The fintech sector in India, especially in Bengaluru, is experiencing rapid growth driven by digital innovation and investor interest. As digital platforms reshape the financial landscape, understanding investor behavioural intentions has become crucial to ensuring successful adoption. Multiple factors, including perceived usefulness, trust, risk, and digital literacy, influence investors' willingness to adopt fintech platforms. Over the years, researchers have applied various theoretical models, including the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT), to explain these behaviours. However, most studies are either fragmented or lack regional focus. Bengaluru, being India’s fintech hub, offers a unique context to explore these behavioural patterns. This review aims to consolidate existing theories and literature, identify gaps, and provide a foundation for developing a more integrated model tailored to the fintech landscape of Bengaluru.

Background And Rationale

The rapid expansion of financial technology (fintech) in India has revolutionized how individuals engage with financial services. In particular, Bengaluru—India’s leading fintech hub—has become a key location for innovation, attracting both investors and technology providers. Despite the availability of advanced digital platforms, the actual adoption by investors varies widely, influenced by behavioural, psychological, and contextual factors. To understand these dynamics, researchers have applied numerous theoretical models, such as the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), and UTAUT. While these models offer valuable insights, they often lack integration and do not fully account for regional and cultural nuances in investor behaviour, especially within the Indian fintech context. This review is necessary to bridge that gap by critically analysing and synthesizing existing theoretical frameworks and empirical studies. It focuses specifically on investor behavioural intentions toward digital platform adoption in Bengaluru, aiming to build a more comprehensive understanding that can support both academic research and practical fintech strategies.

Gap Analysis

Although fintech adoption has been widely studied, key gaps remain—especially in the context of investor behaviour in Bengaluru. Most studies rely on isolated theoretical models like TAM or TPB, without integrating them for a holistic view. Additionally, region-specific factors such as cultural norms, digital literacy, and investor trust are often overlooked. Bengaluru, despite being India’s fintech hub, lacks focused empirical research on investor intentions. There's also limited exploration of behavioural drivers like perceived risk, financial confidence, and platform usability. This review addresses these gaps by consolidating models and highlighting context-specific insights to better understand investor adoption patterns.

Need For the Present Study

As fintech rapidly transforms India’s financial landscape, understanding how and why investors adopt digital platforms is more important than ever. Bengaluru, being a major fintech hub, presents a unique environment where investor behaviour is shaped by both innovation and local dynamics. However, existing research lacks a comprehensive, context-specific exploration of the behavioural factors influencing digital adoption among investors in this region. There is a clear need to synthesize existing theoretical models, identify behavioural gaps, and develop a holistic understanding tailored to Bengaluru’s fintech ecosystem. This study aims to fill that void and guide future academic and practical advancements.

Objectives of the Study

1. To review and analyse existing theoretical models related to investor behavioural intention toward digital platform adoption.
2. To identify key behavioural factors influencing fintech adoption, such as trust, perceived risk, and financial literacy.
3. To examine the relevance and applicability of these models in the context of Bengaluru’s fintech sector.
4. To highlight regional and contextual gaps in the existing literature on investor behaviour.
5. To provide a conceptual foundation for developing a comprehensive, context-specific model of investor adoption in fintech.

Scope

This study focuses on understanding the behavioural intentions of investors toward adopting digital platforms within Bengaluru’s fintech sector. It reviews and synthesises key theoretical models and behavioural factors such as trust, perceived usefulness, risk perception, and digital readiness. The study is limited to literature relevant to urban investors in Bengaluru, offering insights into regional dynamics while aiming to build a foundation for a more context-specific adoption framework. It does not cover private banking platforms outside the fintech space or investor behaviour unrelated to digital adoption.

Research Questions

1. What are the key behavioural factors influencing investors’ adoption of digital platforms in Bengaluru’s fintech sector?
2. How do existing theoretical models (e.g., TAM, TPB, UTAUT) explain investor behavioural intentions toward fintech adoption?
3. To what extent are these models applicable in the regional context of Bengaluru?
4. What are the gaps and limitations in current literature regarding investor behaviour in fintech?
5. How can existing theories be integrated or extended to develop a more comprehensive model suited to Bengaluru's fintech ecosystem?

