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Abstract

Employee turnover presents an ongoing challenge in the financial and banking sector, threatening organizational stability and operational efficiency. Turnover intention, widely recognized as a precursor to actual resignation, has attracted increasing academic interest. However, systematic reviews focusing specifically on this sector remain scarce. This study addresses the gap by systematically reviewing empirical literature to identify theoretical frameworks, institutional contexts, and key antecedents associated with turnover intention in financial and banking institutions. Guided by PRISMA protocols, a systematic literature review was conducted using Scopus and Web of Science databases. The review included identification, screening, and eligibility assessments of studies published between 2019 and 2024, resulting in 93 articles that met the inclusion criteria. Findings show that 38 theoretical frameworks were employed, with Social Exchange Theory being the most dominant. Commercial banks were the most commonly studied institutions, while Pakistan, India, and Indonesia dominated as research settings. Turnover intention was driven by five major categories of antecedents: personal characteristics, organizational factors, job-related conditions, supervisory influences, and coworker dynamics. While compensation remains an important consideration, non-monetary factors such as leadership quality, organizational justice, job stress, and peer relations emerged as equally critical. The review also reveals a fragmented use of theory and a concentration of research in South Asia, suggesting a need for more integrative theoretical approaches and broader geographic coverage. This study provides a consolidated understanding of turnover intention in the financial and banking sector and offers practical insights for developing more effective employee retention strategies.

Keywords

turnover intention financial and banking sector systematic review PRISMA workplace antecedents

Introduction

Turnover among employees is a constant challenge faced by many organizations in retaining their workforce. Particularly in the financial and banking sector where employee’s turnover is a prevalent issue (Ab Kadir et al., 2022; Martins et al., 2023; Rasheed et al., 2024). Employee turnover in the banking sector adversely affects productivity and performance of banking branches as well as to the whole organization (Hale et al., 2016; M. S. Islam et al., 2023). Wahana et al. (2024) and Kasa et al. (2023) emphasized that the financial and banking sector observed a higher turnover rate than other sectors. The high rate of employee turnover causes banks to spend more to find and train new people and lose experienced personnel (Falahat et al., 2019). For these reasons, employee’s continuous departure impacts the stability of the organization. Additionally, M. S. Islam et al. (2023) points out that employees who leave to join competitors can harm the organization. Previous studies have conceptualized and defined employee turnover in various ways. Hom et al. (2017)define turnover as the voluntary termination of the employee-employer relationship by employees leaving the organization. Employees’ turnover can also be described as a job movement where an employee leaves their position and completely exits the organization for another opportunity (Roche et al., 2015) or move internally within the same organization (Halter et al., 2017). According to Mobley (1977) turnover is a muti-faceted process of disengagement. Employees who decide to depart either from their job, career and organization will feel disconnected, uninterested, or unmotivated, leading to reduced involvement and productivity at work. Mobley (1977) further explained that this process entails psychological stages that include job evaluation, experiencing dissatisfaction, contemplating departure, assessing potential alternatives while considering benefits and costs, intending to explore options, actively seeking alternatives, evaluating available choices, comparing them with the current position, reinforcing the intent to leave, and ultimately departing. The multifaceted conceptualization of turnover accentuates the intricacy of employees’ experiences during the employment termination process.

Turnover does not happen abruptly; rather it requires that employees to develop the intention to quit as a prerequisite step of the quitting plan. Existing literatures indicate that turnover intention serves as a proxy or antecedent of actual quitting actions (Bui et al., 2024; Chang et al., 2013; Cohen et al., 2016; Tahir et al., 2024). The intention to quit signifies an important phase in severance of employment relationship between employees and employer of which initiated by employees. Employees contemplating departure frequently exhibit persistent thoughts of resignation and engage in withdrawal behaviours (Mubashar & Harzer, 2023), consequently, affecting the sustainability of financial and banking sector performance (Haider et al., 2019). The intention to quit influences the likelihood that an employee will depart from an organization (Salama et al. 2022; Tian-Foreman, 2009). In this study, the concept of intention to quit refers to the employee’s desire and thinking about leaving the organization, which is often the first step in the exit transition process. This intention is an early indicator of the actual action to quit, which can affect the continuity of organizational performance, particularly in the financial and banking sectors.

Financial and banking sectors comprises of commercial banks, Islamic banks, financial institutions which includes insurance companies, and investment firms. It plays an important role in supporting the financial stability and economic growth of a country (Alexiou et al., 2018; Batayneh et al., 2021; Shadab, 2021). As the financial and banking sector is growing increasingly competitive, the nature of the work environment is becoming substantially demanding (Kasa et al., 2023). Employees are often given high performance targets, which requires them to cope with heavy workloads (M. S. Islam et al., 2023; M. T. Islam et al., 2021; Kasa et al., 2023). This causes them to have to work beyond normal hours and face constant pressure to achieve the set targets. Occupational stress due to high job demands leave employees feeling overwhelmed and heightened their propensity to quit (M. T. Islam et al., 2021; Wahana et al., 2024).

The increasing number of studies on intention to quit shows the importance of this issue, thus a comprehensive literature review is necessary to identify key findings and research gaps. Prior reviews have examined turnover intention across various occupational and industrial contexts. Research in the hospitality and tourism sector has focused on frontline employees (Nguyen et al., 2023), while studies in healthcare have investigated factors influencing turnover intention among pharmacists (Thin et al., 2022) and nurses (Hayes et al., 2006). Additionally, turnover intention in India’s service industry has been analyzed, particularly in relation to HR practices (Guchait & Cho, 2010). In the broader domain of management, scholars have conducted comprehensive reviews on employees’ turnover intention (Chiat & Panatik, 2019). Although these studies collectively contribute to a nuanced understanding of the determinants and implications of turnover intention across different industries and diverse professional settings, none of these review articles focused on turnover intention within the financial and banking sectors. There are still gaps that need to be explored to understand the factors of quit intention in the context of the financial and banking sector. A systematic literature review is necessary to gain deeper insights and inform future research on turnover intention in the financial and banking sectors. This study addresses this gap by examining research patterns and trends through an SLR, guided by the following research questions.

i. What theoretical frameworks commonly used in the study of turnover intentions within the financial and banking sector?

ii. Which types of financial and banking sectors most frequently studied in research on employees’ turnover intentions?

iii. What are the key antecedents that contribute to employees’ turnover intentions in the financial and banking sector?

