The Empirical Nexus between Data-Driven Decision-Making and Productivity: Evidence from Pakistan’s Banking Sector

Gul, Raazia; Leong, Kelvin; Mubashar, Ammara; Al‐Faryan, Mamdouh Abdulaziz Saleh; Sung, Anna

doi:10.1080/23311975.2023.2178290

Cited by 5 publications

(5 citation statements)

References 35 publications

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“…Ariff et al ( 2007) spread has emerged as a significant credit risk factor. Nonetheless, the indication was inconsistent for the connection between spread and credit risk, i.e., adverse for the banks in India and Thailand but optimistic for the French banks (Gul, Leong, Mubashar, Al-Faryan, & Sung, 2023). This inverse relationship indicates that a bank that charges its borrower greater interest to maximize its spread would deprive less qualified borrowers (future borrowers) of borrowing, thereby reducing the bank's risk of loan exposure.…”

Section: Bank Spread With Credit Riskmentioning

confidence: 99%

Impact of Bank Specific Factors on Credit Risk: Evidence from Islamic and Conventional Banks of Pakistan

Khan

Ramzan

Kousar

et al. 2023

Pak. J. Humanit. Soc. Sci

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The impact of credit risk (CR) on bank-specific factors (BSF’s) and banks in the event of conventional and Islamic banks of Pakistan is an essential motivation behind this learning. These banks are chosen by their value commitment. The financial explanation investigation of chosen Islamic and conventional banks is contemplated from 2007 to 2017. Relapse examination of non-performing loan (NPL) proportion and Z-Score is utilized to discover the connections of BSF’s on chosen banks. The Islamic banking system consists of (return on equity (ROE), ROA, liquidity, spread and bank size) having a significant relationship toward credit risk. Therefore, the impact of the Z-score is less for Islamic banks relatively compared to conventional banks. The increased risk of bank debt reflects a strong NPL. In this examination bank, certain factors, for instance, efficiency, return on assets (ROA) and bank dimension, have a significant liaison through credit card risk in the conventional selected banking system, and this process affects overall banking performance. These findings provide valuable insights for policymakers, regulators, and banking professionals to manage credit risk effectively in the context of Pakistan's banking system. The originality of this study lies in its focus on the comparison between conventional and Islamic banks in Pakistan, which has yet to be extensively explored in the literature.

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Section: Bank Spread With Credit Riskmentioning

confidence: 99%

Impact of Bank Specific Factors on Credit Risk: Evidence from Islamic and Conventional Banks of Pakistan

Khan

Ramzan

Kousar

et al. 2023

Pak. J. Humanit. Soc. Sci

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“…Some authors provide a concise overview of what big data entails; according to Talaoui et al [29], big data is a digital transformation brought about by the proliferation of numerous data sources that generate massive volumes of datasets at rapid or real-time speeds. Visco et al [30] and Gul et al [31] define big data as information volumes that are significantly larger than what conventional data management methods can handle. Factors driving the prevalence of big data include increased digitization levels, the shift from a data society to an information society, the evolution of social media networks, and the growing use of electronic devices [32,33].…”

Section: The Concept Of Big Datamentioning

confidence: 99%

The barriers and prospects related to big data analytics implementation in public institutions: a systematic review analysis

2023

IJACR

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Undoubtedly, one of the primary drivers of digitization is big data analytics (BDA) [1]. Vast volumes of big data are frequently generated, often in real-time [2]. As Lampropoulos [3] explains, BDA plays a crucial role as the technological foundation for numerous cutting-edge advancements and technologies, including the Internet of Things (IoT), artificial intelligence (AI), autonomous driving (AD), and many others.

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“…The relationship between trade openness [ 8 ], industrialization [ 5 ], foreign direct investment [ 9 ], and environmental taxes [ 10 ] in reducing environmental degradation has also been empirically assessed. Financial growth fosters the financial sector's progression [ [11] , [12] , [13] ]. Many researchers have empirically investigated its relationship with carbon emissions [ 14 , 15 ], and the relevant empirical literature on this nexus is still evolving.…”

Section: Introductionmentioning

confidence: 99%

Relationship between financial inclusion and carbon emissions: International evidence

Hussain¹,

Akbar

Gul

et al. 2023

Heliyon

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The Empirical Nexus between Data-Driven Decision-Making and Productivity: Evidence from Pakistan’s Banking Sector

Cited by 5 publications

References 35 publications

Impact of Bank Specific Factors on Credit Risk: Evidence from Islamic and Conventional Banks of Pakistan

Impact of Bank Specific Factors on Credit Risk: Evidence from Islamic and Conventional Banks of Pakistan

The barriers and prospects related to big data analytics implementation in public institutions: a systematic review analysis

Relationship between financial inclusion and carbon emissions: International evidence

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