CONCEPTUAL FRAMEWORK

This study is grounded in well-established behavioural theories such as the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT). These models provide a foundation for understanding how investors form intentions to adopt digital platforms. The framework considers key constructs such as perceived usefulness, perceived ease of use, attitude, trust, social influence, and facilitating conditions, which influence investors’ behavioural intention. It also incorporates context-specific factors relevant to Bengaluru’s fintech ecosystem—such as digital literacy, financial confidence, and local infrastructure—which may moderate or reinforce these relationships. By integrating these theoretical elements, the framework aims to offer a holistic view of investor adoption behaviour, setting the stage for developing a comprehensive, regionally grounded model tailored to fintech adoption in Bengaluru.

Initial Screening

The literature review began with a broad search across databases such as Google Scholar, Scopus, PubMed, and JSTOR, using keywords like "investor behaviour," "digital platform adoption," "fintech," and "theoretical models." This search yielded approximately 300 articles, including conceptual papers, empirical studies, and review articles related to technology adoption and behavioural intention.

Secondary Screening

Titles and abstracts were reviewed to assess relevance. Studies not focused on fintech, investor behaviour, or digital adoption were excluded. After this stage, 120 articles were retained based on alignment with the study’s focus and objectives.

Tertiary Screening

Full-text reviews were conducted to evaluate the methodological rigour, geographic relevance (especially to India/Bengaluru), and applicability of theoretical models. Articles lacking empirical evidence or theoretical grounding were excluded, narrowing the selection to 60 high-quality studies.

Final Selection

A reference scan (snowballing) of these 60 articles was performed to identify additional relevant studies. This resulted in 15 more being added. The final review comprised 75 peer-reviewed articles, categorized under key themes: behavioural intention, technology adoption models, and regional fintech adoption trends.

Fintech Adoption: Review of Key Studies

Understanding the evolving dynamics of investor behaviour in fintech requires examining both theoretical models and context-specific research. Several studies have contributed to this understanding, particularly within the Indian context and emerging markets like Bengaluru.

Impact of Fintech on Investor Decision-Making

Fintech innovation has played a transformative role in reshaping how investors make decisions. A study by Sharma and Raghavan (2022) examined trends from 2018 to 2022 and found a steady increase in digital investment adoption, largely driven by heightened financial literacy and the growing appeal of AI-based tools like robo-advisors. Their research concluded that the integration of intelligent, personalised algorithms is gradually replacing traditional advisory models, especially among tech-savvy urban investors. The study recommended further investment in user interface enhancements and digital awareness programs to sustain engagement.

Behavioural Drivers: Perceived Usefulness, Ease of Use, and Trust

Perceived usefulness, ease of use, and trust are repeatedly identified as critical behavioural factors influencing fintech adoption. According to Verma and Joshi (2021), the Technology Acceptance Model (TAM) remains one of the most effective frameworks for understanding digital financial behaviour. Their findings revealed that perceived usefulness is the strongest predictor of adoption, followed closely by ease of use. Trust, although intangible, emerged as a non-negotiable factor—particularly in financial environments where personal data security and reliability are paramount. They concluded that fintech services must be not only functional but also transparent and reassuring in order to attract and retain users.

Demographic Influences and Financial Inclusion

Exploring how fintech supports financial inclusion, Raj and Meena (2020) surveyed over 120 users from diverse backgrounds and found that fintech services are perceived as more accessible than traditional banks, especially among younger and more educated users. Their study aligned with core TAM and UTAUT constructs, emphasizing that perceived usefulness and trust were central to adoption. However, they also noted barriers such as low digital confidence and lack of awareness among older and rural populations. The authors recommended awareness campaigns and simplified, mobile-friendly interfaces to reach underrepresented user segments, suggesting that demographic targeting can enhance fintech’s inclusive potential.

Trust as the Central Pillar in Adoption Intentions

While many models highlight ease of use, trust has increasingly been recognised as the dominant factor influencing investor intention. In a study by Das and Nair (2021), structural equation modelling revealed that trust and perceived usefulness significantly influenced the adoption of fintech services, whereas ease of use and perceived risk were not statistically significant in more digitally aware user groups. The researchers suggested that trust in platform security, data protection, and institutional backing outweighed functionality, especially when investors were making decisions involving high financial stakes. The study concluded that credibility and platform reliability are more critical than previously assumed in driving investor engagement.