The SLR method used in this study will be detailed in the next section. Our findings from this literature review is also presented which includes: (1) the theories used in the study of turnover intentions in the financial and banking sector; (2) the context of the study examining the turnover intentions of employees in the financial and banking sector; and (3) antecedents related to employees’ turnover intentions. This study also proposed a research agenda as a guide for future studies and practical recommendations for financial and banking organizations.

Methodology

The PRISMA method was used as a guide in the systematic review of this study, while Scopus and Web of Science databases were used for information searches involving the process of identifying relevant articles and screening.

PRISMA

PRISMA provides a structured approach for conducting systematic literature reviews. PRISMA consist of four stages which includes (1) identification, (2) screening, (3) eligibility, and (4) inclusion (Moher et al. 2009; Page et al., 2021). These steps help evaluate relevant studies in a thorough and transparent way. To facilitate in the article retrieving process, screening and to identify duplicates articles, authors adapted an improved and easy to understand flow diagram proposed by Shaffril et al. (2019) (refer Figure 1). Shaffril et al. (2019) enhanced the previous flowchart developed by Moher et al. (2009).

Figure 1.

The flow diagram of the study.

Resources

Authors used Scopus and Web of Science (WoS) as the two main databases in this review. WoS developed by Clarivate Analytics provides various indexes such as Science Citation Index, Social Sciences Citation Index, and Arts & Humanities Citation Index with access to more than 33,000 journals and 1.7 billion references. WoS covers over 256 disciplines, including environmental studies, interdisciplinary social sciences, social issues, and development planning. Scopus, managed by Elsevier, is a multidisciplinary database containing more than 75 million records from more than 25,000 peer-reviewed journals, conference proceedings, and patents spanning the fields of science, technology, medicine, social sciences, arts, and humanities. Both databases select high-quality journals through strict selection criteria, making them the primary choice in ensuring the quality of the articles reviewed in this study.

Systematic Review Process

The review process involved three main stages: identification, screening, and eligibility, before selecting the articles to be included in the findings and discussion. Further details are provided below.

Identification

The systematic review process in the selection of relevant articles for this study comprised of three stages. The first stage is the determination of keywords, followed by the search for related and similar terms obtained through thesauruses, dictionaries, encyclopaedias, and previous studies. Next, a search string in the Scopus and Web of Science databases was developed in January 2025 (refer to Table 1). This study successfully obtained 250 articles from the Scopus database and 256 articles from the Web of Science (WOS) database.

Table 1.

The Search String Used for the Systematic Review Process.

Database	Search string
Scopus	TITLE-ABS-KEY ( ( “turnover intention” OR “intent to leave” OR “intent-to-leave” OR “intent to quit” OR “quit intent” OR “leave intent” OR “intent to leave” OR “resign* intent” OR “intent to resign” OR “intent to resign” OR “employee* withdrawal intention” OR “organization* turnover intent” OR “job turnover intent” OR “occupation* turnover intent” OR “career withdrawal intention” OR “voluntary turnover intent” OR “career exit intention” OR “job exit intent” OR “organization exit intent” OR “intent to exit” OR “withdrawal attitude” OR “turnover behave” ) AND ( “financial sector” OR “financial institution” OR “financial service” OR “bank” OR “banking” OR “bank*” ) )
WoS	TS=( ( “turnover intention” OR “intent to leave” OR “intent-to-leave” OR “intent to quit” OR “quit intent” OR “leave intent” OR “intent to leave” OR “resign* intent” OR “intent to resign” OR “intent to resign” OR “employee* withdrawal intention” OR “organization* turnover intent” OR “job turnover intent” OR “occupation* turnover intent” OR “career withdrawal intention” OR “voluntary turnover intent” OR “career exit intention” OR “job exit intent” OR “organization exit intent” OR “intent to exit” OR “withdrawal attitude” OR “turnover ehave” ) AND ( “financial sector” OR “financial institution” OR “financial service” OR “bank” OR “banking” OR “bank*” ) )

Database

Search string

Scopus

TITLE-ABS-KEY ( ( “turnover intention*” OR “intent to leave” OR “intent-to-leave” OR “intent to quit” OR “quit intent*” OR “leave intent*” OR “intent* to leave” OR “resign* intent*” OR “intent to resign” OR “intent* to resign” OR “employee* withdrawal intention” OR “organization* turnover intent*” OR “job turnover intent*” OR “occupation* turnover intent*” OR “career withdrawal intention” OR “voluntary turnover intent*” OR “career exit intention” OR “job exit intent*” OR “organization* exit intent*” OR “intent* to exit” OR “withdrawal attitude*” OR “turnover behave*” ) AND ( “financial sector” OR “financial institution*” OR “financial service*” OR “bank” OR “banking” OR “bank*” ) )

WoS

TS=( ( “turnover intention*” OR “intent to leave” OR “intent-to-leave” OR “intent to quit” OR “quit intent*” OR “leave intent*” OR “intent* to leave” OR “resign* intent*” OR “intent to resign” OR “intent* to resign” OR “employee* withdrawal intention” OR “organization* turnover intent*” OR “job turnover intent*” OR “occupation* turnover intent*” OR “career withdrawal intention” OR “voluntary turnover intent*” OR “career exit intention” OR “job exit intent*” OR “organization* exit intent*” OR “intent* to exit” OR “withdrawal attitude*” OR “turnover ehave*” ) AND ( “financial sector” OR “financial institution*” OR “financial service*” OR “bank” OR “banking” OR “bank*” ) )

