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In October 2016, Timothy Sloan, the newly appointed CEO of American banking giant Wells Fargo, faced a massive public-relations crisis. A few weeks earlier, a United States government agency had announced the results of its regulatory review of the bank and exposed a shocking practice common in the retail division, in which aggressive community bankers had created more than a million fraudulent accounts and credit card applications on behalf of unaware customers for the past several years. Over the next few weeks, the bank—and Sloan's predecessor, John Stumpf, in particular—suffered from harsh criticism from politicians, journalists, and former employees alike, ultimately forcing Stumpf's resignation. As Sloan sought to minimize the public-image backlash and restore general trust in Wells Fargo, he struggled to construct the best communication strategy for the bank's next chapter.

This paper compares traditional and digital banks in nine categories of complaints and provides insights to improve complaint management performance.

A sample of the major Brazilian banks was defined, with four traditional and four digital banks. The grey relational analysis (GRA) method was applied as an analytical tool to compare the most frequent complaints of traditional and digital banks. The most critical complaints identified were considered to discuss potential improvements in complaint management using quality and service management system concepts.

The GRA method enabled the development of a ranking of nine complaint categories, considering the uncertainty involved in the data and differentiating between traditional and digital banks. The most critical complaint categories, regardless of business model, were “unauthorized charges” and “poor service,” which were ranked first and second in the frequency rankings. Traditional and digital banks differed the most in the complaint category “unfair charge,” ranking third and eighth in the rankings, respectively.

Managers from traditional and digital banks can improve complaint management performance by applying ISO 9001 and ISO 20000 concepts such as incident, problem, change, service level, availability, capacity, information technology service continuity and financial management.

The study's findings can help bank managers improve service levels in the face of technological competition. Improving these organizations is an important factor for developing countries such as Brazil.

This paper reveals the differences between two business models regarding complaint management. It also considers a methodological approach to include the uncertainty related to customers' perception and subjectivity inherent to complaints.

Purpose: The purpose of this chapter is to offer a discussion on the role played by Central Bank Digital Currency (CBDC) in enhancing financial inclusion. The central interest of the study is to place CBDC on the financial inclusion landscape and provide insights on potential opportunities and barriers in making CBDC a strong building block of financial inclusion, as well as the digital financial system.

Design/methodology/approach: This chapter is a conceptual work that builds on relevant literature. This study identifies and suggests potential aspects that can help in the adoption of CBDC as a tool for financial inclusion.

Findings: This chapter analyses opportunities, barriers, and concerns for CBDC in the context of financial inclusion and discusses how critical functions of blockchain technology can lead to the acceptance and adoption of CBDC. Furthermore, it has been demonstrated how CBDC can pave the way for financial inclusion and benefit the existing financial system taking more people from financial exclusion towards financial inclusion.

Originality/value: This is evident that CBDCs and financial inclusion need to be intertwined to support upcoming technological transformations happening in the digital financial ecosystem. Therefore, CBDCs must be viewed from varying lenses to understand the relevance of including CBDCs in the financial system can be expanded. Further, repercussions from the given framework are suggested.

The Central Bank of Nigeria (CBN) recently relaunched Nigeria’s cashless policy initiative which seeks to reduce financial crime and tax avoidance, decrease cash dependency, advance the adoption of digital financial services (DFS), decrease the risks to the payment system and foster financial inclusion. This study aims to identify the unique challenges of going cashless in Nigeria, particularly in terms of infrastructural, exclusionary and cost implications of the policy on the average citizens.

The author applies a doctrinal research methodology to identify and reflect on key challenges of the cashless policy from the economic, regulatory and transactional perspectives.

The cashless policy initiative in Nigeria heralds value for financial integrity, financial policy regulation and user convenience. The mode of introduction, however, ushers in significant challenges and hardly considers Nigeria’s inadequate payment infrastructure, persistent financial exclusion, low levels of financial and digital literacy and capability, high cost of using DFS and pervasive proclivity for cash. As Nigerians adjust albeit inconveniently to the policy, the CBN can ameliorate the hardship by strengthening the payment infrastructure, particularly for digital payments, fostering consumer trust by safeguarding user funds and enabling consumer preferences.

Research materials include the national regulator’s policy documents and newspaper articles that have not been published in formal reports but non-the-less adequately mirror the policy intention of the CBN and the lived experiences of Nigerians.