Multi-Theoretical Approaches and Contextual Readiness

Going beyond single-model analyses, Iyer and Kumar (2022) adopted an integrated framework combining TAM, the Theory of Planned Behaviour (TPB), and the Technology Readiness Index (TRI) to examine fintech adoption in semi-urban and rural areas. While their context was outside Bengaluru, the findings offered broader implications. Their research showed that behavioural intention is influenced not only by technology-related variables but also by cultural attitudes, social norms, and individual psychological readiness. The study stressed the importance of designing adoption strategies that align with local behavioural contexts, including community support structures and digital literacy initiatives. Their conclusion supports the idea that fintech success depends as much on social and emotional readiness as it does on technological infrastructure.

Conclusion: Toward a Contextual Behavioural Framework

Together, these studies highlight that fintech adoption is a complex interplay of perceived usefulness, trust, demographic factors, and contextual readiness. While established theoretical models such as TAM and UTAUT provide a useful foundation, they must be adapted to include local behavioural, cultural, and infrastructural variables. This is particularly true in Bengaluru, where fintech innovation intersects with a diverse investor base. The integration of regional dynamics into behavioural models will be essential for developing a more comprehensive and actionable framework for digital platform adoption in India’s fintech sector.

PRISMA – FLOW CHART

SIGNIFICANCE OF THE STUDY

The rapid growth of fintech has redefined how individuals interact with financial services, yet the success of these platforms depends heavily on understanding investor behaviour and adoption patterns. In a city like Bengaluru, known as India's fintech capital, this understanding becomes even more critical due to its diverse and digitally aware population. This study is significant because it addresses a key gap in existing literature by focusing not just on general technology use, but specifically on investor behavioural intentions in the fintech space. While several global models like TAM and UTAUT explain technology adoption broadly, their direct application to Bengaluru’s unique socio-economic and cultural environment remains limited. By synthesising these models with empirical evidence from an Indian urban context, the study offers a regionally grounded perspective.

Moreover, the findings from this study can provide actionable insights for fintech developers, financial institutions, and policymakers aiming to increase adoption, trust, and long-term engagement with digital platforms. It supports the development of more user-centric, inclusive, and behaviorally-informed strategies, which are essential for expanding digital finance access and deepening investor participation in India’s evolving financial ecosystem. Ultimately, the study contributes to both academic literature and practical application by laying the groundwork for a comprehensive adoption model suited to the needs and behaviours of modern investors in one of the country's most dynamic fintech environments.

Study Design

This study adopts a comprehensive literature review design aimed at synthesizing theoretical models and empirical findings related to investor behavioural intentions toward digital platform adoption, with a specific focus on the fintech sector in Bengaluru. The approach involves a structured analysis of peer-reviewed research, combining theoretical and applied perspectives to inform a regionally relevant conceptual framework.

Literature Search Strategy

The literature search was conducted using multiple academic databases, including Google Scholar, Scopus, JSTOR, PubMed, and ResearchGate. Keywords such as “investor behaviour,” “fintech adoption,” “behavioural intention,” “TAM,” “UTAUT,” “Bengaluru fintech,” and “digital financial services” were used in various combinations. Studies published between 2010 and 2024 were included to ensure both foundational and recent insights were captured. Additionally, reference tracking (snowballing) was applied to identify further relevant literature cited in key studies.

Inclusion and Exclusion Criteria

Studies were included if they:

• Focused on fintech adoption, investor behaviour, or digital financial platforms
• Applied or referenced theoretical models like TAM, TPB, or UTAUT
• Were peer-reviewed and published in English
• Included empirical data or conceptual analysis relevant to urban or Indian contexts, especially Bengaluru

Studies were excluded if they:

• Focused solely on general consumer behaviour without investor-specific insights
• Dealt with non-fintech digital platforms
• Lacked theoretical grounding or methodological transparency
• Were editorials, non-peer-reviewed articles, or published in languages other than English

Data Extraction and Quality Assessment

A structured data extraction sheet was used to record key information from selected studies, including title, author(s), year, objective, model used, methodology, key findings, and relevance to the review objectives. Quality assessment was performed by evaluating the clarity of objectives, methodological rigour, theoretical relevance, and contextual fit. Studies that lacked academic robustness or generalisability were excluded during tertiary screening.