Screening

The article screening process filters studies based on predefined criteria, ensuring the selection of relevant sources for a systematic literature review. Only journal articles with empirical data are included, while review papers, books, book chapters, notes, and conference proceedings are excluded as they are not primary sources. The review covers articles published between 2019 and December 2024. To maintain consistency, only English-language publications are considered, preventing translation challenges. After screening 506 documents, 250 articles were selected for analysis (see Table 2 and Figure 1). This approach ensures a focused and reliable dataset for the study. Two independent reviewers screened the articles at each stage, with discrepancies resolved through consensus. Although inter-rater reliability metrics were not calculated, the process ensured consistency in inclusion decisions.

Table 2.

The Inclusion and Exclusion Criteria.

Criterion	Inclusion	Exclusion
Literature type	Journal (research articles)	Review article, book series, book, chapter in book, conference proceeding
Language	English	Non-English
Timeline	Between 2019 and December 2024	2018 and earlier

Eligibility (Manual Screening)

The author carefully screened each article’s title, abstract, and main content to ensure alignment with the inclusion criteria. Duplicate records were removed, eliminating 75 articles. The remaining 181 articles underwent further eligibility assessment. At this stage, 87 articles were excluded because they did not focus on turnover intention, addressed the incorrect type of turnover, were inaccessible, had been retracted, did not focus on the financial or banking sector, and were not empirical studies. Finally, after this thorough filtering, 93 articles met all criteria and were included in the systematic review.

Data Extraction and Analysis

The authors systematically reviewed 93 selected articles, focusing on abstracts, discussions, and findings. Data extraction followed research questions, compiling relevant information into a structured table. The synthesis process began with coding key article details, including author, journal, title, year, and study context, using Microsoft Excel. Additional coding incorporated study design, methods, theoretical frameworks, and factors influencing turnover intentions. The findings were synthesized to identify theoretical perspectives, research contexts, research measurement and tools as well as key themes related to turnover intention antecedents.

Findings and Discussion

Based on the findings of the final articles, the results were categorized into several aspects, including the theories used, the context of the financial and banking sectors, and the antecedents of turnover intention

Theories Used to Explain Turnover Intention in Financial and Banking Sector

The authors have identified 38 theories applied in studies on employee turnover intention in the financial and banking sector. Among these, Social Exchange Theory emerged as the most widely used, forming the basis of 24 empirical studies. Developed by Homans (1958), Blau (1964), and Emerson (1976), this theory highlights how relationships are shaped by rewards, costs, and mutual obligations. When employers uphold their commitments, employees are more likely to reciprocate with loyalty. However, unmet psychological contracts (Azeem et al., 2020; Bari et al., 2022) can increase turnover intention, prompting employees to seek better opportunities. This theory has been used to explain turnover intention influenced by ethical leadership (Saleh et al., 2022; Seth et al., 2022; Suifan et al., 2020); compensation and career growth (Devi et al., 2022; Saritha & Sunitha, 2022); organizational, supervisor and coworker supports (Chowdhury et al., 2022; Khan et al., 2020; Saritha & Sunitha, 2022); as well as abusive supervision (Afshan et al., 2022; Ahmad & Begum, 2023). These organizational factors significantly impact employees’ decisions to stay or leave.

The next most common theories used in the literature were Conservation of Resources Theory, Social Identity Theory and Job Demands-Resources Theory. According to Conservation of Resources Theory (Hobfoll et al., 2018), employees use various resources for completing job tasks, such as time, cognitive focus, and physical energy. However, individuals must replenish those resources to avoid stress (Hobfoll, 2001). Awan et al. (2021) found that role conflict depletes these resources, increasing turnover intentions. As an occupational stressor, role conflict drains mental energy and time, leading to dissatisfaction. Without recovery through support or rest, prolonged stress may push employees to consider leaving as a way to preserve their well-being.

Tajfel and Turner (2004) Social Identity Theory explains that individuals shape their identity by associating with groups, such as family or colleagues, influencing their self-view and social interactions. By distinguishing between in-groups and out-groups, people tend to favour their own group, reinforcing a positive self-concept. This theory helps examine how corporate social responsibility (CSR) affects workplace outcomes, including turnover intention (Alnehabi & Al-Mekhlafi, 2023; Shaikh et al., 2022). Employees who identify with their organization’s CSR efforts often feel a stronger connection to their workplace and are less likely to leave.

The JD-R model suggests that job stress arises from three key factors: job demands, job resources, and personal resources. Job demands require physical or mental effort, potentially leading to physiological or psychological strain (Bakker & Demerouti, 2014). According to Bakker and Demerouti (2014), job and personal resources help individuals achieve work goals, mitigate stress, and support personal development. Mubashar and Harzer (2023) applied the JD-R model to examine how signature strengths (personal resources) and perceived organizational support (job resources) enhance work engagement and reduce turnover intention.

Taken together, these findings suggest that while multiple theories have been applied to turnover research in financial services, their predictive strength is uneven. Social Exchange Theory demonstrates the most consistent explanatory power, particularly in contexts emphasizing relational obligations and perceived fairness. Conservation of Resources Theory and the Job Demands–Resources model add valuable perspectives on stress and resource depletion but are less frequently applied (refer Table 3). By contrast, Social Identity Theory offers supplementary insights, though it appears less central in explaining turnover in financial institutions where relational and contractual dynamics dominate. This suggests that future research should not only draw from a wide theoretical base but also evaluate the comparative predictive power of these frameworks to establish which offer the most robust explanations in financial services.

Table 3.

Theories Used in Turnover Intention Research Within the Financial and Banking Sector.

