Search results

Non-performing assets (NPAs) are classified as loans and advances which are in default, either refund of principal or interest payments are not duly met. This not only leads to dishonour of loan agreement from the recipients' point of view but also huge NPAs result macroeconomic instability and economic crisis. The financial crisis may create hindrances towards achievement of sustainable development of an economy. Keeping NPA in balance sheet portrays lacunae in management of the lender. The non-recovery of interest and principal reduces the lender's operating cash flow, which upsets the budget and drops the earnings. Statutory provisions, set aside to cover probable losses, reduce the income further. When the non-recovery is determined to be definite in nature, they are written off against earnings of the lending institution. Thus, presence of NPAs in balance sheet gives a distress signal to the stakeholders of the lending institution. Under this consideration, the present study will look upon some of these issues related to NPA management in Indian banking sector. The main objective of this study is to discuss the nexus between the NPA of Indian scheduled banks for priority sector, non-priority sector and public sector and the gross domestic product (GDP) of Indian economy for the time period 2005–2020. To study this objective, the ratio analysis and the trend analysis of NPA of three sectors and GDP of Indian economy over the given time frame have been done. Finally, some policy prescriptions regarding achievement of sustainable development after taking into account NPA management of an economy have also been proposed.

This study developed a new analytical model to quantify the influence of business intelligence (BI) adoption on bank performance. An in-depth review of academic literature revealed a significant research gap exists in investigating BI's performance impacts, especially in the under-studied Indian banking context. Additionally, customer relationship management (CRM) was incorporated as a moderating variable given banks' large customer databases.

A survey was administered to 413 employees across leading Indian banks to collect empirical data for evaluating the conceptual model. Relationships between variables were analysed using partial least squares structural equation modelling (PLS-SEM). This technique is well-suited for theory building with smaller sample sizes and non-normal data.

Statistical analysis supported the hypothesised positive effect of BI adoption on bank performance dimensions including growth, internal processes, customer satisfaction, and finances. Furthermore, while CRM did not significantly moderate this relationship, its inclusion represents an incremental contribution to the limited academic literature on BI in Indian banking.

The model provides a quantitative basis for strategies leveraging BI's performance benefits across the variables studied. Moreover, the literature review revealed an important knowledge gap and established a testable framework advancing BI theory in the Indian banking context. Significant future research potential exists through model replication, expansion, and empirical verification.

This research thoroughly reviewed existing academic literature to develop a novel testable model absent in prior studies. It provides a robust conceptual foundation and rationale for ongoing scholarly investigation of BI's deployment and organisational impacts.