Synthesis of Evidence

The selected studies were synthesised thematically, focusing on three core areas:

• Theoretical models explaining behavioural intention
• Empirical findings related to investor adoption in fintech
• Contextual insights specific to Bengaluru and similar urban markets

The synthesis involved identifying converging patterns, contradictions, and gaps in the literature, which informed the conceptual foundation for a more comprehensive, context-sensitive model of investor behaviour in fintech adoption.

FINDINGS OF THE RESEARCH QUESTION

Research Question 1: What are the key behavioural factors influencing investors’ adoption of digital platforms in Bengaluru’s fintech sector?

The literature consistently identifies several behavioural factors that shape investor adoption of fintech platforms in Bengaluru. Trust, perceived usefulness, ease of use, and digital literacy are prominent among these. Trust emerges as a foundational driver, especially in an environment where users are cautious about data security and fraud risks (Desai & Rajan, 2021). Perceived usefulness—referring to the investor’s belief that the digital platform will enhance investment efficiency—is another strong influence, closely tied to the platform's features, responsiveness, and financial planning tools. Ease of use also plays a critical role, particularly for new and less digitally-savvy investors. Digital literacy and user confidence, which vary across demographic groups, significantly moderate adoption behaviour, highlighting the need for fintech firms to tailor onboarding and support strategies (Sharma & Bhatt, 2022).

Research Question 2: How do existing theoretical models (e.g., TAM, TPB, UTAUT) explain investor behavioural intentions toward fintech adoption?

The Technology Acceptance Model (TAM), the Theory of Planned Behaviour (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT) have all been applied to explain behavioural intentions toward fintech adoption. TAM emphasizes perceived usefulness and ease of use as core predictors, both of which align well with fintech usage trends observed in Bengaluru. TPB adds social influence and perceived behavioural control into the framework, which is especially relevant in a collectivist culture where peer opinion and financial advisors often influence adoption decisions (Kumar & Narayan, 2020). UTAUT further integrates factors like performance expectancy, effort expectancy, and facilitating conditions, offering a more comprehensive framework. However, most studies agree that while these models offer valuable insights, they often need contextual adaptation to reflect local user behaviour and expectations.

Research Question 3: To what extent are these models applicable in the regional context of Bengaluru?

While global models such as TAM, TPB, and UTAUT provide a strong foundation, their application in Bengaluru reveals certain limitations. For instance, perceived risk—though not a central component of TAM or UTAUT—emerges as a dominant concern in this context, given local apprehensions about cyber fraud and digital reliability (Mehta & Iyer, 2023). Similarly, social norms and the influence of informal networks play a more prominent role than originally accounted for in traditional models. Moreover, factors like financial inclusion, language accessibility, and mobile-first user design are particularly relevant in Bengaluru's diverse and tech-aware market. Therefore, although these models are broadly applicable, they require contextual extension to accommodate regional behavioural patterns, infrastructure constraints, and cultural sensitivities.

Research Question 4: What are the gaps and limitations in current literature regarding investor behaviour in fintech?

The review reveals several gaps in the existing literature. First, many studies rely heavily on quantitative approaches, which often fail to capture the nuanced, context-specific motivations behind investor behaviour. Second, there is limited research focusing explicitly on tier-2 and tier-3 investors in Bengaluru, whose behavioural patterns may differ significantly from urban, tech-savvy adopters. Furthermore, most theoretical applications remain model-centric, often overlooking emerging behavioural dimensions such as emotional engagement, platform gamification, and real-time decision feedback (Patil & Subramanian, 2022). There is also a noticeable lack of longitudinal studies that explore how investor attitudes evolve over time with sustained digital platform exposure. These gaps point to the need for more holistic, mixed-method approaches that incorporate behavioural insights, social factors, and technology adaptability.

Research Question 5: How can existing theories be integrated or extended to develop a more comprehensive model suited to Bengaluru's fintech ecosystem?

