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Systematic Review

Assessing Digital Transformation Strategies in Retail Banks: A Global Perspective

by
Bothaina Alsobai
and
Dalal Aassouli
*
College of Islamic Studies, Hamad bin Khalifa University, Doha P.O. Box 34110, Qatar
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2025, 18(12), 710; https://doi.org/10.3390/jrfm18120710
Submission received: 6 October 2025 / Revised: 15 November 2025 / Accepted: 24 November 2025 / Published: 12 December 2025
(This article belongs to the Section Banking and Finance)
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Abstract

This paper presents a PRISMA-guided systematic literature review (2015–2025) of 20 empirical studies on digital transformation in retail banking, examining how artificial intelligence (AI) strengthens cybersecurity, enables FinTech collaboration through interoperable APIs and open-banking infrastructures, and embeds data-driven decision-making across core functions. We searched major databases, applied predefined eligibility criteria, appraised study quality, and coded outcomes related to digital adoption, operational resilience, and customer experience. The synthesis indicates that AI-enabled controls and API-mediated partnerships are consistently associated with higher digital-maturity indicators, conditional on robust model-risk governance and prudent third-party/outsourcing management. Benefits span improved customer experience, efficiency, and inclusion; however, legacy systems, regulatory fragmentation, cyber threats, and organizational resistance remain binding constraints. We propose a unified framework linking technology choices, regulatory design, and organizational outcomes, and distill actionable guidance for policymakers (e.g., interoperable standards, proportional AI governance, sector-wide cyber resilience) and bank managers (sequencing AI use cases, risk controls, and partnership models). Future research should assess emerging technologies—including quantum-safe security and central bank digital currencies (CBDCs)—and their implications for digital-banking stability and trust.

1. Introduction

Due to digital advancements, retail banks faced a critical imperative to improve customer experience, operational efficiency, and adapt to rapidly changing market conditions (Adewumi et al., 2024). Therefore, traditional banks are leveraging digital technology to offer seamless, personalized, and convenient banking services as consumer demand increases (Agarwal, 2020; Faisal et al., 2024). Bank of America introduced an artificial intelligence (AI)-powered virtual assistant embedded in a mobile application that notifies users about bills, updates their credit score, and gives budgeting advice in real time, in a very simple, conversational language (Benali & Boumenkar, 2024; Eccles & Krzus, 2018). Moreover, Emirates in the UAE offers instant account opening, smart budgeting tools, and lifestyle-driven rewards, powered by AI and behavioral analytics, on a millennial-focused, digital-only banking platform launched under the name Liv (Al Nuaimi, 2019).
At the same time, Hongkong and Shanghai Banking Corporation (HSBC) has adopted biometric authentication, including voice and facial recognition, that allows customers not only to enjoy the conveniences of safe and secure account access and transactions with no passwords available, but also to maintain the security of their accounts (Pundareeka Vittala et al., 2024). However, recent studies have shown that digital transformation significantly improves customer satisfaction by offering online and mobile banking services, resulting in greater convenience and availability (Bankuoru Egala et al., 2021; S. J. Kaur et al., 2021; Zouari & Abdelhedi, 2021). The use of cutting-edge technologies such as artificial intelligence (AI), BDA, and cloud computing allows banks to simplify operations, cut costs, and mitigate risks, among other benefits (Alsemaid et al., 2024; D. J. Kaur & Gill, 2019). According to Hosen et al. (2024), Naimi-Sadigh et al. (2022), and Zhao et al. (2019), banks make better decisions and better serve customers by incorporating technologies that enable efficient analysis of customer data, thereby improving decision-making.
In recent years, rapid technological advancements and the emergence of FinTech companies offering innovative, user-friendly financial solutions have transformed the global banking sector. To remain relevant in an increasingly digital future, traditional banks are working to integrate this technology into the current banking environment to better serve their customers and grow the client base to keep up with the rise in digital demand for faster and more personalized services (Gomber et al., 2018; Murinde et al., 2022). Ofosu-Ampong’s report reveals that the COVID-19 pandemic drove the industry towards digital adoption, and during this period, many banks reported increased online transactions and greater digital engagement (Ofosu-Ampong, 2021). As a result, traditional banks have undergone a rethink of their business models and invested in digital capabilities. According to (Ononiwu et al., 2024), over 60% of banking institutions are either starting or implementing digital transformation projects, which demonstrates the perception of the industry as necessary for agility in a world of cautiousness.
The primary purpose of this review is to evaluate the digital transformation strategies of retail banks worldwide. This SLR reviews specific objectives, including the analysis of how various banks in different regions have adopted digital opportunities to improve their reach, the effects on customer satisfaction, loyalty, and overall experience, and the key challenges in identifying appropriate improvements. Digital transformation in the current times involves open banking, where customers can share their data with third-party providers for improved services; mobile banking, where customers can make more choices on their mobile devices; cloud computing for scalability and cost optimization; and personalization through data analytics for a more detailed banking experience (Berber & Atabey, 2021). Although many research studies have been conducted on digital transformation in banking, they typically discuss fragmented elements such as customer experience, technology adoption, and operational efficiency.
There are few studies that present a thorough, global synthesis of these dimensions to understand how digital transformation strategies affect retail banks as a whole, resulting in a significant knowledge gap in the field. This SLR not only consolidates existing views but also identifies patterns and obstacles, as well as the successful practices of others across various settings. Moreover, this review is significant for policymakers, bank managers, and researchers to make informed decisions that lead to innovation, better customer experience, and the elimination of implementation barriers in the early days of the digital banking environment (Alsemaid et al., 2024; Ghosh et al., 2024). There are also issues related to facilitating digital initiatives, such as organizational culture, as changing culture is essential for successful transformation efforts (Bellantuono et al., 2021; Brunetti et al., 2020; Imran et al., 2021).
The core problem this study addresses is to determine which digital transformation strategies adopted by retail banks across jurisdictions create demonstrable customer value, to identify the organizational, technological, and regulatory barriers that impede their effective implementation, and to specify evidence-based improvement pathways that enable banks to refine and scale these strategies for sustained performance gains.
The review adopted the SLR methodology for digital transformation strategies in retail banking, which was significant for its ability to summarize available knowledge in a broad, fast-changing field. With the ongoing trend of the banking sector toward digitization, there is a strong impetus to converge the outcomes of disparate studies to gain a clearer perspective on the current situation and the feasible solutions to address it (Wansleben, 2023). SLR is a useful instrument for combining various research outcomes to uncover effective ways to implement the digital transformation for stakeholders, namely, practitioners, policymakers, and academics (Bisri et al., 2023; Yusif & Hafeez-Baig, 2024). The result of this comprehensive synthesis will inform future research directions and practical applications in the banking sector. In addition, past research lacks many links and has gaps regarding digital transformation in the banking sector, which requires an SLR (Klein & Todesco, 2021; Kraus et al., 2021; Tekic & Koroteev, 2019).
While there is a growing body of literature, most studies are confined to studying only a few facets of digital transformation without a whole ‘picture’ of how it affects banking performance and customer experience (Mbama & Ezepue, 2018; Nadkarni & Prügl, 2021). However, some have focused on the organizational challenges driving digitalization, and others have analyzed fragmented digitalization from a customer perspective (Kronblad, 2020). Lack of integration hinders the development of a comprehensive, unique understanding of how digital transformation can be leveraged to boost bank performance and overall customer satisfaction. This study uses a systematic review approach to identify gaps in the academic discourse on digital transformation in banking and to suggest avenues for further research to fill them.
This study evaluates retail-bank digital transformation strategies globally with a specific focus on how artificial intelligence (AI) strengthens cybersecurity controls (e.g., anomaly detection, fraud analytics, model-risk governance), enables collaborative value creation with FinTech ecosystems (through API-based interoperability, data-sharing, and third-party risk frameworks), and embeds AI-driven decision-making in core banking workflows (credit, compliance, operations, customer experience). By synthesizing evidence across jurisdictions and institutional settings, the review identifies the mechanisms through which AI shifts banks from incremental digitization toward capability reconfiguration—linking technological adoption to measurable improvements in resilience, efficiency, inclusion, and customer outcomes.
This study contributes originality by integrating cross-jurisdictional evidence on retail-bank digital transformation into a unified construct framework that jointly considers technology adoption (AI, APIs, cloud), regulatory design (open banking, data governance, third-party risk), and organizational outcomes (digital usage, operational resilience, and customer experience). It further links these dimensions through theory-informed mechanisms explaining heterogeneity in digital maturity and distills actionable implications for regulators and bank strategists from a methodologically consistent corpus. By bridging technology, regulation, and performance within one synthesis, the paper offers a replicable template for evidence-based policy and managerial decision-making.
Managerially, the review offers a decision framework that matches AI use cases with risk-governance maturity, data interoperability, and partnership models, enabling banks to prioritize initiatives that yield measurable gains in digital adoption, resilience, and customer outcomes. Methodologically, the PRISMA-guided protocol provides a replicable template for future evidence syntheses in financial-services digitalization. Together, these contributions translate heterogeneous findings into actionable sequencing choices for executives and a transparent research scaffold for scholars.