Theories	Number of articles	Researchers that used these theories
Social Exchange Theory	24	Afshan et al. (2022); Alqubati et al. (2019); Aslam et al. (2024); Azeem et al. (2020); Bari et al. (2022); Chowdhury et al. (2022); Devi et al. (2022); Ekmekcioglu and Aydogan (2019); Gautam and Gautam (2024); Haider et al. (2019); Kasa et al. (2023); Khan et al. (2020); Mensah (2019); Naeem and Khurram (2020); Nketsiah and Nkansah (2024); Piasecki (2020); Piasecki (2024); Saleh et al. (2022); Salleh et al. (2020); Saritha and Sunitha (2022); Seth et al. (2022); Suifan et al. (2020); Yasin et al. (2023); Zeeshan et al. (2021)
Conservation of Resources Theory	10	Ahmad and Begum (2023); Baheer et al. (2023); Martins et al. (2023); Awan et al. (2021); Kerse et al. (2022); Zeeshan et al. (2021); Farasat et al. (2021); Kopperud et al. (2020); Haider et al. (2020); Huang and Lin (2019)
Social Identity Theory	9	Alnehabi and Al-Mekhlafi (2023); Bayraktaroglu et al. (2023); Ekmekcioglu and Aydogan (2019); Haider et al. (2019); Huang and Lin (2019); Mahmood et al. (2020); Shaikh et al. (2022); Yasin (2021)
Job Demands-Resources Theory	7	Rasheed et al. (2024); Mubashar and Harzer (2023); M. S. Islam et al. (2023); Saritha and Sunitha (2022); Van Heerden et al. (2022); Van der Merwe et al. (2020); Vermooten et al. (2019)
Corporate Social Responsibility Theory	3	Sobhani et al. (2021); Yasin (2021); Yasin et al. (2021)
Theory of Planned Behaviour	2	Dahri et al. (2023); Haider and de Pablos-Heredero (2024)
Human Capital Theory	2	Piasecki (2020); Piasecki (2024)
Herzberg’s Two-Factor Theory of Motivation	2	Saritha and Sunitha (2022); Qureshi et al. (2024)
Organizational Equilibrium Theory	2	Saritha and Sunitha (2022); Tutar and Erdem (2021)
Social Learning Theory	2	Akuffo and Kivipõld (2021); Seth et al. (2022)
Social Cognitive Theory	1	Huang and Lin (2019)
Social Cognitive Career Theory	1	Lathabhavan (2020)
Social Comparison Theory	1	Piasecki (2020)
Self-concept theory	1	Suifan et al. (2020)
Self-determination Theory	1	Mustafa and Ali (2019)
Theory of Work Adjustment	1	Saritha and Sunitha (2022)
Person-environment fit Theory	1	Saritha and Sunitha (2022)
Goal-setting Theory	1	Qureshi et al. (2024)
McGregor’s Theory Y	1	Qureshi et al. (2024)
Behavioural Agency Model	1	Z. Ali and Mehreen (2019)
Agency Theory	1	Z. Ali and Mehreen (2019)
Acculturation theory	1	Hommey et al. (2020)
Job Demand-Control-Support Model	1	Saritha and Sunitha (2022)
Spiral of Silence Theory	1	Tutar and Erdem (2021)
Affective Events Theory	1	S. A. Ali et al. (2022)
Job Embeddedness Theory	1	Haider et al. (2019)
The Unfolding Theory of Turnover	1	Ahmad and Begum (2023)
Organizational justice theory	1	Alyahya et al. (2024)
Psychological Contract Theory	1	Lee et al. (2022)
Organizational CSR Climates Theory	1	Sobhani et al. (2021)
Perceived Organizational Politics Theory	1	Bhattarai (2021)
Psychological Contract Theory	1	Syed et al. (2021)
Stimulus-Organism-Response Theory	1	To and Yu (2024)
Regulatory Focus Theory	1	Hamstra et al. (2023)
Resource Based View Theory	1	Alimuddin et al. (2023)
Three-component model of organizational commitment	1	Serhan et al. (2022)
Referent Cognitions Theory of Relative Deprivation	1	Gharbi et al. (2022)
Uncertainty Management Theory	1	Caemmerer et al. (2021)

Table 3 outlines the theoretical frameworks employed by researchers in this study.

Context for Investigating Employee’s Turnover Intention in the Financial and Banking Sector

Turnover intention within the financial and banking sectors has been evaluated in a diverse type of financial and banking sector (refer Table 4). The top countries in which these empirical studies took place were Pakistan (n = 27), followed by India (n = 10), Indonesia (n = 9), Africa (n = 8), and a two-way tie among Malaysia (n = 6) and Arab countries (n = 6). The analysis also revealed that most investigations were conducted in commercial banks (n = 29), followed by private banks (n = 15), Islamic or syariah banks (n = 10), public banks (n = 7), state-owned (n = 3), insurance (n = 3), foreign or international banks (n = 2), co-operative banks (n = 2) and investment bank (n = 1).

Table 4.

Types of Financial and Banking Sector That Have Been Analyzed in Turnover Intention Research.