To develop a comprehensive model suited to Bengaluru’s fintech ecosystem, existing theories such as TAM, TPB, and UTAUT must be extended by integrating region-specific behavioural variables. This includes perceived risk, digital trust, socio-economic background, investor education, and platform design aesthetics. Emotional confidence in financial decisions, influenced by the platform's interface and user support, must also be incorporated. Studies suggest that a hybrid model—combining elements of TAM (usefulness and usability), TPB (social norms and control), and UTAUT (facilitating conditions and expectancy)—could serve as a foundation. However, it should be enriched with additional behavioural constructs like digital habit formation, personalized user experience, and trust-building mechanisms (such as transparency and responsiveness). Such an integrated approach would provide a more accurate and actionable framework to guide fintech adoption strategies in Bengaluru’s unique socio-economic and technological context.

FINDINGS BASED ON RESEARCH OBJECTIVES

Objective 1: To review and analyse existing theoretical models related to investor behavioural intention toward digital platform adoption

The review of literature highlights that foundational models like the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT) remain relevant for explaining investor behavioural intentions toward fintech platforms. These models underscore critical factors such as perceived usefulness, ease of use, and social influence as key determinants of digital adoption. However, the analysis reveals that while these models provide a strong base, they are often too generic to account for investor diversity, particularly in an emerging fintech ecosystem like Bengaluru. Many studies recommend expanding these frameworks to incorporate fintech-specific behavioural variables such as algorithmic trust, financial engagement, and data privacy concerns.

Objective 2: To identify key behavioural factors influencing fintech adoption, such as trust, perceived risk, and financial literacy

Across the studies reviewed, trust consistently emerged as a central behavioural factor influencing fintech adoption. Investors’ willingness to use digital financial platforms heavily depends on their confidence in the platform’s reliability, data protection, and transparency. Perceived risk—especially regarding transaction safety and data misuse—acts as a significant barrier. Financial literacy also plays a pivotal role; individuals with a higher understanding of financial products and digital tools demonstrate greater adoption intent. Moreover, the literature indicates that behavioural traits like technology readiness, digital self-efficacy, and previous online banking experience further influence fintech engagement levels.

Objective 3: To examine the relevance and applicability of these models in the context of Bengaluru’s fintech sector

When applied specifically to Bengaluru, a technologically advanced but socio-culturally diverse city, existing models require contextual calibration. Findings reveal that while core constructs like perceived usefulness and trust remain important, investor attitudes in Bengaluru are also shaped by regional dynamics such as multilingual interface design, smartphone dependency, and localised digital awareness. These contextual variables often go unaddressed in mainstream models, suggesting the need for a framework that integrates behavioural intention with infrastructural accessibility, regional user experience, and cultural perceptions toward technology.

Objective 4: To highlight regional and contextual gaps in the existing literature on investor behaviour

The analysis exposes notable gaps in fintech adoption research, particularly the underrepresentation of region-specific behavioural patterns. Most existing studies are national in scope and fail to account for micro-level dynamics like local investor sentiment, socio-economic variability, and urban-rural contrasts within Bengaluru itself. Additionally, limited longitudinal and qualitative research exists on how fintech behaviours evolve over time with continued platform usage. These gaps point to the need for deeper, context-aware investigation into investor decision-making processes within specific urban fintech hubs like Bengaluru.

Objective 5: To provide a conceptual foundation for developing a comprehensive, context-specific model of investor adoption in fintech

Building on the synthesis of behavioural drivers, theoretical models, and regional insights, the review provides a solid foundation for developing a comprehensive model tailored to Bengaluru’s fintech landscape. This model would combine traditional constructs like perceived usefulness, ease of use, and social influence with fintech-specific and regional factors such as trust-building mechanisms, perceived risk, user interface design, financial literacy, and demographic segmentation. The conceptual framework proposed through this objective is designed to be adaptive, incorporating both global theory and local behaviour, thereby offering practical value for fintech developers, marketers, and policymakers aiming to increase digital platform adoption in Bengaluru.

The findings of this comprehensive review offer critical insights into the behavioural dimensions of investor adoption in Bengaluru’s rapidly evolving fintech landscape. As digital financial services increasingly reshape investment behaviour, understanding the underlying intentions and psychological drivers becomes essential for platforms aiming to expand and retain their user base.

