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Articles

The nexus of customer behaviour, corporate perception and banking: Australian perspective

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Pages 334-355 | Received 15 Jan 2022, Accepted 29 Dec 2023, Published online: 14 Feb 2024
 

ABSTRACT

The Australian Hayne Royal Commission (2017–2019) inquired into misconduct within the banking, superannuation, and financial service sectors. Existing literature produced mixed results with regards to the effectiveness of the Hayne Royal Commission while focusing on the legislative angle. The first major contribution of this paper is it looks at the Hayne Royal Commission through the lens of a customer by creating indices which include the Retail Banking Perception Index, the Monthly Review Score, the Monthly Growth Score, and the Monthly Headline Score. The second major contribution of this paper is it adds to the field of perception analysis for banks by using novel data instead of point in time survey data. By creating these indices, we conclude that banks have been impacted idiosyncratically by the Hayne Royal Commission in terms of customer perception driven by increased transparency.

Acknowledgements

The author(s) are grateful to the anonymous referees for their thorough review and helpful comments, which strengthened the quality of the manuscript.

Disclosure statement

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

Data availability statement

The author(s) confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials.

Notes

1 David Wishart and Ann Wardrop, ‘What Can the Banking Royal Commission Achieve: Regulating for Good Corporate Culture?’ (2018) 43(2) Alternative Law Journal 81; Justin O’Brien, ‘“Because They Could”: Trust, Integrity, and Purpose in the Regulation of Corporate Governance in the Aftermath of the Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry’ (2019) 13(2–3) Law and Financial Markets Review 141; Steve Kourabas, ‘Prudential Regulation in Australia and the Banking Royal Commission: A Missed Opportunity for Reform?’ [2020] Monash University Faculty of Law Legal Studies Research Paper Series; Penny Crofts, ‘Strategies of Denial and the Australian Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry’ (2020) 29(1) Griffith Law Review 21.

2 Kimberly Hedley and others, ‘Banking 2015: A Classic Strategy Battle of Scale vs Focus’ English (2006) 34(3) Strategy & Leadership 51; Gavin Lees and Maxwell Winchester, ‘Do Customer Profiles Change Over Time? An Investigation of the Success of Targeting Consumers of Australia’s Top 10 Banks – 2009 and 2011’ English (2014) 19(1) Journal of Financial Services Marketing 4; Gavin Lees, Maxwell Winchester and Sidath De Silva, ‘Demographic Product Segmentation in Financial Services Products in Australia and New Zealand’ English (2016) 21(3) Journal of Financial Services Marketing 240; Mark Tucker and Christine Jubb, ‘Bank and Product Selection – an Australian Student Perspective’ (2018) 36(1) The International Journal of Bank Marketing 126; Ravindra Saxena and Pradeep Khandelwal, ‘Exploring Customer Perception and Behavior Towards CRM Practices in Banking Sector: An Empirical Analysis’ (2011) 5(9) The International Journal of Interdisciplinary Social Sciences 375; Belén Ruiz and Juan A García, ‘Analyzing the Relationship Between CSR and Reputation in the Banking Sector’ (2021) 61 Journal of Retailing and Consumer Services 102552; Johan Anselmsson and Niklas Bondesson, ‘Brand Value Chain in Practise; the Relationship Between Mindset and Market Performance Metrics: A Study of the Swedish Market for FMCG’ (2015) 25 Journal of Retailing and Consumer Services 58.

3 Kenneth Hayne, ‘Final Report of the Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry’ (2019) <https://treasury.gov.au/publication/p2019-fsrc-final-report/> accessed 19 March 2023.

4 ASIC, ‘Financial Services Royal Commission: Summary of ASIC Enforcement Action’ (2023) <https://asic.gov.au/regulatory-resources/regulatory-index/financial-services/financial-services-royal-commissionsummary-of-asic-enforcement-action/> accessed 19 March 2023.

5 See n 1.

6 Kourabas (n 1).

7 Wishart and Wardrop (n 1); O' Brien (n 1).

8 Crofts (n 1).

9 Tucker and Jubb (n 2).

10 Hedley and others (n 2).

11 Lees and Winchester (n 2); Lees, Winchester and De Silva (n 2).

12 Saxena and Khandelwal (n 2).

13 Anselmsson and Bondesson (n 2).

14 Praphula Kumar Jain, Rajendra Pamula, and Gautam Srivastava, ‘A Systematic Literature Review on Machine Learning Applications for Consumer Sentiment Analysis Using Online Reviews’ (2021) 41 Computer Science Review 100413.

15 Alessandro Arbore and Bruno Busacca, ‘Customer Satisfaction and Dissatisfaction in Retail Banking: Exploring the Asymmetric Impact of Attribute Performances’ (2009) 16(4) Journal of Retailing and Consumer Services 271.

16 Aslam Faheem and others, ‘Sentiments and Emotions Evoked by News Headlines of Coronavirus Disease (COVID-19) outbreak’ (2020) 7(1) Humanities & Social Sciences Communications.

17 Seema Narayan and Paresh Kumar Narayan, ‘Are Oil Price News Headlines Statistically and Economically Significant for Investors?’ (2017) 18(3) Journal of Behavioral Finance 258.

18 Frederick F Reichheld, ‘The One Number You Need to Grow’ en (2003) 88(12) Harvard Business Review 46.

19 Mohamed Zaki and others, ‘The Fallacy of the Net Promoter Score: Customer Loyalty Predictive Model’ (2016) 10 Cambridge Service Alliance 1.

20 David M Blei, Andrew Y Ng, and Michael I Jordan, ‘Latent Dirichlet Allocation’ (2003) 3 The Journal of Machine Learning Research 993.

21 Liudmila Prokhorenkova and others, ‘CatBoost: Unbiased Boosting with Categorical Features’ [2017] arXiv preprint arXiv:1706.09516; Guolin Ke and others, ‘Lightgbm: A Highly Efficient Gradient Boosting Decision Tree’ (2017) 30 Advances in Neural Information Processing Systems 3146; Vladimir Svetnik and others, ‘Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling’ (2003) 43(6) Journal of Chemical Information and Computer Sciences 1947; Tianqi Chen and others, ‘Xgboost: Extreme Gradient Boosting’ (2015) 1(4) R Package Version 0.4–2 1; Yan-Yan Song and LU Ying, ‘Decision Tree Methods: Applications for Classification and Prediction’ (2015) 27(2) Shanghai Archives of Psychiatry 130.

22 Yasunobu Nohara and others, ‘Explanation of Machine Learning Models Using Shapley Additive Explanation and Application for Real Data in Hospital’ (2021) abs/2112.11071 CoRR.

23 Davide Chicco and Giuseppe Jurman, ‘The Advantages of the Matthews Correlation Coefficient (MCC) Over F1 Score and Accuracy in Binary Classification Evaluation’ (2020) 21 BMC Genomics.

24 HRC received 10,000 submissions from members of the public highlighting the nature, magnitude and prevalence of misconduct and conduct falling below community standards in the financial services industry. 2000 of these related policy issues, 621 related superannuation, 222 relating to insurance, and 1114 in response to the Interim Report (Hayne (n 3)).

25 See n 1.

26 Hayne (n 3).

27 ASIC (n 4).

28 Hayne (n 3).

29 See n 1.

30 ASIC (n 4).

31 See n 2.

32 Hayne (n 3).

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