This study identifies the practical steps and regulatory measures that the CBN can take to improve acceptance and meaningful and sustainable adoption of the cashless policy by the majority of Nigerians.

The recommendations that are proffered provide some rich insights to inform regulatory direction for the CBN to seamlessly phase-in the cashless policy and consequently drive down financial exclusion in Nigeria.

This study contributes to the policy discussion around the introduction of the cashless Nigeria project. The doctrinal research method highlights the policy intentions of the regulator in juxtaposition with lived experiences of Nigerians. This study offers recommendations to bolster financial inclusion, stability and integrity.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

This research focuses on the Metaverse's evolving trend and the potential application of blockchain technology in the accounting of virtual assets in this digital domain. The Metaverse introduces a new economy in which users may earn real-world revenue through virtual activities, necessitating the need for efficient and dependable virtual asset accounting. Blockchain technology, with its decentralized and immutable record, appears to be a viable answer to these problems. This chapter discusses the present status of blockchain technology for accounting for virtual assets in the Metaverse as well as its potential role for businesses and the economy. It also determines the technology's issues and limits and makes recommendations for further development. The findings indicate that blockchain technology has the potential to transform virtual asset accounting in the Metaverse by improving security, transparency, and consistency. However, scalability and legal/regulatory issues must be overcome before it can completely achieve its promise. Accounting experts, developers, and stakeholders interested in the convergence of blockchain technology and the Metaverse economy will find this chapter useful.

The purpose of this study is to propose a framework for the convergence of maturity model and education and evaluation in accounting.

The present research was conducted in two phases. In the first phase, to determine the indicators of convergence of the maturity model and education and evaluation in accounting, a Meta-Synthesis method was used. The conceptual model includes two dimensions of “Teaching and learning processes” and “Evaluation methods"; five levels of initial, repeatable, defined, managed and optimized; and a total number of 35 indicators. In the second phase, a questionnaire was developed, and academics as accounting faculty members in Iranian public universities were employed to fill out the questionnaire electronically and present a final framework. Having received the questionnaires, 66 questionnaires were analyzed statistically.

The results showed that the two dimensions of “Teaching and learning processes” and “Evaluation methods” considering initial, repeatable, defined, managed and optimized levels include 35 indicators, which form a framework for the convergence of maturity model and education and evaluation in accounting. The results show that both dimensions have positive and significant regression path coefficients in the convergence model. Moreover, the dimension of teaching and learning processes has the highest regression path coefficient indicating a greater impact on the convergence model. Besides, all five levels have positive and significant regression path coefficients with dimensions. Finally, in this study, all indicators were prioritized according to five levels.

Due to the success of maturity models and the urgent developments that require transformative improvements in accounting education, maturity models can respond to the challenges associated with education and learning in accounting. Thus, conceiving an image of the convergence of maturity model, education and evaluation in accounting seems imperative which has been scarcely investigated previously.

To measure the dynamic features of compassion as an emotional and behavioral construct, the present research used a univariate latent growth modeling (LGM) approach within the structural equation modeling (SEM) framework. The aim was to trace the dynamic development of compassion longitudinally in accounting and business students during a three-credit English course at university.

The suggested method ensures the measurement invariance over time, deals with the first order latent variable, traces its growth and takes into account the measurement errors. This longitudinal analytical method was used to explore the initial state and the growth of compassion in four points of time during a language course. The data were collected from 60 adult accounting and business students in four time phases using Sprecher and Fehr's Compassionate Love Scale and were analyzed in Mplus 8.4 with univariate LGM.

The model fit was accepted and the invariance of the latent factor was confirmed over time. The negative covariance between intercept and slope (second-order latent variables) suggested that lower initial scores in L2 learners' compassion show a faster increase in compassion over time as the mean of slope is larger than that of the intercept. L2 learners who started off at a higher level of compassion showed a slower change in compassion over time. This can be at least partly explained by the teacher's motivating role or learners' compassion but needs to be further explored in complementary qualitative phases for deeper insights.

In the present research, awareness was raised of the developmental nature of compassion as an emotional and behavioral construct essential to the accounting and business profession. The great strength of this research lies in the dynamic approach to the compassion construct and the LGM used to capture the temporal growth of compassion and how it evolved through the L2 course.