Purpose

Banks in India have started opening their branches in different areas to make sure that their customers get a high-touch experience and they see them as a premier brand. This could be ensured only if the banks show a stable physical presence in the market as well as provide the recent high-tech services to their customers as per the population group. The purpose of this study is to examine the survival rates of the commercial banks in India across the four population groups along with the differences that exist in their survival rates in all the population groups.

Design/methodology/approach

The analysis is based on the quarterly data of the number of functioning offices of the commercial banks in India as per the four population groups from March 2006 to December 2019. The survival is estimated using the Kaplan–Meier estimator.

Findings

From the analysis, it is revealed that survival of the banks changes as per the population group. In addition to this, it is found that the survival time of each category of the bank varies in each population group.

Research limitations/implications

This study focuses only on the commercial banks of India; a similar research could be done for other categories of Indian banks. Also, the results would have been different if the variables such as the size of the bank, bank risk, etc. are included and studied. Moreover, this study is done using the Kaplan–Meier estimator, i.e. time-to-event. Further, an advance study could be done after considering the financial parameters of banks using the Cox’s regression model, which explores the relationship between various predictors and the time-to-event.

Social implications

Due to the changes in the preferences of societies, the banks should also adopt different strategies to ensure that their products are understood and accepted by their customers. This will eventually increase the survival rate of the banks.

Originality/value

The work made in this study is completely new.

中文翻译：

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人口群体与银行：印度商业银行生存分析的比较研究

目的

印度的银行已开始在不同地区开设分行，以确保他们的客户获得高度接触的体验，并将其视为一流品牌。只有当银行在市场上表现出稳定的实体存在并根据人口群体为其客户提供最新的高科技服务时，才能确保这一点。本研究的目的是检查印度商业银行在四个人群中的存活率，以及它们在所有人群中存活率的差异。

设计/方法/方法

该分析基于 2006 年 3 月至 2019 年 12 月按四个人口组划分的印度商业银行运营办事处数量的季度数据。使用 Kaplan-Meier 估计器估计存活率。

发现

从分析中可以看出，银行的生存情况会随着人口群体的变化而变化。除此之外，还发现银行每个类别的生存时间在每个人群中都有所不同。

研究限制/影响

本研究仅关注印度的商业银行；可以对其他类别的印度银行进行类似的研究。此外，如果包括并研究银行规模、银行风险等变量，结果也会有所不同。此外，这项研究是使用 Kaplan-Meier 估计量完成的，即事件发生时间。此外，可以在使用 Cox 回归模型考虑银行的财务参数后进行预先研究，该模型探索各种预测变量与事件发生时间之间的关系。

社会影响

由于社会偏好的变化，银行也应采取不同的策略来确保其产品被客户理解和接受。这最终将提高银行的生存率。

原创性/价值

这项研究中所做的工作是全新的。