The relationship between risk, capital and efficiency in Indian banking: Does ownership matter?

2019 ◽  
Vol 11 (2) ◽  
pp. 218-231
Author(s):  
Sanjukta Sarkar ◽  
Rudra Sensarma ◽  
Dipasha Sharma
Keyword(s):  
Public Sector ◽  
Credit Risk ◽  
Large Data ◽  
Foreign Banks ◽  
Risk Capital ◽  
Lower Efficiency ◽  
Data Set ◽  
Content Type ◽  
Balance Sheets ◽  
Indian Banks

Purpose This paper aims to examine the interplay between risk, capital and efficiency of Indian banks and study how their relationship differs across different ownership types. Design/methodology/approach Panel regression techniques are used to analyze a large data set of all Indian scheduled commercial banks operating during the period 2008-2016. Findings The results show that lower efficiency is associated with higher credit risk in the case of public sector and old private sector banks (”bad management hypothesis”). However, higher efficiency leads to higher credit risk in the case of foreign banks (“cost skimping hypothesis”). The authors further find that the more efficient institutions among public sector hold more capital. Finally, they find that the better-capitalized banks among those in the public sector have lower risks on their balance sheets (“moral hazard hypothesis”). Originality/value There is a paucity of papers on the interplay between risk, capital and efficiency of banks in emerging economies. This paper is the first to study the inter-relationship between risk, capital and efficiency of Indian banks across ownership groups using a number of different measures of risk.

Exploring the effect of intellectual capital on financial performance: a study of Indian banks

2020 ◽  
Vol 24 (4) ◽  
pp. 511-529 ◽  
Author(s):  
Faizi Weqar ◽  
Ahmed Musa Khan ◽  
Syed Mohammed Imamul Haque
Keyword(s):  
Financial Performance ◽  
Intellectual Capital ◽  
Value Added ◽  
Physical Capital ◽  
Foreign Banks ◽  
Data Set ◽  
Content Type ◽  
Study Results ◽  
Nationalised Banks ◽  
Indian Banks

Purpose The purpose of this paper is to inspect the effect of intellectual capital (IC) on the financial performance (FP) of Indian banks. Design/methodology/approach The study uses the data of 58 Indian banks, namely, 20 nationalised banks, 17 private Indian banks and 21 private foreign banks, for the period between 2009 and 2018. A modified value-added intellectual coefficient methodology was used for measuring the efficiency of the IC. Findings The efficiency of IC significantly enhances the profitability and productivity of the Indian banks. Overall, human capital is the most substantial component of IC in augmenting the profitability and productivity of the Indian banking industry. Structural capital and physical capital are vital only for improving profitability while the contribution of relational capital towards the banks’ FP is nominal. The result also shows that amongst the three categories of Indian banks, private foreign banks are most efficient in leveraging their IC. Research limitations/implications The study results are only restricted to Indian banks and the data of only 58 banks are used for drawing the inferences. Originality/value The paper fills the void in the existing literature of IC and corporate FP by using the data set of Indian banks divided into the public sector, private Indian and private foreign banks.

Assessing the impact of global financial crisis on the intermediation efficiency of Indian banks in the presence of non-performing loans

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anju Goswami
Keyword(s):  
Public Sector ◽  
Financial Crisis ◽  
Technical Efficiency ◽  
Global Financial Crisis ◽  
Foreign Banks ◽  
Undesirable Output ◽  
Content Type ◽  
Public Sector Banks ◽  
Indian Banks ◽  
The Impact