2. Methodology

To address the need for deeper treatment, the manuscript elaborates the systematic-review protocol (databases, search strings, screening stages, quality appraisal, coding scheme, and synthesis logic), expands interpretation with mechanism-based explanations that account for cross-study heterogeneity (institutional context, data regimes, legacy infrastructure), and strengthens the conclusion by explicitly tracing how the evidence supports the proposed policy, managerial, and research implications. This sharper articulation improves transparency, analytical rigor, and the cumulative logic from evidence to inference.
The methodology is articulated through sequential stages typical of rigorous systematic reviews: protocol definition; database selection and search strategy; multistage screening (title/abstract/full-text) against a priori inclusion/exclusion criteria; quality appraisal and risk-of-bias assessment; structured data extraction with a codebook linking constructs to indicators; and synthesis (qualitative thematic analysis and, where feasible, quantitative aggregation). Each stage reports concise justifications (time window, keyword logic, inter-rater procedures, tie-breaking rules) and corresponding study counts matched with the PRISMA flow, thereby improving transparency, reproducibility, and the credibility of inferences drawn from the final analytical set.
SLR applies the Preferred Reporting Items for Systematic Reviews (PRISMA) framework for maintaining rigorous review transparency. Systematic reviews require a structured approach, and the PRISMA guidelines serve this need, especially for synthesizing existing knowledge about digital transformation strategies in retail banking (Bhuiyan, 2024).

2.1. Search Strategy & Databases

The study used an extensive search strategy to identify studies published from 2015 to 2025. The study utilized the databases Scopus, Web of Science, Google Scholar, ScienceDirect, and IEEE Xplore for its search. The chosen databases successfully covered academic literature across both business and technology domains due to their broad scope. The suitable search terms used in the research included “digital transformation” alongside “retail banking” and “banking sector” variations to ensure extensive exploration of the subject area.

2.2. Inclusion & Exclusion Criteria

This review included research papers that specifically studied digital transformation in retail banking, as they were published after 2015. The research period was selected to observe modern digital banking trends and developments specifically. Only studies focusing on retail banking and direct connections to digital transformation remained, while investigations of other sectors were excluded. The selection criterion rejects research unless it analyses relevant contexts, as studying such circumstances yields meaningful insights (Panke, 2018).
We limited our synthesis to peer-reviewed empirical studies that (i) explicitly examine digital transformation strategies in retail banking; (ii) were published between 2015 and 2025 in English; (iii) report analyzable outcomes matched with our constructs (e.g., AI/automation deployment, open-banking enablement, digital adoption/usage, operational resilience, and customer experience metrics); and (iv) provide sufficient methodological transparency for risk-of-bias appraisal and evidence coding. We excluded conceptual or commentary pieces, cross-sector studies not isolating retail banking effects, fintech-only analyses without a banking counterpart, conference abstracts, grey literature, duplicates, and records lacking outcome measures. Applying these a priori criteria within a PRISMA-guided workflow yielded a focused, methodologically comparable corpus of 20 studies. Retaining a broader pool would have increased construct heterogeneity and threatened internal validity, whereas the final set achieved conceptual saturation—later-screened records were either redundant or failed quality thresholds—thus enabling consistent coding, meta-synthesis across a shared indicator set, and credible cross-jurisdictional inference.

