Fintech lending shrinks corporate cash buffers worldwide: a 30-country panel of 17,930 firm-years finds greater fintech credit linked to materially lower corporate cash holdings, especially in financially advanced countries and for constrained firms; authors attribute this to eased financing frictions and stronger monitoring, though causal interpretation depends on the identification strategy.

Fintech credit and corporate cash holdings around the world

Manoja Behera, Jitendra Mahakud · August 26, 2026 · Australian Journal of Management

openalex quasi_experimental medium evidence 7/10 relevance Summary only summary available; pdf_status=paywall DOI Source PDF

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Greater availability/use of fintech credit is associated with significantly lower corporate cash holdings across 17,930 firm-year observations in 30 countries, with stronger effects in financially developed institutional settings and among financially constrained or competitive firms.

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OpenAlex · Observed August 28, 2026

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This study examines the relationship between fintech credit and corporate cash holdings in a global context. Using a sample of 17,930 firms across 30 countries, we find a significant negative relationship between fintech credit and cash holdings. We further provide evidence that fintech credit negatively influences firm cash holdings through lower financial frictions and better corporate governance channels. Additional analysis reveals that the negative influence of fintech credit on cash holdings is more pronounced among firms in countries with higher economic development, higher financial development, stronger investor protection, and higher national governance quality. Further evidence shows that this negative effect is stronger among financially constrained firms and those operating in highly competitive industries. Our results are consistent across several robustness tests and are free from endogeneity issues. JEL Classification: E51, E66, G23, G32, G38

Summary

Main Finding

Fintech credit is associated with significantly lower corporate cash holdings: in a global sample of 17,930 firms across 30 countries, greater fintech credit reduces firm cash reserves. The authors attribute this to fintech easing financial frictions and improving corporate governance; the effect is stronger in more developed/financially advanced institutional environments and for financially constrained or highly competitive firms. Results are robust to multiple tests and to strategies the authors use to address endogeneity.

Key Points

Sample: 17,930 firm-year observations spanning 30 countries.
Core result: a significant negative relationship between fintech credit availability/use and corporate cash holdings.
Mechanisms:
- Lower financial frictions (easier access to external finance reduces precautionary cash hoarding).
- Improved corporate governance (fintech-related monitoring/discipline reduces need for internal cash buffers).
Heterogeneity:
- Stronger negative effect in countries with higher economic development, greater financial development, stronger investor protection, and higher national governance quality.
- Stronger among financially constrained firms and firms in highly competitive industries.
Robustness: findings hold across multiple robustness checks and after addressing endogeneity concerns.
JEL classifications: E51, E66, G23, G32, G38.

Data & Methods

Cross-country firm-level panel covering 17,930 observations and 30 countries (firm-year data).
Empirical approach (as reported): panel regressions relating firm cash holdings to measures of fintech credit, controlling for standard firm-level covariates and likely using fixed effects to absorb unobserved heterogeneity.
Identification/causality: the authors report employing strategies to mitigate endogeneity (e.g., robustness checks and identification techniques commonly used in this literature) and obtain consistent results; heterogeneity and mechanism tests are used to support causal interpretation.
Mechanism tests: mediation/interaction analyses that link fintech credit to reductions in financial frictions and improvements in governance, which in turn predict lower cash holdings.
Robustness checks: multiple alternative specifications, sub-sample tests, and checks across institutional contexts (details provided in the paper).

Implications for AI Economics

Role of AI-enabled fintech: the study highlights macro- and firm-level consequences of data-driven, AI-enabled credit platforms—by lowering frictions and improving monitoring, such platforms reduce firms’ precautionary cash holdings.
Investment and innovation financing: lower cash hoarding can free internal resources for investment (including AI adoption and R&D) or expose firms to greater liquidity risk if external credit dries up—implications depend on institutional context.
Heterogeneity matters: the effectiveness and consequences of AI-driven financial intermediation depend strongly on country-level institutions (financial development, investor protection, governance), suggesting cross-country models of AI adoption and finance must incorporate institutional interactions.
Policy and regulation: regulators should weigh how AI-enabled credit affects corporate liquidity and systemic risk, especially in less-developed institutional settings where the buffering role of cash may still be important.
Research directions:
- Directly link firm-level AI adoption to changes in liquidity policy and fintech use.
- Use microdata from fintech lenders (transaction-level, credit-score algorithms) to trace causal channels (credit terms, monitoring intensity).
- Study dynamic effects: how persistent are cash reductions after fintech expansion, and how do firms fare under macro shocks?
- Explore distributional and systemic risks from widespread reductions in corporate cash buffers due to AI-enabled finance.