PurposeBy incorporating the role of nonperforming loans (NPLs), the study aims to assess the impact of global financial crisis (GFC) on the intermediation efficiency of Indian banks for the period of 1998/99 to 2016/17.Design/methodology/approachTo obtain efficiency level of Indian banks, this study applied sequential data envelopment analysis (DEA) based directional distance function (DDF) approach, which performed simultaneous expansion of desirable output and reduction of undesirable output in the bank's loan production structure. Additionally, using fixed effect regression approach in the panel data framework, this study assesses both the phenomenon of σ- and unconditional β-efficiency convergence in public sector banks (PSBs), private banks (PBs), foreign banks (FBs) and overall scheduled commercial banks (SCBs) during the pre-crisis, crisis and post-crisis years in India.FindingsIrrespective of the bank's production model, the evidence suggests that the accounting NPLs as an undesirable output significantly deteriorating the intermediation technical efficiency levels of Indian banks, especially after the crisis years until the last year of the study period. This reflects that Indian banks failed more to achieve their financial intermediation objective in the post-crisis years as compared to the crisis and pre-crisis years. In-depth, statistical evidence of commercial bank ownership groups reveals that public sector banks exhibit a higher level of efficiency in pursuance of traditional loan-based activity followed by private and foreign banks. The study also found the existence of sigma convergence in technical efficiency levels of Indian banks and ownership groups as well.Originality/valueThis study is perhaps the first one, which present the robust evolution of Indian banks intermediation efficiency by taking into account both endogenous (i.e. NPLs as an undesirable output and equity as a quasi-fixed input in the bank production process) crisis and exogenous (i.e. global financial and economic stress) crises. Moreover, none of the existing studies have conducted sub-period wise analysis to show the apparent occurrence of both convergence properties in technical efficiency, adding novelty in the literature.

User password repetitive patterns analysis and visualization

2016 ◽  
Vol 24 (1) ◽  
pp. 93-115 ◽  
Author(s):  
Xiaoying Yu ◽  
Qi Liao
Keyword(s):  
Security Policy ◽  
Large Data ◽  
Efficient Algorithms ◽  
Privacy And Security ◽  
Data Set ◽  
Web Based ◽  
Content Type ◽  
Word Cloud ◽  
Individual Privacy ◽  
Password Security

Purpose – Passwords have been designed to protect individual privacy and security and widely used in almost every area of our life. The strength of passwords is therefore critical to the security of our systems. However, due to the explosion of user accounts and increasing complexity of password rules, users are struggling to find ways to make up sufficiently secure yet easy-to-remember passwords. This paper aims to investigate whether there are repetitive patterns when users choose passwords and how such behaviors may affect us to rethink password security policy. Design/methodology/approach – The authors develop a model to formalize the password repetitive problem and design efficient algorithms to analyze the repeat patterns. To help security practitioners to analyze patterns, the authors design and implement a lightweight, Web-based visualization tool for interactive exploration of password data. Findings – Through case studies on a real-world leaked password data set, the authors demonstrate how the tool can be used to identify various interesting patterns, e.g. shorter substrings of the same type used to make up longer strings, which are then repeated to make up the final passwords, suggesting that the length requirement of password policy does not necessarily increase security. Originality/value – The contributions of this study are two-fold. First, the authors formalize the problem of password repetitive patterns by considering both short and long substrings and in both directions, which have not yet been considered in past. Efficient algorithms are developed and implemented that can analyze various repeat patterns quickly even in large data set. Second, the authors design and implement four novel visualization views that are particularly useful for exploration of password repeat patterns, i.e. the character frequency charts view, the short repeat heatmap view, the long repeat parallel coordinates view and the repeat word cloud view.

Which professional skills value more under digital transformation?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sofia Paklina ◽  
Elena Shakina
Keyword(s):  
Text Mining ◽  
Labour Market ◽  
Empirical Evidence ◽  
Labour Force ◽  
Sample Selection ◽  
Large Data ◽  
Hedonic Pricing ◽  
Data Set ◽  
Content Type ◽  
Computing Skills

