Determining Risk Factors that Diminish Asset Quality of Indian Commercial Banks

Swami, Onkar Shivraj; Nethaji, B.; Sharma, Jyoti

doi:10.1177/0972150919861470

Cited by 11 publications

(9 citation statements)

References 28 publications

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“…A recent literature review on the bank-specific determinants of NPLs is in Swami et al (2019). In brief, previous empirical studies consider the capital adequacy, measured by the specific ratios, (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting the macro determinants of bank credit quality: a non-linear perspective

Fallanca

Forgione

Otranto

2020

JRF

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Purpose This study aims to propose a non-linear model to describe the effect of macroeconomic shocks on delinquency rates of three kinds of bank loans. Indeed, a wealth of literature has recognized significant evidence of the linkage between macro conditions and credit vulnerability, perceiving the importance of the high amount of bad loans for economic stagnation and financial vulnerability. Design/methodology/approach Generally, this linkage was represented by linear relationships, but the strong dependence of bank loan default on the economic cycle, subject to changes in regime, could suggest non-linear models as more appropriate. Indeed, macroeconomic variables affect the performance of bank’s portfolio loan, but such a relationship is subject to changes disturbing the stability of parameters along the time. This study is an attempt to model three different kinds of bank loan defaults and to forecast them in the case of the USA, detecting non-linear and asymmetric behaviors by the adoption of a Markov-switching (MS) approach. Findings Comparing it with the classical linear model, the authors identify evidence for the presence of regimes and asymmetries, changing in correspondence of the recession periods during the span of 1987–2017. Research limitations/implications The data are at a quarterly frequency, and more observations and more extended research periods could ameliorate the MS technique. Practical implications The good forecasting performance of this model could be applied by authorities to fine-tune their policies and deal with different types of loans and to diversify strategies during the different economic trends. In addition, bank management can refer to the performance of macroeconomic conditions to predict the performance of their bad loans. Originality/value The authors show a clear outperformance of the MS model concerning the linear one.

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Section: Literature Reviewmentioning

confidence: 99%

Forecasting the macro determinants of bank credit quality: a non-linear perspective

Fallanca

Forgione

Otranto

2020

JRF

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“…Fixed-effect panel data regression analysis is applied based on the model estimation test, followed by multicollinearity, heteroscedasticity and autocorrelation tests. Panel data regression has been applied in different formats by Menicucci and Paolucci (2016), Saona (2016), Almaqtari et al (2018), Al-Harbi (2019), Swami et al (2019) and Duan and Niu (2020).…”

Section: Methodsmentioning

confidence: 99%

“…For example, Erina and Lace (2013), Ozgur and Gorus (2016), Bucevska and Misheva (2017), Menicucci and Paolucci (2016), Tan et al (2017), Bouzgarrou et al (2018) and Migliardo and Forgione (2018) focused on European countries. Middle Eastern and Asian countries have even been studied more extensively (Adam, 2014; Mehta and Ganga, 2017; Al-Omar and Al-Mutairi, 2008; Tan and Floros, 2012a, b; Tan, 2016; Lee and Isa, 2017; Shawtari, 2018; Sufian and Habibullah, 2009; Batten and Vo, 2019; Swami et al , 2019). Latin American and African countries were relatively understudied (Abel and Le Roux, 2016; Olalekan and Adeyinka, 2013 and Saona 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

What drives the performance of different bank-ownership types in Indonesia? The pre- and post-GFC analysis

Atahau

Cronje

2021

IJPPM

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PurposeThe Indonesian banks play crucial roles in the economy, especially because of less developed bond and stock markets. It has undergone drastic changes in bank-ownership composition over time. This paper aims to analyze the impact of bank-specific characteristics on the performance of different bank-ownership types in Indonesia to determine whether their profitability drivers differ.Design/methodology/approachFixed-effect panel data regression is applied to 1,649 bank-year observations (97 banks throughout 2003–2019). It encompasses the pre- and post-global financial crisis (GFC) period.FindingsThe findings show that age, liquidity, equity and credit risk are significant determinants of bank performance. The significance of these effects differs for each bank-ownership type and show changes between the pre-GFC and post-GFC periods.Research limitations/implicationsNotwithstanding the merit of this paper, the results are not without limitations. This paper only focuses on one country. Furthermore, the prominence of banks relative to bond and stock markets with consideration of the GDP of countries may result in different findingsPractical implicationsThese findings provide the owners and managers of banks with information that can be applied to compare and assess own bank drivers and performance to enhance their own efficiency. The findings also inform bank authorities and regulators about differences in performance drivers that could be considered in changes to policies aimed at improving the performance of different bank-ownership types.Originality/valueThis paper is a pioneer study that focuses on the drivers of bank performance for different ownership types during the pre- and post-GFC periods in a country where the financial market is overall small and bank credits dominate capital supply.

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“…The size of banks has an impact on several aspects of Indian banks, such as their exposure to NPAs (Swami et al, 2019). However, larger banks with more employees may have the advantage of reaching a broader customer base.…”

Section: Hypothesesmentioning

confidence: 99%

Operational and policy efficiency: a comparison between public and private Indian banks

Kundu

Banerjee

2021

IJPPM

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PurposeThis paper introduces the concept of policy efficiency of banks as their efficiency in implementing the government's policies. It further compares the Indian public sector banks (PSBs) and private sector banks (PVBs) on two efficiency paradigms, operational efficiency and policy efficiency.Design/methodology/approachA three-stage analysis is carried out on data collected for 19 PSBs and 16 PVBs for ten years. Non-radial DEA with slack-based measure (SBM) is used to obtain efficiency scores of the banks for the two efficiency paradigms. The efficiency scores and the changes in efficiency and Malmquist index are further analysed by Tobit regression and seemingly unrelated regression (SUR) models.FindingsPVBs are found to be more operationally efficient than PSBs. On the contrary, PSBs are found to be more policy efficient. Among the PSBs, the older and larger banks performed better in both the paradigms. Though Indian banks have become more operational and policy efficient over the years, the rate of improvement is slowing down.Practical implicationsResults imply that evaluating banks, especially PSBs, only on their operational efficiency is myopic. Their efficacies must also be measured by the roles they play on social and policy front. The loss of efficiency of Indian PSBs in a competitive environment should provoke thoughts of reforms. The study suggests that the proposed merger of PSBs to form large banks might be fruitful.Originality/valueThe study contributes to the literature by introducing the measure of policy efficiency. It shows that the Indian PSBs are indispensable as vehicles of government policy implementation.

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Determining Risk Factors that Diminish Asset Quality of Indian Commercial Banks

Cited by 11 publications

References 28 publications

Forecasting the macro determinants of bank credit quality: a non-linear perspective

Forecasting the macro determinants of bank credit quality: a non-linear perspective

What drives the performance of different bank-ownership types in Indonesia? The pre- and post-GFC analysis

Operational and policy efficiency: a comparison between public and private Indian banks

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