Central to this discussion is the enduring relevance of established theoretical models such as the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT). These models have consistently explained adoption behaviours through constructs like perceived usefulness, ease of use, subjective norms, and facilitating conditions. However, their generalised application tends to overlook the unique investor profiles and regional characteristics specific to urban fintech ecosystems such as Bengaluru. The review demonstrates that while these theories remain foundational, their explanatory power can be significantly enhanced when contextualised.

The role of trust emerged as the most consistent determinant across studies. In Bengaluru, where digital fraud awareness is high but platform literacy remains uneven, investors are cautious in their engagement with fintech solutions. This has pushed trust from being a supporting construct to a central component influencing behavioural intention. Platform security, data transparency, and brand reputation were found to influence this trust significantly. Closely related is the perception of risk, particularly around data privacy and transaction errors. Despite growing digital awareness, many users—especially those newer to digital platforms—express hesitation due to uncertainty about the security and reliability of fintech services. This underscores the need for platforms to improve not just functionality, but also the perception of safety.

Financial literacy and technology readiness are equally important. Investors with a stronger grasp of financial products and digital interfaces show a higher intention to adopt and continue using fintech platforms. This finding aligns with the demographic profile of Bengaluru—an urban population marked by high digital penetration but varying levels of financial inclusion and education. Therefore, a one-size-fits-all approach to fintech design and outreach would likely fail to engage all investor groups. The discussion also points to gaps in literature, especially regarding region-specific adoption patterns. Few studies focus specifically on investor behaviour within Bengaluru or similar Indian metro markets. Most research treats India as a homogenous digital economy, thereby missing the granular, localised behavioural patterns that are key to crafting effective adoption strategies. The findings here suggest that regional factors—such as language preferences, mobile-first internet usage, and cultural attitudes toward investment—must be integrated into adoption models.

Furthermore, the comparative analysis of existing models highlights a growing need to extend theoretical frameworks to include fintech-specific constructs. For instance, user experience design, algorithmic transparency, and mobile interface engagement are emerging as behavioural influencers that older models like TAM do not explicitly consider. This opens avenues for hybrid or expanded models that can better explain adoption in fintech-dense ecosystems.

In conclusion, the discussion underscores that while core behavioural drivers such as perceived usefulness and trust remain significant, they interact dynamically with regional variables in a city like Bengaluru. Thus, the pathway to digital platform adoption among investors lies in creating a comprehensive, culturally and technologically aligned model—one that recognises the intersection of theoretical rigour with local behavioural realities.

IMPLICATIONS

The findings of this comprehensive review carry significant implications for fintech practitioners, policymakers, and academic researchers working within Bengaluru's digital finance ecosystem. First and foremost, fintech platforms must go beyond basic usability improvements and actively foster trust and risk mitigation through robust data protection policies, clear communication, and transparent algorithmic decision-making. Building credibility will be crucial for sustained investor engagement, especially among new or hesitant users.

For policymakers, the study suggests the need for tailored digital literacy programs and investor protection regulations that reflect the behavioural nuances of urban Indian investors. Policies encouraging standardisation of fintech operations and greater accountability can enhance consumer confidence and promote broader adoption.

In academia, this review reveals a compelling need to develop context-specific behavioural models that integrate cultural, regional, and technological factors unique to markets like Bengaluru. The current gap between generic global models and local investor behaviour suggests fertile ground for future empirical work. Ultimately, recognising and responding to investor psychology, grounded in trust, literacy, usability, and local relevance, will be essential for scaling digital platform adoption in India’s fintech sector.

LIMITATIONS

While this review provides valuable insights into investor behavioural intention toward digital platform adoption in Bengaluru’s fintech sector, several limitations must be acknowledged. Firstly, the study is based solely on secondary data from published literature, which may omit emerging or unpublished findings relevant to the local context. Additionally, most of the reviewed studies are based on generalized national or international samples, limiting their direct applicability to Bengaluru’s unique demographic and economic landscape.

Another limitation is the variation in theoretical frameworks and methodologies used across the studies, which creates challenges in drawing uniform conclusions. Also, given the rapidly evolving nature of fintech, some models and data might not fully capture recent technological advancements or behavioural shifts due to post-pandemic digital acceleration.