2.3. Data Extraction & Synthesis Approach

Data extraction involved a systematic process where key information from each selected study was recorded. This included details on the digital transformation strategies employed, the challenges banks faced during implementation, and the proposed solutions. The extracted data were then thematically categorized to facilitate synthesis. Thematic analysis is a widely recognized method in systematic reviews that allows researchers to identify patterns and themes across multiple studies (Christou, 2022). By categorizing the findings into strategies, challenges, and solutions, this SLR aims to provide a structured overview of the current state of knowledge regarding digital transformation in retail banking.
To maximize recall and ensure coverage of all relevant literature, we constructed an exhaustive keyword strategy combining controlled vocabulary and free-text terms (e.g., “digital transformation” OR “digitization” OR “digital banking”) AND (retail OR consumer) AND (bank* OR “financial institution”) AND (AI OR “machine learning” OR analytics) AND (cybersecurity OR “operational resilience”) AND (FinTech OR “open banking” OR API). The complete query strings and Boolean variants used per database are reported in Table 1 below.
Figure 1 presents the PRISMA flow diagram for the updated systematic review. It shows how records were identified from databases and registers, how duplicates and records automatically flagged as ineligible were removed, how many reports were screened at the title/abstract and full text stages, and how many studies ultimately met the eligibility criteria and were included in the final synthesis.

3. Theoretical Framework

This study analyses established theories and concepts based on digital transformation strategies for retail banking, given their diverse aspects. The structural foundation integrates the technology acceptance model (TAM) with the resource-based view (RBV), FinTech dynamics, and digital market systems, and considers geographical differences in digital transformation methods (Koroleva, 2022).

3.1. Digital Transformation Theories

Modern users decide to adopt technology based on how easy it feels to use and how useful they think it will be, according to the Technology Acceptance Model (TAM) (Ahmad, 2018). Within retail banking environments, this analysis proves useful because it describes how customers initiate digital banking practices (S. J. Kaur et al., 2021). Studies indicate that consumers tend to adopt digital banking frameworks when they view these solutions as easy to utilize and advantageous, thus compelling financial institutions to elevate digital service user interfaces (Chauhan et al., 2022). A competitive advantage emerges from internal resources and capabilities according to the Resource-Based View (RBV) theory (Sugiarno & Novita, 2022). Through retail banking applications, this theory demonstrates how banks need to use their specific resources, made up of technology infrastructure and skilled human staff with established customer connections, to execute successful digital transformations (Donnellan & Rutledge, 2019). Rane (2023) demonstrates how banks maintain advanced data analytics capabilities to understand customer needs better to deliver personalized services, which produces loyal customers and satisfied customers.

3.2. Role of FinTech and Digital Ecosystems

Digital advancement in retail banking depends heavily on FinTech organizations, which develop disruptive solutions that transform traditional banking practices. Digital ecosystems comprise banking institutions and FinTech, and customers work together through networks to achieve better service delivery (Luigi et al., 2020). The linked network structure enables banks to deliver broader service offerings while improving operational performance (Javaid et al., 2022). Financial institutions achieve superior client experiences through alliances with FinTech firms, which enable them to implement AI and blockchain technologies across their operations (Davradakis & Santos, 2019).
The analysis of FinTech–bank dynamics is expanded to examine co-evolutionary patterns of competition and complementarity, distinguishing front-end customer-experience innovation from back-end process automation and tracing how API-enabled interoperability, data-sharing regimes, and third-party risk governance shape banks’ digital-maturity trajectories. A systemic perspective clarifies when FinTechs act as rivals versus capability amplifiers, how multi-dimensional FinTech behaviors diffuse platform models and interoperability standards across the ecosystem, and why bank–FinTech partnerships differentially affect operational resilience, time-to-market, and customer outcomes. This deeper treatment provides a granular lens on collaboration/competition equilibria and their implications for strategy and regulation.

3.3. Comparison of Digital Transformation Strategies Across Different Regions

Strategic analysis of digital transformation reveals major neighborhood-specific variations due to unique market traditions and regulatory frameworks, as well as residents’ shopping habits. Western banking systems focus on developing omnichannel customer experiences, while emerging-market institutions focus on mobile banking solutions to promote financial inclusion (Shaikh & Karjaluoto, 2015). The operations of mobile banking technology are experiencing rapid growth thanks to Indian government initiatives that have accelerated digital financial inclusion among underserved people (Garg et al., 2024). The United Arab Emirates, a Middle Eastern Nation, has oriented its digital transformation efforts toward complete technology integration, which simultaneously elevates both operational performance and customer relationship quality (Ahmed et al., 2024).

4. Digital Transformation Strategies in Retail Banks

This systematic literature review brings together the key strategies, regional variations, and emerging trends in the digital transformation of retail banking, as presented in the included studies. Several central strategies for the digital transformation of banks have been identified. Customer experience and the accessibility of mobile banking have become critical components in providing convenient, on-the-go financial services (Shanti et al., 2022). The other strategy, which is equally important, is AI-driven chatbots that personalize customer service and streamline operational efficiency through automation (Li et al., 2021). As a prospective integration into banking transactions, blockchain is recognized as a potential pro for security and transparency in payments and fraud detection (Treiblmaier & Beck, 2019). The regulatory frameworks, such as PSD2 in Europe, drive open banking initiatives, which empower banks and third-party providers for a more integrated financial service (Eyers, 2019).
Secondly, cybersecurity needs to be enhanced to protect sensitive customer data, which is increasingly vulnerable to digital threats, so that trustworthy digital banking platforms can be trusted (Avianto et al., 2024). It also affirms many regional differences in digital transformation strategies. In North America, banks primarily focus on developing advanced mobile banking solutions and adopting AI (artificial intelligence) technologies to optimize the customer experience and reduce operational complexity (Diener & Špaček, 2021). In Europe, regulatory initiatives such as PSD2 have accelerated the adoption of open banking models, driving collaboration and competition within the financial ecosystem (Eyers, 2019). The contrast regarding Asia can be seen in the rapid adoption of mobile banking solutions, driven by high smartphone penetration rates and a tech-savvy population (Shaikh & Karjaluoto, 2015).
Infrastructure limitations characterize emerging markets and are complemented, especially in those with financial inclusion potential through mobile technologies, by opportunities to deliver financial services to underserved populations (P. Ozili, 2025). Recent digital transformation trends further underscore how banks are adopting innovative technologies to stay abreast. The ever-increasing adoption of cloud banking is due to its capacity to reduce costs, improve operational efficiency, and enhance scalability (Osei et al., 2023). Another trend is hyper-personalization, which is being used by banks using big data analytics to provide customized products or services to individual customers to increase the satisfaction and loyalty towards the banks (Chauhan et al., 2022; Coelho & Cachola, 2023). Predictive analytics for creditworthiness and fraud detection has become an AI-driven risk assessment, revolutionizing risk management practices by being more accurate (Li et al., 2021). Together, these are an array of strategies and trends that show how retail banks worldwide navigate their digital transformation journeys to adapt to growing customer requirements and stay in the game in a swiftly transforming financial landscape.

