The role of board age diversity in the performance of publicly listed Fintech entities

Abstract

The present study addresses the important demographic of director age in relation to the performance of the constituent firms of Fintech-focused Exchange Traded Funds (ETFs). While private Fintech boards accommodate generally young officers, regulatory and market forces contribute to notable shifts in the board age composition of seasoned, publicly listed Fintech entities. Within the fast-moving and evolving context of Fintech, we assess how board age composition impacts on such firms’ return-on-assets, sales-on-assets, cash flow proficiencies, and market-to-book value. Our study findings suggest age diversity exhibits a significant inverse relation with the first three of these performance measures. Fintech entities with lower board age dispersion achieve stronger performance in the key metrics. Such a finding holds in cross-sectional terms (i.e. without material change in the average age of board members across the study period). Within our study context, we also assess the age gap between non-executive directors (NEDs) and executive officers (EDs). For most sample firms, average NED age markedly exceeds ED age. Through a battery of tests, we demonstrate more seasoned (i.e. less young) EDs support Fintech firm performance. The presence of more experienced EDs serves in narrowing the age gap with older and more seasoned NEDs.

KEYWORDS:

• Financial technology (Fintech)
• director age
• board age diversity
• executive versus non-executive directors
• firm financial performance

Acknowledgements

We thank Sumon Baumik for comments rendered on an earlier draft of this paper. We also wish to express our gratitude to two anonymous reviewers, an associated editor of the Journal, and the Chief Editor of the EJF for their feedback during the review process.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Only a small minority of NEDs are non-independent or potentially ‘connected’ to EDs. Such persons typically provide a corporate consulting role. We offer further discussion in Section 2.1 and Footnote 9 of this paper.

2 Several cross-market analyses reveal a positive link. Major international business contributions on this frontier include CSRI (2012), García-Meca, García-Sánchez, and Martínez-Ferrero (2015), Post and Byron (2015), Terjesen, Couto, and Francisco (2016), and Christiansen et al. (2016).

3 The existence and magnitude of such costs vary according to alternative financing form (Farag and Johan 2021). ‘Free rider’ incentives in crowdfunding potentially open-up moral hazard concerns (Strausz 2017; Farag and Johan 2021).

4 Notable exceptions exist. See, for example, Yermack’s (2017) analysis of the governance impact of blockchains.

5 Haddad and Hornuf (2019, 89–91) report a marked increase in FinTech start-ups in the post GFC period.

6 For incisive discussion of the role of age in decision-making processes, see Graham, Harvey, and Puri (2013, 107).

7 As a countervailing argument, and predicated on career concern issues, Andreou, Louca, and Petrou (2017) demonstrate that younger executive officers are less likely to divulge unfavurable news. Consequently, older board officers, with fewer career concerns, may serve a stronger role in attenuating information asymmetry.

8 However, and as Bo, Li, and Sun (2016, 446) attest, firms with younger, less seasoned officers may, on account of career concerns, be less willing to deviate from industry norms in relation to fixed investment decisions.

9 As shown in Table 1C, NED officers account for around 8.84 board members on average in sample firms. Within this NED subgroup, around 8.37 officers are independent directors.

10 A non-linear relation between board age diversity and performance is also permissible. Ali, Ng, and Kulik’s (2014) analysis of Australian firms reports a curvilinear relation between board age diversity and return-on-assets. They show that a positive relation inverts at comparatively high age diversity levels. An initial positive relation peaks at a coefficient of variation value of 0.1 (see Page 504). Thereafter, additional board age diversity results in weaker performance.

11 Based on listed firms in China, Cheng, Chan, and Leung (2010) show that older board chairs boost performance. They contend that the esteem afforded more seasoned chairpersons opens-up access to the chair's extensive networks and resources. In relation to domestic and foreign firms in China’s insurance industry, Li et al. (2011) reveal age diversity across employees bears a significant positive association with performance for Western firms. However, insignificant effects emerge for Asian entities.

12 Loko and Yang (2022) also reveal the positive effect of Fintech on gender employment diversity in financial services.

13 Chen, Leung, and Evans (2016, Page 65, Note 12) also cite Zhou (2001), with the latter arguing that firm fixed effect models are inappropriate when cross-sectional variation accounts for a substantial part of a dependent variable’s movement. Both papers, Chen, Leung, and Evans (2016) and Zhou (2001), suggest the inclusion of firm fixed effects obscures active firm-specific factors. In the present context, the extremely high R² figures that result from the inclusion of firm fixed effects supports such an account. Firm specific dummies thus remove much of the cross-sectional variation in firm-level characteristics (as at least partly explained by board demographics) from view.