References	CB	I/SB	Pr	Pb	S-O	F/IB	Co-op	Ins	Inv	Micro
To and Yu (2024)	√
Gautam and Gautam (2024)	√
Haider and de Pablos-Heredero (2024)	√
Maharani and Tamara (2024)	√							√
M. S. Islam et al. (2023)	√
Afshan et al. (2022)	√
Lee et al. (2022)	√
Chowdhury et al. (2022)	√		√
Shaikh et al. (2022)	√
Bari et al. (2022)	√
Saleh et al. (2022)	√	√
Yasin et al. (2021)	√
Sobhani et al. (2021)	√
Bhattarai (2021)	√
Syed et al. (2021)	√		√
Yasin (2021)	√
Khan et al. (2020)	√
Azeem et al. (2020)	√
Salleh et al. (2020)	√	√				√
Mahmood et al. (2020)	√
Giao et al. (2020)	√
Naeem and Khurram (2020)	√		√	√
Haider et al. (2020)	√		√
Mazhar et al. (2020)	√
Mensah (2019)	√
Mainardes et al. (2019)	√
Z. Ali and Mehreen (2019)	√
Kurniawaty et al. (2019)	√
Haider et al. (2019)	√
Aslam et al. (2024)		√
Husniati et al. (2024)		√
Bayraktaroglu et al. (2023)		√
Santoso et al. (2023)		√
Serhan et al. (2022)		√
Prilyana and Aseanty (2020)		√
Zahari et al. (2020)		√
Janon et al. (2019)		√
Zanabazar et al. (2024)			√
Yadav and Srivastava (2024)			√
Zeeshan et al. (2021)			√
Awan et al. (2021)			√
Singh and Randhawa (2021)			√
Akuffo and Kivipõld (2021)			√	√
Farasat et al. (2021)			√	√
Tutar and Erdem (2021)			√	√
Hommey et al. (2020)			√					√
Shafqat and Mushtaq (2020)			√	√
Lathabhavan (2019)			√	√		√
Mustafa and Ali (2019)				√
Dahri et al. (2023)					√
Nketsiah and Nkansah (2024)					√
Hamstra et al. (2023)					√
Piasecki (2024)							√
Piasecki (2020)							√
Bilginoglu and Yozgat (2022)								√	√
Saritha and Sunitha (2022)										√
Total	29	10	15	7	3	2	2	3	1	1

Note. CB = commercial banks; I/SB = Islamic/Syariah banks; Pr = private banks; Pb = public banks; S-O = state-owned; F/IB = foreign/international banks; Co-op = co-operative; Ins = insurance; Inv = investment; Micro = microfinance.

Turnover intention research has been conducted across different type of financial institution. Studies suggest that Islamic banks report lower turnover rates (Milhem et al., 2024), compared to commercial and private banks as employees in Islamic financial institutions are more influenced by organizational ethics and work values (Caniago & Mustoko, 2020). Conversely, commercial banks, known for high-pressure work environments, tend to experience greater voluntary turnover due to stress-related burnout (M. S. Islam et al., 2023; M. T. Islam et al., 2021). These findings emphasize the need for context-specific HR strategies that consider regulatory conditions, organizational structures, and cultural influences in mitigating employee turnover.

Antecedents of Turnover Intention Financial and Banking Sector

In the context of turnover intention, antecedents are the factors or conditions that precede and influence an employee’s decision to consider leaving an organization. They represent the underlying causes that shape how turnover intentions develop (Chang et al., 2013). In this study, antecedents were identified across five dimensions: personal, organizational, job-related, supervisor-related, and coworker factors (see Figure 2). While earlier studies have often grouped antecedents into three broader categories (personal, team and organizational-level factors) (Han, 2022; Saritha & Sunitha, 2022), this study differentiates them into five distinct dimensions. This finer classification highlights the specific roles of supervisors and coworkers, which are frequently subsumed under broader “job” or “organizational” categories. By presenting them separately, the analysis offers a more detailed understanding of the multiple, interconnected pathways that lead to turnover intention. These five dimensions did not emerge in a fixed sequence but appeared in parallel as distinct yet interconnected influences on turnover intention. Rather than a linear hierarchy, they coexist and collectively shape employees’ decisions about staying or leaving. In line with prior evidence, inconsistencies in the impact of antecedents such as the mixed role of compensation were also observed. Furthermore, much of the existing literature relies on cross-sectional designs, which limits causal inference (Figueiredo et al., 2025). Although antecedents may vary across industries, job levels, and cultural settings, this study focuses only on assessing the direct influence of the five dimensions, without exploring such contextual variations. Further explanations for each cluster of antecedents are provided in detail in the next section

Figure 2.

Antecedents of turnover intention financial and banking sector.

Organization Antecedents

Saritha and Sunitha (2022) derived and combine organization antecedents’ definition as factors encompassing employees’ perceptions of monetary and non-monetary benefits, the value and care shown by employers for their contributions and well-being, and the favourable treatment they experience from the organization. This study identified organizational antecedents as the most frequently highlighted in the literature, with 34 factors being noted. Among these, compensation or rewards received the greatest emphasis (Alimuddin et al., 2023; Falahat et al., 2019; M. S. Islam et al., 2023; Mainardes et al., 2019; Mazhar et al., 2020; Santoso et al., 2023; Saritha & Sunitha, 2022; Yadav & Srivastava, 2024), followed by dimensions of organizational justice (Alyahya et al., 2024; Ekmekcioglu & Aydogan, 2019; Gharbi et al., 2022; Lee et al., 2022), organizational commitment (Alqubati et al., 2019; Bayraktaroglu et al., 2023; Nketsiah & Nkansah, 2024; Serhan et al., 2022), and training (M. S. Islam et al., 2023; Kasa et al., 2023; Mazhar et al., 2020; Prilyana & Aseanty, 2020).

Drawing from the reviewed studies, organizational antecedents can be grouped into six clusters. HRM practices (e.g. compensation, promotion, appraisal, succession planning, training) reflect the organization’s investment in employee growth. Organizational climate and culture (e.g. autonomy support, workplace climate, incivility, cultural differences) shape employees’ daily experiences and sense of belonging. Organizational justice and fairness (e.g. interactional and procedural justice, trust, perceptions of politics) influence how employees judge fairness and loyalty. Commitment and retention factors (e.g. cost of quitting, employer branding, organizational commitment) capture how employees balance attachment to the organization against external opportunities. These factors reflect how employees weigh their attachment to the organization against opportunities elsewhere. Corporate image and social responsibility (e.g. diversity, wellness programs, responsible HRM) shape organizational reputation and value alignment. Lastly, external and strategic pressures (e.g. after-service plans, competitive intensity) highlight broader environmental forces affecting turnover decisions.