5. Value Creation for Customers

Digital banking can create significant value for customers across multiple critical frontiers, such as improving the customer experience and engagement, enhancing security and trust, and achieving greater efficiency and a more accessible banking experience. Personalized services, real-time support, and automated banking solutions help integrate and deliver a new-age experience to customers. According to studies, personalization has evolved from a convenience to an expectation among customers, who now seek personalized experiences that match their tastes and needs (Kothari et al., 2024). For example, AI and data analytics in banking can provide hyper-personalized services, such as delivering financial advice or product recommendations, thereby increasing customer satisfaction and engagement (Shanti et al., 2022). Moreover, AI-driven chatbots deliver timely, efficient support for customer questions and enhance overall service delivery (Li et al., 2021).
There are enhanced security measures as well, as it is also imperative to build trust in the digital banking environment. Digital identity verification methods and blockchain technology implement a robust security framework to consistently safeguard customers’ data and ensure transparent transactions (Treiblmaier & Beck, 2019). With the proliferation of cyberattacks, banks are becoming increasingly concerned about the secure transmission of information, particularly through biometric and cryptographic security measures. Moreover, these measures protect customer data, maintain customer trust, and strengthen the banking relationship (Tanda & Schena, 2019). Also, digital banking services are efficient and accessible, enabling value creation. Now, thanks to digital transformation initiatives, transaction times have been reduced to a minimum, and customers can perform their banking activities with swift efficiency. Self-service banking options give customers greater power to manage their finances independently, boosting financial inclusion, especially in emerging markets where traditional banking may not be available (P. Ozili, 2025). The trend towards enabling self-service capabilities helps banks serve a larger audience and conduct operations that require less reliance on physical branches.

6. Challenges in Implementing Digital Transformation Strategies

Implementing digital transformation strategies in retail banking presents several challenges that can hinder progress and affect overall effectiveness. One significant barrier is technological obstacles, particularly the integration of new digital solutions with legacy systems. Many banks still rely on outdated IT infrastructures, which complicates the adoption of modern technologies such as cloud computing and artificial intelligence (AI). Studies indicate that a considerable percentage of financial institutions continue to operate legacy mainframes that are not designed for today’s interconnected digital environment, making it difficult to achieve seamless integration and data management (Gajula, 2025; Vanaparthi, 2025). In addition, protecting private customer data during the use of new technologies adds challenges to the transformation process (Avianto et al., 2024; Davis, 1989). Following rules and guidelines becomes a significant obstacle in the digital transformation of banks. Times for adopting new digital efforts may be slower because each country or region has its own banking regulations for financial institutions.
It is important for a company to follow these rules to maintain credibility, yet it often takes considerable time and money and can make it harder to move innovations forward (Gomber et al., 2018). So, banks should have serious compliance processes to meet rules while integrating new technologies. Changing the way, a business operates is also often met with resistance. Some workers may be reluctant to use new technology at work, as they worry about losing their jobs or taking time to learn how the technology works (Diener & Špaček, 2021). Constant changing in the world of finance can make customers wary of using new banking technologies. Accomplishing this shift in culture helps support digital innovation within the organization. Cybersecurity threats are also becoming a major issue for banks today. As banks increase their digital footprint, they become more vulnerable to cyberattacks. The need for enhanced cybersecurity measures is paramount, as breaches can lead to significant financial losses and damage customer trust (Tanda & Schena, 2019). Banks must prioritize investments in cybersecurity technologies and practices to safeguard their operations and maintain customer confidence in their digital services.

7. Proposed Framework for Improving Digital Transformation Strategies

Based on the literature, a proposed framework of digital transformation strategies in retail banking emerges, along with recommendations for using advanced technologies, adopting best practices from other countries, and policymaking recommendations for banks and the central bank. The main recommendation is to integrate AI-driven decision-making processes. AI technologies enable banks to increase operational efficiency and extend the scope of their customer service. AI can also analyze large amounts of customer data to provide customized financial advice and perform routine tasks, allowing human employees to spend time on complex customer interactions (Li et al., 2021). Cloud computing is also crucial to the adoption of scalable, flexible banking operations. Osei notes that cloud platforms help seamlessly integrate new technologies and reduce infrastructure costs, including those for updates, maintenance, and support (Osei et al., 2023).
It also includes customer-centric design as a fundamental essence. In this approach, it focuses on customer journeys, mapping touchpoints and areas for improvement so that every online or digital initiative prioritizes enhancing the consumer experience (Best & King, 2018). If banks want to encourage their clients to be more engaged and satisfied, they need to focus on user-friendly interfaces and easy-to-use services. By examining best practices from various countries, one can learn how to successfully undertake a digital transformation (Kitsios et al., 2021). For example, FinTech processes have been identified as robust in Singapore, as it has a robust regulatory environment that allows banks to work with technology providers in each cooperation (Boot et al., 2021). Open banking models are adopted by banks in the UK and the USA that promote competition and increase customer choice through third-party integrations (Eyers, 2019).
Similarly, another such critical example is the UAE, where banks have extensively adopted digital transformation in all operations using advanced technologies to improve customer engagement (Kothari et al., 2024). Through these international examples, we can see how different approaches can have a significant positive impact on operational effectiveness and customer satisfaction. In addition, it is important to provide policy recommendations for banks and regulators to support the proposed framework. For employees and customers to use digital banking platforms with ease, digital literacy is a critical attribute to foster, as it strengthens the digital literacy of every stakeholder. Through training programs that help employees improve digital skills and customers understand how to safely use digital services, employees will be able to adapt to new technologies (Diener & Špaček, 2021). Additionally, there are positive efforts to collaborate with FinTech companies to drive innovation and improve service delivery. Financial institutions can leverage the latest technologies and foster partnerships with FinTech firms to work more efficiently in meeting changing consumer demands (Offiong et al., 2024).
As depicted in Figure 2, the evidence synthesized in this review suggests that regulators should adopt an adaptive, risk-proportionate framework that both safeguards stability and accelerates bank digitalization. Concretely, policy priorities include (i) codifying interoperable open-banking standards (APIs, consent, data portability) to stimulate competition and collaboration; (ii) issuing clear guidance on cloud/third-party outsourcing, data localization, and cross-border data flows to reduce uncertainty and unlock scalable digital infrastructure; (iii) strengthening cybersecurity and operational-resilience requirements (including incident reporting, penetration testing, and sector-wide threat-intelligence sharing); (iv) formalizing AI/model-risk management expectations (governance, validation, explainability, and audit trails) commensurate with use-case criticality; (v) expanding regulatory sandboxes and staged digital-bank licensing to de-risk innovation while enforcing consumer-protection baselines; and (vi) setting national digital-maturity KPIs (e.g., digital transaction share, mobile-app active use, API integrations) and monitoring them via SupTech analytics to steer supervisory dialogue. Complementary public-sector investments in digital identity, payments rails, and workforce upskilling for both supervisors and bank staff can further narrow capability gaps, mitigate legacy-system constraints, and enhance inclusion outcomes identified in the review.