PurposeThis study seeks to explore the demand side of the labour market influenced by the digital revolution. It aims at identifying the new composition of skills and their value as implicitly manifested by employers when they look for the new labour force. The authors analyse the returns to computing skills based on text mining techniques applied to the job advertisements.Design/methodology/approachThe methodology is based on the hedonic pricing model with the Heckman correction to overcome the sample selection bias. The empirical part is based on a large data set that includes more than 9m online vacancies on one of the biggest job boards in Russia from 2006 to 2018.FindingsEmpirical evidence for both negative and positive returns to computing skills and their monetary values is found. Importantly, the authors also have found both complementary and substitutional effects within and between non-domain (basic) and domain (advanced) subgroups of computing skills.Originality/valueApart from the empirical evidence on the value of professional computing skills and their interrelations, this study provides the important methodological contribution on applying the hedonic procedure and text mining to the field of human resource management and labour market research.

scholarly journals Translating emotional insights from hospitality employees’ comments

2018 ◽  
Vol 32 (1) ◽  
pp. 75-92 ◽  
Author(s):  
Lisa M. Young ◽  
Swapnil Rajendra Gavade
Keyword(s):  
Job Satisfaction ◽  
Sentiment Analysis ◽  
Big Data Analytics ◽  
Large Data ◽  
Hospitality Management ◽  
Data Set ◽  
Employee Survey ◽  
Content Type ◽  
Employee Job Satisfaction ◽  
The Usa

PurposeThe purpose of this paper is to use the data analysis method of sentiment analysis to improve the understanding of a large data set of employee comments from an annual employee job satisfaction survey of a US hospitality organization.Design/methodology/approachSentiment analysis is used to examine the employee comments by identifying meaningful patterns, frequently used words and emotions. The statistical computing language, R, uses the sentiment analysis process to scan each employee survey comment, compare the words with the predefined word dictionary and classify the employee comments into the appropriate emotion category.FindingsEmployee responses written in English and in Spanish are compared with significant differences identified between the two groups, triggering further investigation of the Spanish comments. Sentiment analysis was then conducted on the Spanish comments comparing two groups, front-of-house vs back-of-house employees and employees with male supervisors vs female supervisors. Results from the analysis of employee comments written in Spanish point to higher scores for job sadness and anger. The negative comments referred to desires for improved healthcare, requests for increased wages and frustration with difficult supervisor relationships. The findings from this study add to the growing body of literature that has begun to focus on the unique work experiences of Latino employees in the USA.Originality/valueThis is the first study to examine a large unstructured English and Spanish text database from a hospitality organization’s employee job satisfaction surveys using sentiment analysis. Applying this big data analytics process to advance new insights into the human capital aspects of hospitality management is intriguing to many researchers. The results of this study demonstrate an issue that needs to be further investigated particularly considering the hospitality industry’s employee demographics.

Performance of agricultural cooperative banks in Japan

2019 ◽  
Vol 80 (1) ◽  
pp. 38-50
Author(s):  
Kozo Harimaya ◽  
Koichi Kagitani
Keyword(s):  
Stochastic Frontier ◽  
Ordinary Least Squares ◽  
Agricultural Cooperatives ◽  
Least Squares Regression ◽  
Business Services ◽  
Lower Efficiency ◽  
Data Set ◽  
Content Type ◽  
Banking Business ◽  
Insurance Business

Purpose The purpose of this paper is to investigate the efficiency of the banking business of Japan’s agricultural cooperatives (JAs), which depend heavily on financial business with non-farmers, contradictory to cooperative principles. Design/methodology/approach The authors construct a panel data set over 2005–2016 from the financial statements of JAs’ prefectural-level federations and use the input distance stochastic frontier model with a time-variant inefficiency effect for analysis. Both the flow and stock measures of the banking output are used in identical models and the efficiency results are compared. The authors also investigate the determinants of efficiency by using the Tobit and ordinary least squares regression models. Findings There is strong evidence of significant prefectural differences in efficiency values. The ratio of lending to non-members to total loans is positively related to efficiency. In contrast, the higher reliance on a central organization and credit business leads to lower efficiency. Research limitations/implications Apart from banking, JAs provide mutual insurance business services. As the authors investigate only the efficiency of JAs’ banking business in this study, it would be necessary to investigate the efficiency of their insurance business as well when evaluating JAs’ overall financial business. Originality/value There are few studies that investigate the efficiency of JAs’ banking business and its determinants, although significant attention has been paid to their excessive dependence on the financial business.