14 We determine such sectors using the variable ‘Sector Code (Sector)’ in BoardEx.

15 For banks, King, Srivastav, and Williams’s (2016) study defines adjusted return-on-assets as the difference between a bank’s raw ROA figure and that of all other banks. Additionally, Katsiampa et al. (2022) provide in-depth analytical comparison of Chinese Fintech and traditional bank entities in relation to a range of prudential and financial performance outcomes.

16 Due to multicollinearity, we exclude from regressions a variable for the number of board officers (BoardSize). BoardSize exhibits strong and significant positive association with firm size, LnTotalAsset.

17 As a side note, evidence on graduate entrepreneurship (Breznitz and Zhang 2020) suggests business competencies undergird corporate success. Evidence in relation to MBA-training is however quite mixed. For example, King, Srivastav, and Williams’s (2016) study of US banks reveals that MBA-trained CEOs boost firm-level innovation. In contrast, Urquhart and Zhang (2022) report, for FTSE350 firm CEOs, that MBA training does not necessarily boost net profit margins or ROA performance. As a further related data point, Chevalier and Ellison (1999) report that MBA-trained fund managers often fail to deliver above-the-norm risk-adjusted returns. MBA-trained CEOs may also pursue short-term strategies. Such an approach may be inimical to longer-run corporate performance goals (Miller and Xu 2019).

18 Gul, Srinidhi, and Ng (2011) find US listed firms with gender-diverse boards have more informative stock prices, i.e., prices embed more specific risk as reflected in lower R² figures in Sharpe (1963) Market Model regressions. Within this context, Gul, Srinidhi, and Ng (2011) reveal gender-diverse boards are more effective in disseminating firm-specific information.

19 Institutional factors, and issues of gender-based homophily, likely characterize the Fintech world. Gu (2020) identifies gender-based recruitment biases within financial services more generally. As shown in Zhang (2020), institutional theory explains industry and jurisdictionally based differences in norms on gender-inclusion. External (regulatory- and market-based) forces should nonetheless act on publicly listed Fintech in coaxing greater gender-based diversity.

20 In other contexts, a greater spread in board member nationality cultivates stronger firm-level performance (Ruigrok, Peck, and Tacheva 2007; Masulis, Wang, and Xie 2012). Board internationalization acts as a palliative against the ‘liability of foreignness’ (Zaheer 1995). Greater diversity in board nationality also accentuates ‘cognitive’ strengths (Maitland and Sammartino 2015), enabling greater receptivity to offshore market norms. In contrast to the foregoing positive effects, Arnaboldi et al. (2020) report that greater variation in the board nationality of EU banks culminates in weaker performance.

21 The sample average value industry-adjusted ROA is 0.014, the coefficient for STDEVAge is equal to −0.618 and its standard deviation is equal to 0.285.

22 Regression findings are of course available on request. Of the control variables in such regressions, asset tangibility exhibits the strongest relation with MTBV. Interestingly, MTBV values decline with time since listing, suggesting that Fintech entities’ growth option valuations decline with stock seasoning. This outcome is indicative of market-to-book values stabilizing as returns crystallize on key investment projects.

23 Lead-Lag regression results for the other three dependent variables considered are available on request.

24 Nonetheless, PSM approaches feature widely in the governance literature (see, for example, Galariotis et al. 2023).

25 In respect to Tables 14 and 15, we check on the issue of covariate balance (see, for example, McMullin and Schonberger 2020; Berger and Lee 2022). We find similar covariate properties in relation to both control and treatment subsamples. We acknowledge the guidance of an anonymous reviewer in relation to the EB approach.

26 We also run Heckman (1979) two-stage regressions for SOA for the respective exogenous variables considered in Tables 9–16 and 17. Significant inverse effects are also evident for CoVAge in relation to SOA performance, albeit at lower thresholds than is the case for the ROA dependent variable. AvgAge is strongly significant in relation to such SOA results. While tables do not include such SOA results, our detailed findings are available on request.

Additional information

Notes on contributors

Paraskevi Katsiampa

Dr. Paraskevi Katsiampa is a Lecturer in Financial Management at the Sheffield University Management School, UK. She holds a PhD in Economics and her research interests include financial econometrics, digital finance, and financial technology, among others.

Paul B. McGuinness

Dr. Paul B. McGuinness is Chair (Professor) in Accounting and Finance at the University of Sheffield Management School, UK and Emeritus Professor, Department of Finance, The Chinese University of Hong Kong. His research interests traverse the fields of corporate finance, financial markets, and capital fund-raising.

Hanxiong Zhang

Dr. Hanxiong Zhang is a Senior Lecturer in Finance in the Department of Finance and Accounting, University of Surrey, UK. His research areas include, but are not limited to, corporate governance, FinTech, and financial economics. He holds a Chartered Financial Analyst (CFA) designation. He was co-opted to the Plane Saver Credit Union Board in December 2021.