Lastly, the review does not include first-hand empirical validation, meaning that the conclusions drawn, while grounded in theory, require primary research to test their applicability within the specific regional ecosystem of Bengaluru. Future studies should include localized, longitudinal data to enhance generalizability and precision.

This comprehensive review underscores the multifaceted nature of investor behavioural intention toward digital platform adoption in Bengaluru’s fintech sector. It reveals that factors such as trust, perceived risk, financial literacy, and usability are critical in shaping investor decisions. Existing theoretical frameworks like TAM, TPB, and UTAUT offer valuable foundations but fall short of fully capturing the regional and cultural nuances specific to Bengaluru. The findings highlight the necessity for a context-sensitive model that integrates both established constructs and local behavioural drivers. Such a model would provide a more accurate understanding of how urban Indian investors interact with digital financial services. In conclusion, advancing fintech adoption in Bengaluru requires a nuanced approach that considers both technological attributes and human behavioural factors. By aligning platform design, regulatory support, and investor education with behavioural insights, the fintech ecosystem can foster deeper trust and broader adoption, ultimately contributing to financial inclusion and innovation in the region.

RECOMMENDATIONS

Based on the review findings, several recommendations can guide stakeholders in enhancing investor adoption of digital platforms in Bengaluru’s fintech sector. Firstly, fintech companies should prioritise trust-building mechanisms such as transparent data policies, strong cybersecurity practices, and user-friendly dispute resolution systems. Trust remains a central determinant of behavioural intention and must be embedded into every stage of the user journey.

Secondly, investor education needs to be strengthened. Initiatives focusing on digital financial literacy, especially among first-time or hesitant users, can reduce perceived risk and improve confidence. Workshops, in-app tutorials, and regional language support can make platforms more accessible and inclusive.

Thirdly, developers should consider personalisation and simplicity in design. Platforms that adapt to user behaviour while remaining intuitive are more likely to drive sustained engagement. Emphasising ease of navigation and clear financial insights can greatly enhance perceived usefulness and user satisfaction.

Additionally, regulators and policymakers should work to establish clear and adaptive policy frameworks that balance innovation with consumer protection. A supportive regulatory environment can reinforce investor confidence and allow fintech firms to innovate responsibly.

Finally, future academic and industry research should focus on developing integrated, context-specific models that combine global theories with regional insights. Bengaluru, as a rapidly growing fintech hub, offers a rich ground for validating and refining behavioural frameworks that can inform practices across similar urban centres in India.

CLOSING THOUGHTS

As Bengaluru’s fintech landscape continues to evolve, understanding investor behaviour is no longer optional—it is essential. This review has shown that digital platform adoption is shaped by a complex interplay of trust, perceived usefulness, risk perception, and regional context. Moving forward, fintech success will depend not just on technological innovation, but on how well platforms align with the behavioural and psychological needs of investors. By grounding strategies in both theory and local insight, stakeholders can foster a more inclusive, confident, and digitally empowered investment community.

ACKNOWLEDGEMENT

• The scholar thanks his guide, Dr. Shilpa Sachdeva, an Associate. Professor and Guide at the School of Management, CMR University, Bengaluru, for all the support and guidance.
• The scholar thanks the Directorate of Research & Innovation (DORI), CMR University, for training and support.
• The scholar thanks the School of Management and CMR University faculty members for extending their support.
• I wholeheartedly express my sincere gratitude to my beloved family members for their constant help, moral support, immense patience, care, prayer, and encouragement, which helped me to complete the study successfully.

Funding

The investigator received no external funding to conduct the research presented in this study.

Conflict of Interest

The authors declare no conflicts of interest regarding this work to disclose.

Author Contributions

As a PhD research scholar, Arun Kumar Sahu conducted the study under the guidance and complete support of Dr. Shilpa Sachdeva, who provided expert advice and oversight throughout the research process.

Ethics Approval

This study was reviewed and approved by the Ethics Committee at the School of Management, CMR University, located at HRBR Layout, Kalyan Nagar, Bengaluru-560043, Karnataka, India. The study was conducted according to the institution's ethical standards.

Data Availability

The datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.

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