Market concentration, diversification and bank performance in China and India

2016 ◽  
Vol 42 (10) ◽  
pp. 980-998 ◽  
Author(s):  
Thanh Pham Thien Nguyen ◽  
Son Hong Nghiem
Keyword(s):  
Cost Efficiency ◽  
Market Concentration ◽  
Two Stage ◽  
Profit Efficiency ◽  
Data Set ◽  
Content Type ◽  
Bootstrap Procedure ◽  
Chinese Banks ◽  
Using Data ◽  
Indian Banks

Purpose The purpose of this paper is to examine the operational efficiency and effects of market concentration and diversification on the efficiency of Chinese and Indian banks in the 1997-2011 period. Design/methodology/approach This study employs the two-stage bootstrap procedure of Simar and Wilson (2007) to obtain valid inferences on the efficiency scores and the efficiency determinants. Findings Using data set for each country separately, the authors found that the bias-corrected cost efficiency displays an upward trend in Chinese and Indian banks. This trend is consistent with profit efficiency among Chinese banks, but the trend is unclear in Indian banks. Market concentration is negatively related to cost and profit efficiencies of Chinese banks. However, market concentration is positively associated with cost efficiency, but unrelated to profit efficiency of Indian banks. In Chinese banks, diversification of revenue, earning assets and non-lending earning assets are associated with increasing profit efficiency, but their effects to cost efficiency are not clear. In Indian banks, diversification of earning assets increases profit efficiency while there are cost efficiency losses from diversification of revenue and earning assets. Practical implications Bank regulators and supervisors in China should consider establishing policies to reduce market concentration and encourage diversification of revenue, earning assets and non-lending earning assets, while increasing concentration and diversification of earning assets should be encouraged in Indian banks. Originality/value To the best of the authors’ knowledge, this is the first study employing the double bootstrap procedure proposed by Simar and Wilson (2007) which can address the problem of the two-stage data envelopment analysis or SFA estimator in the efficiency literature on Chinese and Indian banks that efficiency scores obtained in the first stage are inter-dependent, and hence violating the basic assumption in regression analysis in the second stage.

Fast growth may avert foreign banks' exit from Hungary

2015 ◽  
Keyword(s):  
Financial Institutions ◽  
Banking Sector ◽  
Prime Minister ◽  
Foreign Banks ◽  
Content Type ◽  
Balance Sheets ◽  
Government Relations ◽  
Local Currency ◽  
Wait And See ◽  
The Government

Subject Prospects for the banking sector. Significance The government is buying a 30% stake in the Austrian lender Erste Bank under a memorandum of understanding (MoU) with the European Bank for Reconstruction and Development (EBRD). The MoU signifies a volte-face by Prime Minister Viktor Orban, whose relationship with foreign-owned banks has been fraught with difficulties since the imposition of a levy on financial institutions in 2010 that drove down earnings and achieved notoriety as one of the highest taxes of its kind in Europe. The government has pledged to reduce the bank tax during 2016-19. Impacts The MoU may not redefine government relations with foreign banks, but could mean more activity on the market by institutional investors. Banks will clean up balance sheets, adopting a 'wait and see' strategy until FX debt relief peters out and the bank tax starts to fall. A return to profitability is unlikely before 2016; much depends on an uptake in corporate and household loans denominated in local currency.