It is worth noting that within these clusters, some antecedents produced contradictory findings regarding their significance. For example, performance appraisal was reported as both significant and non-significant in relation to turnover intention (Kasa et al., 2023; Mazhar et al., 2020; Qureshi et al., 2024), while similar inconsistencies were observed for pay or salary satisfaction (Falahat et al., 2019; Kasa et al., 2023; Saritha & Sunitha, 2022; Van der Merwe et al., 2020). This suggests that even when salaries are increased, turnover rates may remain high, highlighting the importance of examining a broader set of antecedents (Falahat et al., 2019).

Job-Related Antecedents

Saritha and Sunitha (2022) defined job-related factors as “perceived job characteristics, roles, and stressors that cause turnover” (p. 168). The term “job-related” is often used interchangeably with “work-related factors.” Previous literature has frequently cited key factors such as work-life balance (Husniati et al., 2024; Maharani & Tamara, 2024; Yusnita & Gursida 2022; Zahari et al., 2020), job or task resources (M. S. Islam et al., 2023; Mubashar & Harzer, 2023; Van Heerden et al., 2022; Van der Merwe et al., 2020), work-family conflict or interference (Aboobaker & Edward, 2020; Khan et al., 2020; Syed et al., 2021), and job satisfaction (Alqubati et al., 2019; Devi et al., 2022; Zanabazar et al., 2024). Studies on work-life balance and job resources have shown these factors negatively influence turnover intentions. Organizations must recognize the critical importance of maintaining a work-life balance, particularly for younger employees, where balancing work demands and personal life is increasingly significant (Husniati et al., 2024).

Job-related antecedents can be grouped into four clusters. The first cluster, job conditions and structural factors, includes job autonomy, job crafting, job embeddedness, job enrichment, work environment, and work values. Empirical evidence shows that factors such as job autonomy (Kasa et al., 2023), job embeddedness (Husniati et al., 2024), and work values (Yusnita & Gursida, 2022) contribute positively to employee retention by fostering stronger workplace attachment. The second cluster, Job demands and stressors, reflects pressures such as work overload, occupational stress, social overload, workplace ostracism, harassment, and envy. Studies highlight that work pressure (Saritha & Sunitha, 2022), job stress (Falahat et al., 2019), workplace envy (Dahri et al., 2023), and work overload (S. A. Ali et al., 2022) increase employees’ likelihood of leaving.

The third cluster, job attitudes and perceptions, encompasses empowerment, job satisfaction, and information sharing. Job satisfaction has been consistently identified as a critical determinant of turnover intention (Alqubati et al., 2019; Devi et al., 2022; Zanabazar et al., 2024). Finally, the fourth cluster, work-family interface, addresses work-family conflict, enrichment, and balance. While work-family conflict has been linked to higher turnover intentions (Aboobaker & Edward, 2020; Khan et al., 2020; Syed et al., 2021), positive factors such as enrichment and balance play an important role in reducing attrition risks. Overall, these findings highlight that job-related antecedents are multidimensional, spanning structural conditions, demands, perceptions, and family–work interactions. Addressing these issues through supportive job design, stress management, and work-life initiatives is essential for organizations seeking to reduce turnover and foster a stable workforce.

Personal/Individual Antecedents

The construct of personal antecedents is referred as the assets that enable employee manage job demands, accomplish their work objectives, and promote learning, growth, and development, ultimately contributing to their overall effectiveness (Van der Merwe et al., 2020) While Schaufeli and Taris (2014) define personal resources as “psychological characteristics or aspects of the self that are commonly associated with resiliency and that refer to the ability to control and impact one’s environment successfully” (p. 49). Together, these definitions imply that personal or individual antecedents have significant potential to influence employees’ decisions to resign. In total, 21 personal antecedents were identified in the reviewed studies (see Figure 2).

These antecedents can be grouped into five clusters. The first, personal traits and dispositions, includes characteristics such as proactive personality, compassion, power distance, and dark triad traits (i.e. Machiavellianism, narcissism, psychopathy), which shape individual differences in turnover tendencies. The second cluster, psychological resources and capital, encompasses emotional intelligence, psychological ownership, rewards, capital, and self-efficacy. Emotional intelligence (Giao et al., 2020; Saritha & Sunitha, 2022; Van der Merwe et al., 2020; Zeidan, 2020) and psychological ownership (Zeeshan et al., 2021) have been among the most widely studied factors, consistently linked to turnover outcomes.

The third cluster, career experience and perceptions, covers factors such as prior experience, gender, the glass ceiling effect, perceived overqualification, and peripheral employee segment membership. Notably, the “glass ceiling” remains a barrier to women’s career advancement (Lathabhavan, 2019, 2020), while gender dynamics more broadly continue to influence turnover intentions (Alqubati et al., 2019). The fourth cluster, work attitudes and engagement, includes employee engagement, stress, and time wasted on non-core activities, highlighting the attitudinal dimension of turnover.

The fifth cluster, psychological contracts, refers to perceptions of contract breach, violation, or fulfilment. When employees perceive contract fulfilment where promises and expectations are met, their turnover intentions are reduced (Shafqat & Mushtaq, 2020). In contrast, breaches or violations where employees perceive a gap between organizational promises and practices lead to diminished trust, lower satisfaction, and higher intentions to resign (Azeem et al., 2020; Bari et al., 2022). Overall, personal antecedents illustrate that turnover intention is not only shaped by organizational or job-related factors but also by employees’ individual traits, psychological resources, career experiences, and perceptions of fairness in employment relationships.