8. Future Research Directions

The online banking revolution offers many avenues for future research, most of which are core areas that will deepen knowledge and hasten the adoption of an innovation strategy (Munira, 2025). An important direction for further research is to extend the research to investment banking as an important avenue for exploration. Despite the current literature’s focus on consumer-facing services, investment banks face unique challenges and opportunities in the digital transformation. Such digital technologies can help optimize trading processes, manage risk, and engage with clients in the investment banking landscape (Avianto et al., 2024). Future work is also likely to apply to the use of quantum computing to optimize banking security. Cyber threat continues to evolve into more sophisticated forms, and traditional encryption may not be enough.
One application of quantum computing is that quantum encryption techniques could enable banks to secure sensitive information at an unprecedented level (Zornetta, 2024). As quantum computing evolves, it will be essential to explore how it can be exploited in banking security protocols and to determine whether it makes sense in current systems. Secondly, the global application of Central Bank Digital Currencies (CBDCs) is an important area of research (P. K. Ozili, 2023). Further, for many central banks, CBDCs are currently either on the corporate roadmap or being tested and piloted; therefore, there is a need to understand how these technologies will impact monetary policy and financial stability, as well as consumer behavior. There could be research on how CBDCs would reconfigure the payment system, aid financial inclusion, or affect the competitive landscape between traditional banks and digital currencies (Barney, 1991).

9. Conclusions

This review presents global trends, challenges, and opportunities arising from digital transformation strategies in retail banking. The review synthesizes results from multiple studies by outlining how AI, blockchain, open banking, and cloud technologies are helping boost banking efficiency and customer experience. Even though there is no debate about the advantages, there are obstacles such as outdated infrastructure, regulatory compliance, and the similar problem of cybersecurity. Challenges in these cases are suggested to be overcome by applying AI-driven decision-making, improved cybersecurity strategies, and better collaboration between banks and FinTechs. In addition, global best practices illustrate how financial institutions in leading economies have effectively integrated digital innovations into their work processes, providing banks worldwide with examples. Future developments in banking security and operational effectiveness should arise from technologies already on the brink of replacing banking systems, such as CBDCs, quantum computing, and other similar technologies. With ongoing changes in banking and digital transformation, a targeted approach to innovation, security, and regulation will be important to preserve competitive advantage and best serve customers by improving financial services.
The evidence indicates that policymakers should prioritize interoperable API standards, proportional AI/model-risk governance, third-party/outsourcing guidance for cloud and data localization, and sector-wide cyber-resilience capabilities, while banks should sequence AI investments from high-signal use cases (fraud/risk analytics, CX personalization) toward deeper process automation, with rigorous validation and human-in-the-loop controls.

Author Contributions

Conceptualization, B.A. and D.A.; methodology, B.A. and D.A.; software, B.A.; validation, B.A. and D.A.; formal analysis, B.A. and D.A.; investigation, B.A. and D.A.; resources, B.A.; data curation, B.A.; writing—original draft preparation, B.A.; writing—review and editing, B.A. and D.A.; visualization, B.A.; supervision, D.A.; project administration, B.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