Determinants of loan losses of Indian Banks: a panel study

2015 ◽  
Vol 9 (1) ◽  
pp. 17-32 ◽  
Author(s):  
Satyajit Dhar ◽  
Avijit Bakshi
Keyword(s):  
Public Sector ◽  
Panel Data Analysis ◽  
Capital Adequacy ◽  
Content Type ◽  
Specific Factors ◽  
Indian Banks ◽  
Loan Losses ◽  
The Impact ◽  
Bank Specific Factors

Purpose – The purpose of this paper is to examine the factors that influence the variability of loan losses (termed as non-performing advances or NPA in India) of Indian banks in the public sector during the period of five years from 2001 to 2005. Design/methodology/approach – The analysis is based on a panel approach, which considers both spatial and time dimensions of observations. Panel regression was used to explore the impact of different bank-specific factors on NPAs of 27 public sector banks (PSBs). Standard tests were used to find out suitability of different models of panel data analysis. Eight bank-specific factors were identified for analysis on the basis of review of extant literature. Findings – Certain bank-specific factors, in particular, net interest margin and capital adequacy ratio exhibit negative and significant impact on gross non-performing advances (GNPA) ratio of Indian PSBs. The results also suggest that relative quantum of sensitive sector (SEN) (comprised of commercial real estate, commodity and capital market) advances has a positive relationship with NPA ratio, and such a relationship is statistically significant. Research limitations/implications – The sample is restricted to India and may not be reflective of other countries. The study considers bank-level factors, and there are some macro factors (e.g. gross domestic product, interest rate and inflation rate) which could have explained the variability of GNPA ratio. Practical implications – Provisioning against loan losses is a major issue for stability of the banking system. Identification of appropriate causes of variability of such loan losses is important for managing credit portfolio of a bank. A positive and significant relationship between SEN advances and NPA calls for a more cautionary approach toward lending to those sectors. Originality/value – This paper is believed to be the first attempt to empirically examine the role of bank-specific factors. This study attempts to enrich empirical research in the field and provides an insight into the role of various bank-specific factors on loan losses in the context of Indian PSBs. The study provides contrary evidence regarding the role of priority sector advances on a GNPA ratio.

Reconciling information gaps in organic farm borrowers’ dealings with farm lenders

2015 ◽  
Vol 75 (4) ◽  
pp. 469-483 ◽  
Author(s):  
Ghangela Jones ◽  
Cesar Escalante ◽  
Hofner Rusiana
Keyword(s):  
Credit Risk ◽  
Organic Farms ◽  
Data Set ◽  
Risk Appraisal ◽  
Content Type ◽  
Credit Access ◽  
Organic Farm ◽  
Organic Farmers ◽  
Credit Risk Measurement ◽  
Information Gaps

Purpose – Organic outputs have been increasing at much lower rates than growth in consumer demand. Organic farmers’ debt aversion hinders them from obtaining business funds through borrowing. The purpose of this paper is to clarify that the farmers’ reluctance to use debt as a funding option can be more attributed to gaps in existing borrower-lender relationships, beyond sustainability principles. Design/methodology/approach – Empirical evidence collected from organic farmers and farm lenders establish differing expectations and perceptions that reinforce the organic farmers’ debt aversion. The farm lender survey data set was analyzed using the Heckman approach applied to two lenders’ decisions: their interest in lending to organic farm borrowers and loan amounts approved for successful loan applicants. The econometric results were reconciled with the compiled inputs provided by organic farmers interviewed. Findings – Results validate the farmers’ lower reliance on loans due to suspicions that lenders lack knowledge and consideration of organic farming conditions and principles. Farm lenders must depart from employing a uniform credit risk appraisal model and adopt borrower-specific versions of the model, but not necessarily delineating organic-conventional farming dichotomy that may not substantially affect credit risk measurement. Organic farms, on the other hand, need to better understand the credit risk appraisal principles and use their inherent business strengths to compete for loans with conventional farms without any special consideration. Practical implications – Borrower-lender relationships can improve if information gaps between lenders and borrowers can be minimized with more extensive outreach education efforts. Better relationships would increase organic farms’ credit access to effectively address an impending supply gap in an expanding industry. Originality/value – To the knowledge, a specific focus on organic farms in understanding farm borrower-lender relationships has never been explored in literature.

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