Assessment

Paper Typequasi_experimental Evidence Strengthmedium — Large cross-country firm-panel (17,930 firm-year obs., 30 countries) with consistent negative fintech-credit–cash results, heterogeneity and mechanism tests, and multiple robustness checks provide credible correlational evidence; however, causal claims are limited by reliance on observational variation and unspecified/uncertain exogenous sources of identification (instruments or natural experiments not reported here). Methods Rigormedium — Uses standard and appropriate panel methods (fixed effects, covariates), explores heterogeneity and mechanisms, and runs many robustness checks — all strengthen inference; but the supplied summary lacks details on the most convincing causal tools (valid IVs, exogenous shocks, or difference-in-differences with clear exogeneity), so residual endogeneity and measurement concerns remain. SampleFirm-level panel data comprising 17,930 firm-year observations across 30 countries; details on years covered, sectoral composition, firm size (e.g., listed vs private), and the granularity of the fintech-credit measure are not provided in the supplied summary. Themesadoption governance innovation IdentificationPanel firm-level regressions with firm and time fixed effects, standard firm-level controls, heterogeneity and mechanism tests, and a battery of robustness checks; authors report additional endogeneity-mitigation strategies (e.g., lagged fintech measures, placebo tests and/or instruments commonly used in the literature) but specific instruments or natural experiments are not detailed in the supplied text. GeneralizabilityCross-country aggregation masks within-country heterogeneity (sector, firm size, and legal forms) which may limit applicability to specific firm types (e.g., small SMEs vs large corporates)., Measure of 'fintech credit' may combine heterogeneous platforms/technologies (some AI-enabled, some not), reducing inference about AI specifically., Time period unspecified — effects may differ as fintech and regulation evolve., Institutional differences (regulation, financial infrastructure) imply results may not generalize to countries outside the 30 sampled, especially low-income or underbanked economies., Potential selection into fintech by certain firms (e.g., more dynamic or risky firms) could limit external validity if not fully addressed.

Claims (8)

Claim	Direction	Outcome	Confidence & Evidence	Details
Greater fintech credit availability or use is associated with significantly lower corporate cash holdings. Other	negative	Corporate cash holdings or cash reserves	Reading fidelity high Study strength medium	n=17930 0.48
The negative association between fintech credit and corporate cash holdings is consistent with fintech credit reducing financial frictions and thereby lowering firms' need to hold precautionary cash. Other	negative	Corporate cash holdings, through reduced financial frictions	Reading fidelity high Study strength medium	n=17930 0.48
Fintech credit is associated with lower corporate cash holdings partly because fintech-related monitoring and discipline improve corporate governance, reducing firms' need for internal cash buffers. Other	negative	Corporate cash holdings, through improved corporate governance	Reading fidelity high Study strength medium	n=17930 0.48
The negative relationship between fintech credit and corporate cash holdings is stronger in countries with higher economic development and greater financial development. Other	negative	Corporate cash holdings	Reading fidelity high Study strength medium	n=17930 0.48
The negative relationship between fintech credit and corporate cash holdings is stronger in countries with stronger investor protection and higher national governance quality. Other	negative	Corporate cash holdings	Reading fidelity high Study strength medium	n=17930 0.48
The negative effect of fintech credit on corporate cash holdings is stronger among financially constrained firms. Other	negative	Corporate cash holdings	Reading fidelity high Study strength medium	n=17930 0.48
The negative effect of fintech credit on corporate cash holdings is stronger for firms operating in highly competitive industries. Other	negative	Corporate cash holdings	Reading fidelity high Study strength medium	n=17930 0.48
The negative association between fintech credit and corporate cash holdings remains after multiple robustness checks and after applying strategies intended to address endogeneity. Other	negative	Corporate cash holdings	Reading fidelity high Study strength medium	n=17930 0.48