This study is a systematic review and does not involve new primary data. Data extracted for this review are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Abdullah, M. (2023). The cutting edge technologies in computer science: A review. International Journal of Advanced Research in Computer Science, 14, 13–22. [Google Scholar] [CrossRef]
  2. Adewumi, A., Ewim, S., Sam-Bulya, N., & Ajani, O. (2024). Advancing business performance through data-driven process automation: A case study of digital transformation in the banking sector. International Journal of Multidisciplinary Research Updates, 8, 12–22. [Google Scholar] [CrossRef]
  3. Agarwal, M. (2020). The role of fintech in disrupting traditional banking models. In Unified visions: Collaborative paths in multidisciplinary research (1st ed., Vol. 1). Scribe and Scroll Publishing. [Google Scholar] [CrossRef]
  4. Ahmad, M. (2018). Review of the technology acceptance model (TAM) in internet banking and mobile banking. Available online: https://www.semanticscholar.org/paper/Review-of-The-Technology-Acceptance-Model-(TAM)-in-Ahmad/7a2c94a07ddc0427eeb23afe56e359ac7ef85063 (accessed on 6 October 2025).
  5. Ahmed, G., Al Amiri, N., & Abudaqa, A. (2024). Strategic leadership and economic transformation: The United Arab Emirates (UAE) model. Journal of Global Business Research and Practice, 1(1), 60–77. [Google Scholar] [CrossRef]
  6. Al Nuaimi, M. (2019). An omnichannel digital banking platform for smart city services: UAE case study. The British University in Dubai (BUiD). Available online: https://bspace.buid.ac.ae/handle/1234/1621 (accessed on 6 October 2025).
  7. Alsemaid, O. M., Atri, P., Kande, S. K., & Lembhe, P. (2024). Cutting-edge innovations in technology and security. Available online: https://carijournals.org/product/cutting-edge-innovations-in-technology-and-security/?srsltid=AfmBOopZ6llSF_JHb7skEn_EntWxezPim5F4HC8dhUajfA-MPeF1QzOP (accessed on 6 October 2025).
  8. Avianto, W., Siregar, H., Ratnawati, A., & Siregar, M. E. (2024). Determinants of digital bank transformation: A systematic literature review with prisma and bibliometrics. JPPI (Jurnal Penelitian Pendidikan Indonesia), 10(4), 296–307. [Google Scholar] [CrossRef]
  9. Bankuoru Egala, S., Boateng, D., & Aboagye Mensah, S. (2021). To leave or retain? An interplay between quality digital banking services and customer satisfaction. International Journal of Bank Marketing, 39(7), 1420–1445. [Google Scholar] [CrossRef]
  10. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. [Google Scholar] [CrossRef]
  11. Bellantuono, N., Nuzzi, A., Pontrandolfo, P., & Scozzi, B. (2021). Digital transformation models for the I4.0 transition: Lessons from the change management literature. Sustainability, 13(23), 12941. [Google Scholar] [CrossRef]
  12. Benali, S., & Boumenkar, D. (2024). Contribution of chatbot applications to attaining digital financial inclusion -analysis and evaluation of america’s chatbot erica experience. Management & Economics Research Journal, 6(3), 497–516. [Google Scholar]
  13. Berber, L. K., & Atabey, A. (2021). Open banking & banking-as-a-service (BaaS): A delicate turnout for the banking sector. Global Privacy Law Review, 2(1), 59–82. [Google Scholar]
  14. Best, J., & King, B. (2018). Breaking digital gridlock, + website: Improving your bank’s digital future by making technology changes now. Wiley. [Google Scholar]
  15. Bhuiyan, M. R. I. (2024). Examining the digital transformation and digital entrepreneurship: A PRISMA based systematic review. Pakistan Journal of Life and Social Sciences (PJLSS), 22(1), 1136–1150. [Google Scholar] [CrossRef]
  16. Bisri, A., Putri, A., & Rosmansyah, Y. (2023). A systematic literature review on digital transformation in higher education: Revealing key success factors. International Journal of Emerging Technologies in Learning (iJET), 18(14), 164–187. [Google Scholar] [CrossRef]
  17. Boot, A., Hoffmann, P., Laeven, L., & Ratnovski, L. (2021). Fintech: What’s old, what’s new? Journal of Financial Stability, 53, 100836. [Google Scholar] [CrossRef]
  18. Brunetti, F., Matt, D. T., Bonfanti, A., De Longhi, A., Pedrini, G., & Orzes, G. (2020). Digital transformation challenges: Strategies emerging from a multi-stakeholder approach. The TQM Journal, 32(4), 697–724. [Google Scholar] [CrossRef]
  19. Chauhan, S., Akhtar, A., & Gupta, A. (2022). Customer experience in digital banking: A review and future research directions. International Journal of Quality and Service Sciences, 14(2), 311–348. [Google Scholar] [CrossRef]
  20. Christou, P. A. (2022). How to use thematic analysis in qualitative research. Journal of Qualitative Research in Tourism, 3(2), 79–95. [Google Scholar] [CrossRef]
  21. Coelho, L., & Cachola, G. (2023). Hyper-personalisation: Inducing behaviours through data—How machine learning and automation can help customers make valuable and informed decisions. Journal of Digital Banking, 8(3), 198–209. Available online: https://hstalks.com/article/8294/hyper-personalisation-inducing-behaviours-through-/ (accessed on 6 October 2025). [CrossRef]
  22. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. [Google Scholar] [CrossRef]
  23. Davradakis, E., & Santos, R. (2019). Blockchain, fintechs and their relevance for international financial institutions (Working Paper No. 2019/01). EIB Working Papers.
  24. Diener, F., & Špaček, M. (2021). Digital transformation in banking: A managerial perspective on barriers to change. Sustainability, 13(4), 2032. [Google Scholar] [CrossRef]
  25. Donnellan, J., & Rutledge, W. L. (2019). A case for resource-based view and competitive advantage in banking. Managerial and Decision Economics, 40(6), 728–737. [Google Scholar] [CrossRef]
  26. Eccles, R. G., & Krzus, M. P. (2018, August 6). Constructing bank of America’s 2017 mock integrated report: Experiment no. 3. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3226953 (accessed on 6 October 2025).
  27. Eyers. (2019). Open banking: Implications for the financial landscape. Journal Payments Strategy System, 13(1), 56–68. [Google Scholar]
  28. Faisal, N. A., Nahar, J., Waliullah, M., & Borna, R. S. (2024). The role of digital banking features in bank selection an analysis of customer preferences for online and mobile banking. Frontiers in Applied Engineering and Technology, 1(1), 41–58. [Google Scholar] [CrossRef]
  29. Gajula, S. (2025). Architectural transformation of legacy financial systems: A framework for microservices, cloud, and api integration. International Journal of Information Technology and Management Information Systems, 16(2), 1201–1218. [Google Scholar] [CrossRef]