Supervisor Antecedents

Another crucial dimension of antecedents is supervisor antecedents, which refer to factors related to supervisors or managers that influence employee attitudes, behaviours, and outcomes in the workplace. These antecedents typically encompass the actions, qualities, and interactions of supervisors that shape employees’ experiences and decisions, including their turnover intentions. Supervisor antecedents can be grouped into three main clusters. The first cluster, leadership styles, reflects positive approaches such as authentic, ethical, inclusive, and responsible leadership. Studies consistently highlight the importance of leadership behaviours, with effective leadership styles linked to lower turnover intentions (Akuffo & Kivipõld, 2021; Alimuddin et al., 2023; Aslam et al., 2024; Saleh et al., 2022; Saqib et al., 2024; Seth et al., 2022; Suifan et al., 2020; Tshwane et al., 2023; Yasin et al., 2021, 2023; Yadav & Srivastava, 2024).

The second cluster, destructive leadership, includes supervisor undermining, abusive supervision, toxic leadership, and positional favouritism. Such negative behaviours have been widely documented as harmful to employees’ well-being and commitment. For example, undermining and abusive supervision are strongly associated with higher turnover intentions (Afshan et al., 2022; Ahmad & Begum, 2023; Mahmood et al., 2020), while toxic leadership (Naeem & Khurram, 2020) and favouritism (Akuffo & Kivipõld, 2021) erode trust and fairness perceptions in the workplace.The third cluster, perceptions of the supervisor–employee relationship, captures employees’ views of supervisory support, person–supervisor fit, and managerial decisiveness. Supervisory support has been shown to reduce turnover intention by providing employees with guidance and care (Chowdhury et al., 2022; Khan et al., 2020; Saritha & Sunitha, 2022; Van der Merwe et al., 2020). Similarly, person–supervisor fit enhances alignment between employees and their immediate managers (Kerse et al., 2022), whereas perceptions of managerial indecisiveness may weaken trust and push employees toward resignation.

Overall, supervisor antecedents are particularly influential because supervisors act as the immediate authority figures who directly affect employees’ daily experiences, appraisals, and career progression. Positive supervisory practices can foster commitment and retention, while destructive or unsupportive behaviours heighten the risk of turnover.

Coworker Antecedents

Although coworker antecedents have been the least discussed in the literature, with only seven dimensions identified, they should not be overlooked. A positive work environment that helps retain talent is significantly influenced by how employees are treated by their coworkers. Specifically, difficult coworkers those who exhibit negative and problematic work-related or interpersonal behaviours can trigger negative attitudes among their peers, which, in turn, may increase turnover intentions (To & Yu, 2024).

Coworker antecedents in this study can be clustered into three groups. The first, peer relationship, includes peer-to-peer interactions and social acceptance. Strong peer bonds and social integration are associated with higher career commitment and lower turnover (Alqubati et al., 2019; Hommey et al., 2020). The second, coworker support and coordination, involves perceived coworker support and relational coordination, which facilitate knowledge sharing and cooperative problem-solving (Chowdhury et al., 2022; Haider et al., 2019). The third, role dynamics within teams, highlights how role clarity reduces ambiguity and supports retention, while role conflict and difficult coworkers increase stress and intention to leave (Awan et al., 2021; Hommey et al., 2020; To & Yu, 2024).

Hommey et al. (2020), in their study on newcomers, found that social acceptance and role clarity were particularly critical in shaping early perceptions of the organization, thereby reducing turnover intentions. These findings extend to existing employees as well, where positive coworker relationships and support foster stronger career commitment and minimize the desire to quit.

Conclusion

This systematic review provides a comprehensive analysis of the factors driving turnover intentions in the financial and banking sector. While existing research has significantly contributed to understanding why employees leave, it remains fragmented, with many studies applying theoretical models in isolation rather than integrating them into a holistic framework. Social Exchange Theory (SET), Conservation of Resources (COR) Theory, and the Job Demands–Resources (JD-R) model have all been used to explain turnover behaviours, yet their combined influence remains underexplored. The dominance of SET highlights the importance of perceived fairness, reciprocity, and organizational support in influencing employee retention. However, this perspective alone does not fully explain why employees leave, as emotional exhaustion, stress, and identity-based motivations also play a critical role. Integrating COR and JD-R theories suggests that turnover is often linked to an employee’s ability to cope with workplace stressors and maintain psychological well-being. Rather than treating these theories as competing explanations, future studies should explore how they intersect to provide a more nuanced understanding of turnover behaviour.

One of the most striking findings of this review is the geographical concentration of research in South Asia, particularly Pakistan, India, and Indonesia. While these studies provide valuable insights, they do not fully capture turnover dynamics in regions with vastly different economic conditions, labour policies, and cultural norms. The lack of research in Latin America, Africa, and Eastern Europe presents a major gap in the literature, limiting the development of globally relevant retention strategies. Similarly, the over-reliance on cross-sectional survey methods weakens the ability to establish causality between antecedents and actual employee departures. Future research should therefore adopt longitudinal designs, qualitative approaches, and experimental methods to capture the lived experiences of employees and explore the deeper psychological and contextual factors influencing turnover.

An important dimension that emerges from this review is the underlying why behind the patterns observed in the turnover literature. The widespread use of frameworks such as Social Exchange Theory (SET), COR, and JD-R can be attributed to their conceptual alignment with the dominant stressors and relational dynamics in financial work environments. The transactional and hierarchical nature of financial institutions, where reward structures, perceived fairness, and supervisory support are central, makes SET particularly attractive to scholars. Similarly, the high-pressure, performance-driven culture in banking explains the frequent application of COR and JD-R theories, which emphasize emotional exhaustion and resource depletion. The geographical concentration of studies in South Asia may be influenced by a combination of factors: the region’s rapid economic growth, high employment volatility, and academic interest in labour instability have made turnover a salient issue. Additionally, research output in these countries may be facilitated by greater access to industry partnerships or graduate research funding on HRM issues. The methodological preference for cross-sectional surveys is likely driven by feasibility and access constraints, particularly in emerging economies where longitudinal tracking may be challenging. These explanations point to structural, cultural, and logistical forces that shape the current state of the literature, highlighting not only what is studied but also why it is studied in these particular ways. Acknowledging these underlying drivers enables a more reflective and context-sensitive understanding of the field, paving the way for more intentional and globally inclusive future research.

