Purpose – This study aims to develop a high-quality impairment loss allowance model in conformity with Indonesian Financial Accounting Standards 71 (PSAK 71) that has significant contribution to national interests and the banking industry. Design/methodology/approach – The determination of the impairment loss allowance model is settled through 7 stages, using integration of some statistical methods such as Markov chain, exponential smoothing, time series analysis of behavioral inherent trends of probability of default, tail conditional expectation and Monte Carlo simulation. Findings – The model which is developed by the authors is proven to be a high-quality and reliable model. By using the model, it can be shown that the implementation of the expected credit losses model on Indonesian Financial Accounting Standards 71 is more prudent than the implementation of the incurred loss model on Indonesian Financial Accounting Standards 55. Research limitations/implications – Determination of defaults was based on days past due, and the analysis in this study did not touch the aspects of hedge accounting in general. Practical implications – This developed model will contribute significantly to national interests as a source of reference for other banks operating in Indonesia in calculating impairment loss allowance (CKPN) and can be used by the Financial Services Authority of Indonesia (OJK) as a guideline in assessing the formation of impairment loss allowance for banks operating in Indonesia. Originality/value – As so far there is not yet an available standardized model for calculating impairment loss allowance on the basis of Indonesian Financial Accounting Standards 71, the model developed by the authors will be a new breakthrough in Indonesia.

Purpose Financial health of a corporation is a great concern for every investor level and decision-makers. For many years, financial solvency prediction is a significant issue throughout academia, precisely in finance. This requirement leads this study to check whether machine learning can be implemented in financial solvency prediction. Design/methodology/approach This study analyzed 244 Dhaka stock exchange public-listed companies over the 2015–2019 period, and two subsets of data are also developed as training and testing datasets. For machine learning model building, samples are classified as secure, healthy and insolvent by the Altman Z-score. R statistical software is used to make predictive models of five classifiers and all model performances are measured with different performance metrics such as logarithmic loss (logLoss), area under the curve (AUC), precision recall AUC (prAUC), accuracy, kappa, sensitivity and specificity. Findings This study found that the artificial neural network classifier has 88% accuracy and sensitivity rate; also, AUC for this model is 96%. However, the ensemble classifier outperforms all other models by considering logLoss and other metrics. Research limitations/implications The major result of this study can be implicated to the financial institution for credit scoring, credit rating and loan classification, etc. And other companies can implement machine learning models to their enterprise resource planning software to trace their financial solvency. Practical implications Finally, a predictive application is developed through training a model with 1,200 observations and making it available for all rational and novice investors (Abdullah, 2020). Originality/value This study found that, with the best of author expertise, the author did not find any studies regarding machine learning research of financial solvency that examines a comparable number of a dataset, with all these models in Bangladesh.

Purpose This study investigates the characteristics of business and management consulting firms (firm size, international affiliation and scope of operation) affecting the adoption rate (i.e. recency of adopting big data analytics (BDA) as a new idea) and usage level of BDA. Ten critical areas of BDA application to business and management consulting were investigated, (1) Human Resource Management; (2) Risk Management; (3) Financial Advisory Services; (4) Innovation and Strategy; (5) Brand Building and Product Positioning; (6) Market Research/Diagnostic Studies; (7) Scenario-Based Planning/Business Simulation; (8) Information Technology; (9) Internal Control/Internal Audit; and (10) Taxation and Tax Management. Design/methodology/approach Survey data was obtained through a structured questionnaire from one hundred and eighteen (118) consultants in Nigeria from diverse consulting firm settings in terms of size, international affiliation and scope of operation (Big 4/non-Big 4 firms). Data was analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance (MANOVA), multivariate discriminant analysis and multivariable logistic regression. Findings Whereas organizational characteristics such as firm size, international affiliation and scope of operation significantly determine the adoption rate of BDA, two attributes (international affiliation and scope of operation) significantly explain BDA usage level. Internationally affiliated consulting firms are more likely to record higher usage level of BDA than local firms. Also, the usage level of BDA by the Big 4 accounting/consulting firms is expected to be higher in comparison to non-Big 4 firms. Practical implications Contrary to common knowledge that firm size is positively associated with the adoption of an innovation, the study found no evidence to support this claim in respect of the diffusion of BDA. Overall, it appears that the scope of operation is the strongest organizational factor affecting the diffusion of BDA among consulting firms. Originality/value The study contributes to knowledge by exposing the factors promoting the uptake of BDA in a developing country. The originality of the current study stems from the consideration that it is the first, to the researchers' knowledge, to investigate the application of BDA by consulting firms in the Nigerian context. The study adds to literature on management accounting in the digital economy.

The textile and apparel industries play an important role in Vietnam’s economy in general and the manufacturing sector in particular. As a matter of fact, Vietnam ranks as one of the leading suppliers of textile and apparel for major economies in the world, including the European Union. This paper attempts to examine the potential impacts of the European Union - Vietnam Free Trade Agreement on the export of Vietnam’s apparel at three levels: 2, 4, 6–digit HS respectively, assuming full liberalization from Vietnam to European Union by 2026. An analysis is undertaken using WITS-SMART model to identify the variation of Vietnam’s apparel export as well as to predict some most affected products if European Union - Vietnam Free Trade Agreement is in full application. As a result, Vietnam’s apparel exporting to European Union will increase significantly by 42% compared to the base year (2016) and is expected to reach US$4.220 billion in the next 8 years. Due to trade diversion dominates over trade creation effect, Vietnam’s apparels will get more gains than non - European Union - Vietnam Free Trade Agreement members; however, this result is not because of an effective allocation of resources. Therefore, policy makers should implement some remedies to improve the competitivey of Vietnam’s apparels, to reduce the production price to bring advantages for both Vietnam and Europe.

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"Purpose – This paper aims to examine the impact of board governance quality (BGQ) and its mechanisms, namely board activity, board independence, board communication and board expertise, on the level of risk disclosure compliance (RDC) among financial institutions (FIs) in Uganda. Design/methodology/approach – The study adopts a cross-sectional design where data are collected through a questionnaire survey and audited financial statements of 83 FIs. The authors employ partial least square structural equation modeling (SmartPLS32.7) to test hypotheses. Findings – The authors find that the level of RDC in Ugandan FIs is low. Further, the study finds the positive relation between BGQ and RDC. Moreover, the authors find that RDC is positively and significantly related with board activity, board independence, board communication and board expertise. Furthermore, the authors find that the level of RDC is positively and significantly related to ownership type, firm size and board size, respectively. Nevertheless, industry type, number of branches and firm age are insignificantly related to RDC. Practical implications – The study provides relevant insights into regulators and policy makers with early symptoms of potential problems regarding weak board governance in FIs. Policy makers may also use these findings as a guideline tool for improving existing board governance frameworks in place and development of new disclosure policies. In addition, the study provides an input into the review and amendments of existing corporate governance codes for the regulators. Originality/value – This study offers the empirical evidence on the nexus between BGQ and RDC of FIs in Uganda. Moreover, the study also offers evidence on how BGQ mechanisms impact RDC. The study also further adds theoretical foundations to the RDC literature."