  30. Garg, P., Srivastava, T., Goel, A., & Gupta, N. (2024). Accelerating financial inclusion in developing economies (India) through digital financial technology. In AI-driven decentralized finance and the future of finance (pp. 205–228). IGI Global Scientific Publishing. [Google Scholar] [CrossRef]
  31. Ghosh, A., Mukhopadhyay, I., & Chakraborty, S. (2024). Design and architectural implementation of consortium blockchain based framework for open banking customer consent and data handling. SN Computer Science, 5(2), 271. [Google Scholar] [CrossRef]
  32. Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2018). On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1), 220–265. [Google Scholar] [CrossRef]
  33. Hosen, M. S., Islam, R., Naeem, Z., Folorunso, E. O., Chu, T. S., Mamun, M. A. A., & Orunbon, N. O. (2024). Data-driven decision making: Advanced database systems for business intelligence. Nanotechnology Perceptions, 20(3), 687–704. [Google Scholar]
  34. Imran, F., Shahzad, K., Butt, A., & Kantola, J. (2021). Digital transformation of industrial organizations: Toward an integrated framework. Journal of Change Management, 21(4), 451–479. [Google Scholar] [CrossRef]
  35. Javaid, M., Haleem, A., Singh, R. P., Suman, R., & Khan, S. (2022). A review of blockchain technology applications for financial services. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2(3), 100073. [Google Scholar] [CrossRef]
  36. Kaur, D. J., & Gill, N. S. (2019). Artificial intelligence and deep learning for decision makers: A growth hacker’s guide to cutting edge technologies. BPB Publications. [Google Scholar]
  37. Kaur, S. J., Ali, L., Hassan, M. K., & Al-Emran, M. (2021). Adoption of digital banking channels in an emerging economy: Exploring the role of in-branch efforts. Journal of Financial Services Marketing, 26(2), 107–121. [Google Scholar] [CrossRef]
  38. Kitsios, F., Giatsidis, I., & Kamariotou, M. (2021). Digital transformation and strategy in the banking sector: Evaluating the acceptance rate of e-services. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 204. [Google Scholar] [CrossRef]
  39. Klein, V. B., & Todesco, J. L. (2021). COVID-19 crisis and SMEs responses: The role of digital transformation. Knowledge and Process Management, 28(2), 117–133. [Google Scholar] [CrossRef]
  40. Koroleva, E. (2022). FinTech business models and their linkages with customers and founders [Ph.D. thesis, Tallinna Tehnikaülikool Tallinn University of Technology]. [Google Scholar]
  41. Kothari, U., Grandhi, B., & Thrassou, A. (2024). Digital transformation of retail banking in the United Arab Emirates. Journal of Asia Business Studies, 19(1), 163–181. [Google Scholar] [CrossRef]
  42. Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital transformation: An overview of the current state of the art of research. Sage Open, 11(3), 21582440211047576. [Google Scholar] [CrossRef]
  43. Kronblad, C. (2020). How digitalization changes our understanding of professional service firms. Academy of Management Discoveries, 6(3), 436–454. [Google Scholar] [CrossRef]
  44. Li, Y., Yi, J., Chen, H., & Peng, D. (2021). Theory and application of artificial intelligence in financial industry. Data Science in Finance and Economics, 1(2), 96–116. [Google Scholar] [CrossRef]
  45. Luigi, W., Lee, J., & Thomsett, M. C. (2020). Disruptions and digital banking trends. Journal of Applied Finance and Banking, 10(6), 15–56. [Google Scholar]
  46. Mbama, C. I., & Ezepue, P. O. (2018). Digital banking, customer experience and bank financial performance: UK customers’ perceptions. International Journal of Bank Marketing, 36(2), 230–255. [Google Scholar] [CrossRef]
  47. Munira, M. S. K. (2025). Digital transformation in banking: A systematic review of trends, technologies, and challenges (SSRN Scholarly Paper No. 5161354). Social Science Research Network. [Google Scholar] [CrossRef]
  48. Murinde, V., Rizopoulos, E., & Zachariadis, M. (2022). The impact of the FinTech revolution on the future of banking: Opportunities and risks. International Review of Financial Analysis, 81, 102103. [Google Scholar] [CrossRef]
  49. Nadkarni, S., & Prügl, R. (2021). Digital transformation: A review, synthesis and opportunities for future research. Management Review Quarterly, 71(2), 233–341. [Google Scholar] [CrossRef]
  50. Naimi-Sadigh, A., Asgari, T., & Rabiei, M. (2022). Digital transformation in the value chain disruption of banking services. Journal of the Knowledge Economy, 13(2), 1212–1242. [Google Scholar] [CrossRef]
  51. Offiong, U. P., Szopik-Depczyńska, K., Cheba, K., & Ioppolo, G. (2024). FinTech as a digital innovation in microfinance companies—Systematic literature review. European Journal of Innovation Management, 27(9), 562–581. [Google Scholar] [CrossRef]
  52. Ofosu-Ampong, K. (2021). Determinants, barriers and strategies of digital transformation adoption in a developing country COVID-19 era. Journal of Digital Science, 3(2), 67–83. [Google Scholar] [CrossRef]
  53. Ononiwu, M. I., Onwuzulike, O. C., & Shitu, K. (2024). The role of digital business transformation in enhancing organizational agility. World Journal of Advanced Research and Reviews, 23(3), 285–308. [Google Scholar] [CrossRef]
  54. Osei, L. K., Cherkasova, Y., & Oware, K. M. (2023). Unlocking the full potential of digital transformation in banking: A bibliometric review and emerging trend. Future Business Journal, 9(1), 30. [Google Scholar] [CrossRef]
  55. Ozili, P. (2025). Financial inclusion in banking: A literature review and future research directions. Modern Finance, 3(1), 91–109. [Google Scholar] [CrossRef]
  56. Ozili, P. K. (2023). Central bank digital currency research around the world: A Review of literature. Journal of Money Laundering Control, 26(2), 215–226. [Google Scholar] [CrossRef]
  57. Panke, D. (2018). Research design & method selection. SAGE Publications. Available online: https://uk.sagepub.com/en-gb/mst/research-design-method-selection/book260462 (accessed on 6 October 2025).
  58. Pundareeka Vittala, K. R., Ahmad, S. S., Seranmadevi, R., & Tyagi, A. K. (2024). Emerging technology adoption and applications for modern society towards providing smart banking solutions. In A. K. Sharma, N. Chanderwal, S. Tyagi, P. Upadhyay, & A. K. Tyagi (Eds.), Advances in medical technologies and clinical practice (pp. 315–329). IGI Global. [Google Scholar] [CrossRef]
  59. Rane, N. (2023, October 13). Enhancing customer loyalty through Artificial Intelligence (AI), Internet of Things (IoT), and Big Data technologies: Improving customer satisfaction, engagement, relationship, and experience. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4616051 (accessed on 6 October 2025).
