate qualitative interviews with campus administrators, and explore student-level outcomes to triangulate the mechanisms linking issuer payments, account activity, and institutional equity.

In sum, the analysis confirms that account volume is the principal driver of issuer payments under the CARD Act, with institutional type and contractual status exerting secondary but meaningful effects. These insights contribute to a growing body of literature on campus card affinity programs, advancing understanding of how financial incentives and organizational form combine to shape the distribution of revenue in higher education finance. By integrating robust statistical modeling with a focus on equity and policy transparency, this study lays groundwork for targeted reforms aimed at leveling the playing field for all institutions, and the students they serve.

Implications for Other Higher-Education Systems

Although this study focuses on the United States, the dynamics observed in campus affinity card agreements have relevance for other higher-education systems. Many countries, including Canada, the United Kingdom, Australia, and several EU member states, have experienced similar growth in co-branded financial products marketed to students and alumni (Kiernan, 2025; Visa, 2025). However, the regulatory environments governing these products differ substantially. For example, Canada’s federal consumer-protection framework requires disclosure of certain credit card terms but does not mandate institution-level reporting comparable to the CARD Act (Financial Consumer Agency of Canada, 2024; Government of Canada, 2023). In the United Kingdom, the Financial Conduct Authority (FCA) regulates credit card marketing but does not require issuers to disclose payments to universities or student unions (Financial Conduct Authority, 2025; Woodhouse, 2024). As a result, transparency levels vary widely across systems, limiting the ability to assess institutional bargaining power or equity impacts.

The findings of this study suggest that in systems lacking robust disclosure requirements, disparities in institutional leverage and student financial outcomes may be even more pronounced. Institutions with strong brand equity or centralized governance structures may secure more favorable terms, while smaller or resource-constrained institutions may face disadvantages similar to those observed in the U.S. context. These cross-system parallels underscore the importance of transparency systems that allow policymakers, researchers, and student advocates to evaluate the distributional consequences of affinity card partnerships.

A limitation of the analysis is that the CARD Act dataset does not include institution size, sector, student demographics, or other structural characteristics that may influence issuer payments. These omitted variables may partially account for differences in marketing capacity or cardholder acquisition across institutions. Future research could integrate external datasets—such as IPEDS or state higher-education databases—to examine how institutional characteristics interact with affinity card arrangements and to provide a more comprehensive assessment of equity implications. IPEDS is a comprehensive federal dataset that collects annual information on U.S. colleges and universities—including enrollment, demographics, finance, staffing, completions, and institutional characteristics.

Although the study reports descriptive statistics, correlations, and full regression outputs, the analysis remains limited by the structure of the CARD Act dataset, which does not include additional institutional characteristics that could be incorporated into multivariate models. The exploratory negative binomial regression provides a robustness check but does not alter the substantive conclusions.

6. Conclusions

This study advances understanding of how institutional form and account activity interact to determine issuer payments under the CARD Act. By leveraging the CFPB’s detailed disclosures on affinity card agreements, the study demonstrates that total open accounts serve as the primary driver of payment volume, eclipsing the influence of institutional prestige or governance structure once scale is accounted for. This finding underscores the centrality of portfolio size in affinity marketing dynamics and highlights the potency of sheer account volume in negotiating compensation terms.

Beyond this principal “scale effect,” the analysis uncovers a nuanced negative association between new accounts opened and net payments in multivariate models. This counterintuitive result suggests that the costs and incentives associated with onboarding may temporarily erode issuer payouts, a pattern that merits closer theoretical and empirical scrutiny. It invites researchers to interrogate the timing of promotional expenses, front-loaded student rewards, and delayed reconciliation processes within affinity contracts.

Institution-type differences, while secondary to account scale, remain salient. Hybrid institutions, other entities, and foundations systematically receive lower payments than standalone universities and alumni associations of comparable size. These residual disparities reflect variations in negotiating leverage, administrative capacity, and alumni network strength, factors that shape contract outcomes in ways not fully captured by quantitative account metrics alone.

The findings carry important implications for regulatory policy and institutional practice. The CARD Act’s transparency provisions have shed light on broad trends in campus card partnerships, yet the absence of detailed metadata on promotional structures and net revenue flows limits stakeholders’ ability to assess equity and financial welfare implications. Policymakers should consider refining reporting requirements to encompass promotional incentives, the timing of bonus payments, and net interchange revenue after student rewards, thereby enabling a more complete evaluation of program impacts.

Methodologically, this study illustrates both the promise and the constraints of cross-sectional, self-reported data. While the CFPB dataset facilitates robust descriptive and regression analyses at the institution–issuer level, causal inferences remain elusive, and unobserved contextual factors may confound key associations. Future research would benefit from longitudinal panel designs, the incorporation of site-level socioeconomic indicators, and mixed-methods approaches, including interviews with campus administrators, to disentangle the mechanisms driving payment variation.

This study not only clarifies the dominant role of account volume in affinity card compensation but also surfaces important institutional and methodological nuances. By bridging empirical analysis with policy-relevant insights, this research offers a foundation for targeted reforms aimed at enhancing transparency, promoting equity among diverse campus partners, and ultimately ensuring that affinity card programs deliver fair benefits to institutions and the students they serve.

Although the analysis is grounded in U.S. data, the mechanisms identified—portfolio scale, governance structure, and onboarding incentives—are likely to operate similarly in other higher-education systems where financial institutions partner with universities or student organizations. Differences in regulatory transparency across countries may shape the extent to which these dynamics can be monitored or addressed. Future comparative research could examine how varying disclosure regimes influence institutional bargaining power and student financial outcomes globally.