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In the post-Enron era around the world, the role of auditor is widely debated. There is an increasing concern that an auditor’s continuous involvement with clients could impair audit quality – the negative view. There is also a positive view that a long auditor tenure leads to accumulation of client-specific knowledge over time, which could lead to high-quality audits. The empirical result with regards to impact of mandatory auditor rotation (MAR) is mixed world-wide. This study aims to examine whether MAR rules implemented in 2017 impact audit quality in India.

Using a unique setting in which MAR was required from 2017 to 2018 onwards in India, this study provides empirical evidence of the impact of MAR regulation on audit quality (modified audit opinion). The study uses data for 714 firms (4,284 firms) for six years (three years before MAR and three years after MAR regulation in India).

The study found that auditor tenure and MAR had significant negative impacts on audit quality, validating the “positive” view of audit tenure and audit quality. In addition, concentrated ownership had a negative impact on audit quality, implying the control and influence by concentrated ownership on auditors and audit opinion. The analysis shows that MAR regulation has not yielded the intended objective of improving audit quality in India. MAR is not a good template for improving audit quality.

The findings of the study are useful to policymakers, regulators, managers, investors and users of financial reports. The study calls for public policy on auditor rotation based on objective scientific evidence. In light of the evidence in India that MAR does not lead to better audit quality, the study calls for reset of regulatory policy in India.

The study provides valuable insights to analysts, regulators and other users of financial accounts about the implications of MAR in India.

The study is one of the few to report on the impact of MAR, particularly in the context of an emerging market economy such as India.

The purpose of this study is to examine whether the quality of financial reporting has improved after the adoption of International Financial Reporting Standards (IFRS) in Europe and across the world. The study investigates the impact of IFRS on income smoothing and earnings management in different geographic regions under different legal origins and disclosure environments.

To measure income smoothing in the pre- and post-IFRS periods, the authors use the coefficient of variation and the panel unit root model proposed by Im et al. (2003) for testing whether net income is stationary throughout the sample period. The study uses a dynamic panel estimation framework, as it captures the dynamics of IFRS on discretionary accruals efficiently. Discretionary accruals are used to measure earnings management.

The results suggest that the adoption of high quality standards, such as IFRS, reduces income smoothing and earnings management. In addition, the study finds that earnings management has decreased in the post-IFRS period, in particular, for French and Scandinavian civil law countries, but not for German civil law countries and common law countries. The latter can be explained by the fact that common law countries have strong investor protection laws, strict law enforcement and high disclosure levels of financial information. The study also finds empirical evidence that the adoption of IFRS reduces earnings management in countries with high levels of financial disclosure. Overall, the study shows that the adoption of IFRS improved the quality of financial reporting.

This study is useful for accounting standard setters across the world, including those countries that have not yet decided to adopt IFRS. The study contributes to the literature by examining the adoption of IFRS in income smoothing and earnings management under different legal regimes and disclosure environments by using advanced empirical methodologies.

The purpose of this paper is to examine whether the stock market in India is efficient in the semi-strong form.

The study uses financial and stock market data of 1,135 listed Indian companies (non-financial) during 2003–2011 collected from Capital IQ to estimate discretionary accruals (DA) using modified Jones model (1995). The study also examines using the widely used Mishkin (1983) test to whether equity market prices accruals in India. The study is conducted for profit/loss-making firms separately as well as for a hedge portfolio of firms based on the lowest to highest accruals.

The empirical study of DA of 1,135 listed Indian companies (non-financial) during 2003–2011 shows that the estimated average DA of the corporate sector in India comes to 1 percent of the total assets of these firms. An empirical analysis whether equity market prices DA in India finds no evidence of investors/market pricing DA. Empirical evidence also finds that the results are invariant for profit/loss-making firms as well as portfolio of firms based on the lowest to highest accruals in the Indian context. The empirical evidence shows that the Indian equity market is inefficient with regard to the incorporation of accruals in expected returns of stocks.