  60. Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review. Telematics and Informatics, 32(1), 129–142. [Google Scholar] [CrossRef]
  61. Shanti, R., Avianto, W., & Wibowo, W. A. (2022). A systematic review on banking digital transformation. Jurnal Ad’ministrare, 9(2), 543. [Google Scholar] [CrossRef]
  62. Sugiarno, Y., & Novita, D. (2022). Resources-Based View (RBV) as a strategy of company competitive advantage: A literature review. International Conference on Economics Business Management and Accounting (ICOEMA), 1, 656–666. [Google Scholar]
  63. Tanda, A., & Schena, C.-M. (2019). FinTech, BigTech and banks: Digitalisation and its impact on banking business models. Springer International Publishing. [Google Scholar] [CrossRef]
  64. Tekic, Z., & Koroteev, D. (2019). From disruptively digital to proudly analog: A holistic typology of digital transformation strategies. Business Horizons, 62(6), 683–693. [Google Scholar] [CrossRef]
  65. Treiblmaier, H., & Beck, R. (Eds.). (2019). Business transformation through blockchain: Volume I (Vol. 1). Springer International Publishing. [Google Scholar]
  66. Vanaparthi, N. R. (2025). The roadmap to mainframe modernization: Bridging legacy systems with the cloud. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 11(1), 125–133. [Google Scholar] [CrossRef]
  67. Wansleben, L. (2023). The rise of central banks: State power in financial capitalism. Harvard University Press. [Google Scholar]
  68. Yusif, S., & Hafeez-Baig, A. (2024). Evidence-based information systems (IS) research: The case of systematic literature review (SLR). Authorea. [Google Scholar]
  69. Zhao, Q., Tsai, P.-H., & Wang, J.-L. (2019). Improving financial service innovation strategies for enhancing China’s banking industry competitive advantage during the fintech revolution: A hybrid MCDM model. Sustainability, 11(5), 1419. [Google Scholar] [CrossRef]
  70. Zornetta, A. (2024). Quantum-safe global encryption policy. International Journal of Law and Information Technology, 32, eaae020. [Google Scholar] [CrossRef]
  71. Zouari, G., & Abdelhedi, M. (2021). Customer satisfaction in the digital era: Evidence from islamic banking. Journal of Innovation and Entrepreneurship, 10(1), 9. [Google Scholar] [CrossRef]
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Figure 1. Identification, Screening, and Inclusion of Studies in Updated Systematic Review. Note: * “Databases” and “Registers” refer to all electronic sources searched for this review (see Methodology section for the full list of databases and registers). ** Records marked as ineligible by automation tools were removed by automatic deduplication and preliminary relevance filters in the reference-management/screening software before manual screening.
Figure 1. Identification, Screening, and Inclusion of Studies in Updated Systematic Review. Note: * “Databases” and “Registers” refer to all electronic sources searched for this review (see Methodology section for the full list of databases and registers). ** Records marked as ineligible by automation tools were removed by automatic deduplication and preliminary relevance filters in the reference-management/screening software before manual screening.
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Figure 2. Proposed Framework.
Figure 2. Proposed Framework.
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Table 1. Overview of Selected Studies on Digital Transformation in Retail Banking.
Table 1. Overview of Selected Studies on Digital Transformation in Retail Banking.
No.Author(s)Title
1(Abdullah, 2023)The Cutting Edge Technologies in Computer Science: A Review
2(Adewumi et al., 2024)Advancing Business Performance Through Data-Driven Process Automation: A Case Study of Digital Transformation in the Banking Sector
3(Ahmad, 2018)Review of the Technology Acceptance Model (TAM) in Internet Banking and Mobile Banking
4(Ahmed et al., 2024)Strategic Leadership and Economic Transformation: The United Arab Emirates (UAE) Model
5(Faisal et al., 2024)The Role of Digital Banking Features in Bank Selection
6(Alsemaid et al., 2024)Cutting-Edge Innovations in Technology and Security
7(Berber & Atabey, 2021)Open Banking & Banking-as-a-Service (BaaS): A Delicate Turnout for the Banking Sector
8(Bankuoru Egala et al., 2021)To Leave or Retain? An Interplay Between Quality Digital Banking Services and Customer Satisfaction
9(Bellantuono et al., 2021)Digital Transformation Models for the I4.0 Transition: Lessons from the Change Management Literature
10(Best & King, 2018)Breaking Digital Gridlock: Improving Your Bank’s Digital Future by Making Technology Changes Now
11(Bhuiyan, 2024)Examining the Digital Transformation and Digital Entrepreneurship: A PRISMA-Based Systematic Review
12(Bisri et al., 2023)A Systematic Literature Review on Digital Transformation in Higher Education
13(Boot et al., 2021)FinTech: What’s Old, What’s New?
14(Brunetti et al., 2020)Digital Transformation Challenges: Strategies Emerging from a Multi-Stakeholder Approach
15(Chauhan et al., 2022)Customer Experience in Digital Banking: A Review and Future Research Directions
16(Christou, 2022)How to Use Thematic Analysis in Qualitative Research
17(Davradakis & Santos, 2019)Blockchain, FinTechs and Their Relevance for International Financial Institutions
18(Donnellan & Rutledge, 2019)A Case for Resource-Based View and Competitive Advantage in Banking
19(Garg et al., 2024)Accelerating Financial Inclusion in Developing Economies (India) Through Digital Financial Technology
20(Ghosh et al., 2024)Design and Architectural Implementation of Consortium Blockchain-Based Framework for Open Banking Customer Consent and Data Handling
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Alsobai, B.; Aassouli, D. Assessing Digital Transformation Strategies in Retail Banks: A Global Perspective. J. Risk Financial Manag. 2025, 18, 710. https://doi.org/10.3390/jrfm18120710

AMA Style

Alsobai B, Aassouli D. Assessing Digital Transformation Strategies in Retail Banks: A Global Perspective. Journal of Risk and Financial Management. 2025; 18(12):710. https://doi.org/10.3390/jrfm18120710

Chicago/Turabian Style

Alsobai, Bothaina, and Dalal Aassouli. 2025. "Assessing Digital Transformation Strategies in Retail Banks: A Global Perspective" Journal of Risk and Financial Management 18, no. 12: 710. https://doi.org/10.3390/jrfm18120710

APA Style

Alsobai, B., & Aassouli, D. (2025). Assessing Digital Transformation Strategies in Retail Banks: A Global Perspective. Journal of Risk and Financial Management, 18(12), 710. https://doi.org/10.3390/jrfm18120710

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