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1 – 4 of 4Etikah Karyani, Setio Anggoro Dewo, Wimboh Santoso and Budi Frensidy
The purpose of this paper is to highlight the disparity between the disclosures of risk governance (RGOV) categories, namely, structures both at the board and management level…
Abstract
Purpose
The purpose of this paper is to highlight the disparity between the disclosures of risk governance (RGOV) categories, namely, structures both at the board and management level, and RGOV practices among five of the Association of Southeast Asian Nations (ASEAN-5) countries. Furthermore, this paper investigates the effects of RGOV and its categories on return on assets (ROA).
Design/methodology/approach
Using 285 ASEAN-5 bank-year observations comprising hand-collected data for the period of 2010–2014, RGOV indexes are developed on the basis of 12 of the 13 governance guidelines published by the Basel Committee.
Findings
Although some banks are found to be early adopters, there is an increasing trend of disclosure for all of the investigated categories. Furthermore, there are no effects of the overall RGOV, board-level RGOV structure and risk management practice on ROA. However, the effect of the management-level RGOV structure on ROA is negative and significant.
Research limitations/implications
Measurements of RGOV indexes are based solely on the examination of criteria that have not been previously tested. Other limitations are related to the information completeness, subjectivity and interpretation.
Practical implications
Management-level RGOV tends to decrease profitability because of the additional costs related to its implementation. Financial regulators may find this result useful as feedback to evaluate the effectiveness of regulation and possible future improvements.
Originality/value
This paper’s uniqueness lies in constructing new RGOV indexes on the basis of the latest bank governance guidelines from the Basel Committee issued on July 9, 2015.
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Wimboh Santoso, Palti Marulitua Sitorus, Sukarela Batunanggar, Farida Titik Krisanti, Grisna Anggadwita and Andry Alamsyah
The development of information technology is highly influential to all sectors, including the financial industry. Various transformations are made in overcoming the dynamics of…
Abstract
Purpose
The development of information technology is highly influential to all sectors, including the financial industry. Various transformations are made in overcoming the dynamics of technological advancements, including the mapping of human resources. This study is conducted in the banking industry and companies operating using financial technology (FinTech) in Indonesia. This study aims to identify talent competencies needed in the future, based on current conditions and future needs, through mapping talent in the banking and FinTech industries.
Design/methodology/approach
This study provides empirical evidence about the mapping of talent management with eight basic competencies. It uses a mixed-method, explanatory sequential with survey approach in the first phase and focus group discussions (FGD) in the second phase. The questionnaire is distributed to 309 respondents who are the specific decision-makers in this industry. Meanwhile, the FGD is conducted twice at different times with academics and practitioners, human resources and talent managers. This research used analytic hierarchy process as a tool for data processing.
Findings
This study provides current competency positions and future needs in the banking and FinTech industries in Indonesia where it found a lot of competence segregation. It also discovered three priority competencies for dealing with Industry 4.0, which included relating and networking, adapting and responding to change and entrepreneurship and commercial thinking.
Practical implications
This study is valuable for decision-makers and regulators; these results can be used to find new competencies and talents to develop existing human resources. Also, these results can be used as a basis for policy-making related to the Industrial Revolution 4.0.
Originality/value
This study provides new insights on talent mapping in the banking and FinTech industries as a strategic approach in the digitalization era. In addition, this research also adds knowledge related to Industry 4.0 as a result of industry developments in the digitalization era.
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Yohanes Sigit Purnomo W.P., Yogan Jaya Kumar and Nur Zareen Zulkarnain
By far, the corpus for the quotation extraction and quotation attribution tasks in Indonesian is still limited in quantity and depth. This study aims to develop an Indonesian…
Abstract
Purpose
By far, the corpus for the quotation extraction and quotation attribution tasks in Indonesian is still limited in quantity and depth. This study aims to develop an Indonesian corpus of public figure statements attributions and a baseline model for attribution extraction, so it will contribute to fostering research in information extraction for the Indonesian language.
Design/methodology/approach
The methodology is divided into corpus development and extraction model development. During corpus development, data were collected and annotated. The development of the extraction model entails feature extraction, the definition of the model architecture, parameter selection and configuration, model training and evaluation, as well as model selection.
Findings
The Indonesian corpus of public figure statements attribution achieved 90.06% agreement level between the annotator and experts and could serve as a gold standard corpus. Furthermore, the baseline model predicted most labels and achieved 82.026% F-score.
Originality/value
To the best of the authors’ knowledge, the resulting corpus is the first corpus for attribution of public figures’ statements in the Indonesian language, which makes it a significant step for research on attribution extraction in the language. The resulting corpus and the baseline model can be used as a benchmark for further research. Other researchers could follow the methods presented in this paper to develop a new corpus and baseline model for other languages.
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