This study builds on the previous literature on accrual pricing in the context of the USA and developed markets. The study extends the empirics to the one of the largest emerging market economy – India. This issue is important not only to investors, but also to policy makers and researchers because the mispricing of accruals could potentially lead to misallocation of capital. The study has implications for stock/firm valuations and cost of equity/capital.

This is the first study for the pricing of accruals and test of semi-strong efficiency of the Indian stock market.

The purpose of this study is to examine the key research question, which is whether fintech innovation for financial inclusion has been successful in India? As fintech has been popular in many countries, there is very little understanding on how successful it has performed in India for financial inclusion. This research attempts to ravel important factors that may or may not have a direct or indirect impact on fintech innovation for financial inclusion, thereby dissecting the empirical data to reveal important information for the reader.

This study covers a comprehensive literature review, from which key variables are discovered, then develops hypotheses to be examined, followed by proposing a research model. The survey data examines important research instruments for fintech inclusion in India, identifying and measuring factors, leading to partial least squares (PLS) model testing. Finally, the key findings are reported.

The findings reveal that fintech innovation from variables such as users experience and motivation for digital payments drives usefulness and ease of use leading to financial inclusion. The security, trust, transparency and customer support when built into the fintech innovation for digital payments influences perceived ease of use (PEOU) and usefulness that mediates to uplift financial inclusion directly. Whereas perceived usefulness (PU) anchoring happens to be a precursor for the financial inclusion. On the contrary, cultural values for fintech innovation through PEOU and usefulness had no impact whatsoever on financial inclusion, thus demystifying cultural influences as non-influential factor.

Research limitations are that the study was conducted in India, and may not be generalised in other countries; however, it can be modified to fit future research. Survey data captured was from a particular region of South India, which may differ from the rest of the country. The sample size and research period were adequate; however, larger data sets would be more meaningful for longitudinal studies. As India is the second most populous country in the world, a comparison with other similar countries of the same size and geographical location will be useful for future research.

This research reveals that financial inclusion is much more complex than previously known and that the penetration of fintech has the capacity to go deeper and include a large number of people into the mainstream financial system and ameliorate the inequities in urban-rural gender and caste. The user’s experience, culture and motivations positively influenced the usefulness and ease of use for driving the financial inclusion of digital payments. Further security, trust, transparency and customer support can facilitate the use of central bank digital currency (CBDC) as a tool for financial inclusion.

Fintech innovation for financial inclusion is based on the successful acceptance of the digital payment system by people in the society. This research has identified that for any fintech innovation, it is essential that society needs to benefit from it. Encouraging a larger population to switch to digital payments offer challenges and opportunities. While the opportunities are enormous research suggests that early adopters of new technology go through different phases of testing, in which a society can completely accept an innovation or can completely reject an innovation if the two mediating factors such as PU and ease of use do not perform as predicted, thus having a higher failure rate. On the other side, if such an innovation as fintech becomes successful it has the capacity to bring billions of people into mainstream financial inclusion, a success story that can greatly benefit the Indian society and which can be replicated among other countries in the world.

To the best of the authors’ knowledge, this study is the first attempt in an effort to understand the influential factors from the point of view of users for the adoption of CBDC for financial inclusion. The main contribution of this paper is to examine the role of CBDC as an instrument to foster financial inclusion in India, which has not been attempted so far. The originality also lies to the heart of the research is dissecting and making meaningful sense of the empirical data, developing and measuring research instruments and hypotheses and finally adopting a PLS model to answer the key research question, which is whether fintech innovation for financial inclusion can be successful for India?

The academic literature has examined why bank runs happen based on the work of 2022 Nobel Prize-winning economists Diamond and Dybvig. They have found the source of banking/financial crisis in terms of mismatch between liabilities (deposits being short term and savers wanting to short-term access to their money) and assets (long term and illiquid). The Lakshmi Vilas Bank (LVB) crisis intensified when it came under Prompt Corrective Action (PCA) of the Reserve Bank of India (RBI). This situation provides the opportunity to study whether the elements embodied in the theoretical models like Diamond and Dybvig hold true for LVB crisis. This study aims to examine the reasons for the demise of LVB in India using DuPont financial model, peer group analysis and time series structural break in crucial financial parameters.