This review identifies five key categories of turnover antecedents: personal factors, job-related stressors, organizational characteristics, supervisory influences, and coworker dynamics. While compensation and salary remain important, with 12 studies emphasizing their role, they are far from the only drivers of turnover. Many employees leave due to toxic work environments, poor leadership, excessive workload, or limited career development opportunities. These findings challenge the outdated assumption that higher salaries alone can solve retention problems, emphasizing instead the importance of holistic workplace strategies.

Implications and Limitations of the Study

Theoretical Implications

The key theoretical implication of this review is the need to strengthen and expand efforts toward multi-theoretical integration. While a number of primary studies have already combined more than one theoretical lens, such integrations remain selective and fragmented, often applied without exploring the deeper complementarities among frameworks. Turnover intention is a multidimensional phenomenon that cannot be fully explained through a single perspective. For example, emotional exhaustion described by COR and JD-R theories frequently interacts with perceptions of fairness and reciprocity central to SET, while identity-based perspectives add further nuance by capturing employees’ alignment with organizational values (refer to Saleh et al., 2022; Saritha & Sunitha, 2022; Van der Merwe et al., 2020). Recognizing these overlaps allows scholars to move beyond partial integrations and develop more systematic approaches in which theories are treated not as competing explanations but as interconnected mechanisms that jointly shape turnover behaviour.

Practical Implications

The findings of this review suggest that effective retention strategies must extend beyond financial incentives and address broader organizational and HRM practices. First, organizations should cultivate positive workplace cultures by reducing toxic behaviours and fostering supportive peer relationships, as such environments enhance employee commitment and reduce voluntary turnover. Second, there is a clear need to invest in leadership development, ensuring that supervisors adopt leadership styles grounded in fairness, inclusivity, and support, given their central role in shaping employee experiences. Third, retention strategies should be tailored to the specific subsector of financial services, as turnover dynamics are not uniform across commercial, Islamic, investment, and emerging fintech institutions. Fourth, organizations should implement resilience and well-being initiatives, particularly those that address burnout, workload stress, and work–life balance, which are consistently identified as critical antecedents of turnover intention. Finally, the provision of clear and structured career development opportunities is essential for aligning employee expectations with organizational goals, thereby reducing dissatisfaction and enhancing long-term retention.

Limitation of the Study

As with any review, this study has limitations. First, the evidence base remains geographically concentrated in South Asia, with limited contributions from Latin America, Africa, and Eastern Europe, thereby restricting global generalisability. Although the search strings were not limited to any specific country, the results revealed that South Asia has produced more publications on this topic compared to other regions. Second, although more than 80% of the primary studies examined mediators and/or moderators of turnover intention, this review did not address those mechanisms. Instead, the scope was deliberately restricted to synthesizing the direct antecedents of turnover intention to maintain focus and clarity. As authors, we acknowledge that our search strings, inclusion/exclusion criteria, and coding framework shaped the synthesis and may reflect interpretive biases. We therefore encourage future reviews to adopt alternative search strategies, broader methodological inclusions, and comparative cross-regional perspectives. In addition, future researchers are encouraged to create a clear and integrated model that brings together the main theories and key factors found in this review, along with specific ideas or hypotheses that can be tested in future studies.

Another important limitation of this review is that it focused only on the financial and banking sector. While this allowed us to provide a detailed understanding of turnover intention in this specific industry, the study did not include a comparison with other sectors such as healthcare, hospitality, or retail. These industries also face high employee turnover and have been studied in many recent reviews. The decision to focus only on financial services was intentional, to ensure clarity and consistency in the analysis. However, this limited our ability to explore how the causes of turnover intention might be similar or different in other sectors. Future studies could conduct a comparative review that looks at multiple industries and examines how different types of workplace pressures, such as strict regulations in finance or emotional stress in healthcare, affect employees’ intentions to leave. This kind of research could provide a broader understanding of turnover and help organizations create better strategies to retain employees in different work environments.

Footnotes

Acknowledgements

The author has no acknowledgment.

ORCID iDs

Nurul’Ashykiin Mohd Fuzi

Nordahlia Umar Baki

Ethical Considerations

Final approval of the version to be published: Nurul’Ashykiin Mohd Fuzi, Nordahlia Umar Baki.

Author Contributions

Conception: Nurul’Ashykiin Mohd Fuzi.

Interpretation and analysis of data: Nurul’Ashykiin Mohd Fuzi and Nordahlia Umar Baki.

Drafting of Manuscript: Nurul’Ashykiin Mohd Fuzi.

Revision for important intellectual content: Nordahlia Umar Baki.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Understanding Turnover Intentions in the Financial Services Sector: A Systematic Review of the Quit Mindset

Abstract

Keywords

Introduction

Methodology

PRISMA

Resources

Systematic Review Process

Identification

Screening

Eligibility (Manual Screening)

Data Extraction and Analysis

Findings and Discussion

Theories Used to Explain Turnover Intention in Financial and Banking Sector

Context for Investigating Employee’s Turnover Intention in the Financial and Banking Sector

Antecedents of Turnover Intention Financial and Banking Sector

Organization Antecedents

Job-Related Antecedents

Personal/Individual Antecedents

Supervisor Antecedents

Coworker Antecedents

Conclusion

Implications and Limitations of the Study

Theoretical Implications

Practical Implications

Limitation of the Study

Footnotes

Acknowledgements

ORCID iDs

Ethical Considerations

Author Contributions

Funding

Declaration of Conflicting Interests

Data Availability Statement

References