The study examines the reason for insolvency of LVB using financial ratios, financial models (DuPont), financial distress model (Z-score) and asset-liability management. The study also adopts univariate structural break models using quarterly financial data covering the key financial measures used in the RBI’s PCA framework.

LVB crisis is like Diamond–Dybvig model, in the sense, savers requiring short-term access to their money (liquidity for their deposits) on the information of high non-performing assets, which further deteriorates the illiquid nature of loan portfolio (assets) of banks. The study finds its profit margin (net interest margin and non-interest margin) and managerial efficiency had started deteriorating since 2018. The study finds that LVB’s main weakness lies in its limited credit appraisal ability, its monitoring and weak internal controls. Lending to sensitive sectors (like real estate, capital markets and commodities) and exposure to large business groups also contributed to its weakness. The study also finds huge, elevated asset-liability mismatch, especially in the short-term maturity buckets. Using univariate econometric time series model, the study also confirms financial weakness being evident much earlier than the time when resolution was undertaken by the RBI through PCA.

The study has implications for analysing and monitoring financial distress of banks. The study also has implications for devising banking regulation and supervision.

The study brings in a perspective of the banking regulations using the application of PCA framework on a listed private sector bank. The authors combine an accounting ratio model and combine risk measures that could identify the incipient risks in a bank. The authors believe this will help in refinement of banking regulations and better monitoring mechanisms.

Financial analysts have been found to be overconfident. The purpose of this paper is to study the ramifications of that overconfidence on the dispersion of earnings estimates as a predictor of the US business cycle.

Whether aggregate analyst forecast dispersion contains information about turning points in business cycles, especially downturns, is examined by utilizing the analyst earnings forecast dispersion metric. The primary analysis derives from logit regression and Markov switching models. The analysis controls for sentiment (consumer confidence), output (industrial production), and financial indicators (stock returns and turnover). Analyst data come from Institutional Brokers Estimate System, while the economic data are available at the Federal Reserve Bank of St Louis Economic Data site.

A rise in the dispersion of analyst forecasts is a significant predictor of turning points in the US business cycle. Financial analyst uncertainty of earnings estimate contains crucial information about the risks of US business cycle turning points. The results are consistent with some analysts becoming overconfident during the expansion period and misjudging the precision of their information, thus over or under weighting various sources of information. This causes the disagreement among analysts measured as dispersion.

This is the first study to show that analyst forecast dispersion contributions valuable information to predictions of economic downturns. In addition, that dispersion can be attributed to analyst overconfidence.

This study aims to examine earnings management around initial public offerings (IPOs) in India. It also explores the influence of issue characteristics on earnings management around the IPOs.

A sample of 511 IPOs that came during April 2003-March 2019 is studied for calculating earnings management for pre-issue, issue and post-issue years. Using Cross-Sectional Modified Jones Model, the paper presents earnings management on the basis of three proxies i.e. discretionary accruals, discretionary current accruals and discretionary long-term accruals. The influence of issue characteristics on earnings management practised around the IPOs is also observed through correlation and multiple regression analysis.

The paper finds that earnings management is abnormally high during the issue year compared with pre-issue and post-issue years. It also unveils that profitability, premium, age, and size of the issuer significantly determine the level of pre-issue and issue year earnings management practised by Indian IPO issuers.

The findings are useful to stakeholders (potential investors, analysts and regulators) to observe, assess and understand the quality of financial numbers that are based on fallacious disclosure of accounting figures. It provides insight into the possibilities of managed earnings around the issue that could influence investors’ decision-making. Further, the study reflects the efficacy of Indian regulatory norms for IPOs.

To the authors’ knowledge, it is the only Indian study that had used an extensive data set of about two decades to calculate earnings management during pre-issue, issue and post-issue years. The uniqueness of the study further lies in three proxies of earnings management representing short-term and long-term accruals. Moreover, it is the first study to observe the influence of IPO issue characteristics on earnings management.