The outbreak of the pandemic in 2019 and the ensuing lockdowns redefined the way individuals live, work, and interact. Restrictions on mobility and face-to-face transactions accelerated the adoption of digital technologies across all spheres of daily life, from communication and commerce to banking and insurance. What was initially a forced shift soon evolved into a structural transformation, positioning digital tools as an integral part of financial service delivery. For banks and insurance companies, this disruption presented not only unprecedented challenges but also a critical opportunity to reimagine traditional business models. In particular, the bancassurance sector where banking and insurance services converge was compelled to accelerate digitalisation, integrate innovative technologies, and adopt customer-centric strategies to remain relevant in an increasingly competitive landscape. This transition has laid the foundation for new approaches in financial services, driven by innovation, integration, and the imperative of building stronger, trust-based customer relationships in the digital era. By embracing technological advancements and innovations, they could strengthen digital models and expand their services more effectively. In the case of bancassurance, which combines banking and insurance under one roof, success now depends largely on banks’ ability to maintain strong customer relationships through digital means, making technology the foundation of digitisation and positioning digitised bancassurance as a key driver of growth in the financial services industry (Bhardwaj, 2021). The insurance and financial services sector are experiencing profound transformation. While integration between banking and insurance is not new, it is entering a critical stage. Initially driven by the idea of convergence that encouraged collaboration between banks and insurers, the current focus is on rethinking models of cooperation. This includes different forms of integration ranging from simple alliances and partnerships to full incorporation into a single group. Distribution strategies are also evolving, with banks and insurers increasingly moving beyond isolated products to provide complete financial packages within unified systems. These strategies include traditional bancassurance models as well as newer approaches such as “assure banking,” which inverts the model by placing insurance as the anchor service. Different countries are experimenting with varying models, and their success will depend on alignment with customer preferences (Falautano & Marsiglia, 2003).

One of the major reasons for the rapid growth of bancassurance is the high level of trust customers place in banks. Research indicates that approximately 95% of customers trust their banks, making them more receptive to purchasing insurance products directly through banking channels. Consequently, most customers who buy insurance products do so via their banks, with vehicle and life insurance being among the most widely adopted offerings. However, banks and insurers cannot afford to be complacent. To meet changing customer needs and expectations, they must continually innovate and refine their products, ensuring they retain trust and expand the reach of bancassurance (Alavudeen & Rosa, 2015). From a banking perspective, offering insurance products presents clear financial benefits. Bancassurance helps diversify revenue streams, reducing reliance on traditional interest margins. The distribution of insurance is cost-efficient, especially when existing employees handle sales, and it involves lower capital requirements compared to risks assumed in other banking activities, enabling income generation with reduced exposure. Customers also benefit by accessing a wide range of services at a single point. Whether paying premiums, repaying loans, or receiving life insurance benefits, everything can be conveniently managed through a bank branch or even at an ATM (Molleli, 2020).

Simultaneously, the global financial system is entering the era of Finance 4.0, powered by technologies such as distributed ledger systems, blockchain-based smart contracts, machine learning, and predictive data analytics. These tools are revolutionising financial services by reducing costs, improving risk management, enhancing fraud detection, and simplifying compliance processes. For customers, they provide 24/7 access to personalised products and services, from investment advice to tailored insurance policies. Leveraging big data and advanced computing, companies can design real-time customised solutions that align more closely with individual needs (George, 2024). The digitalisation of the insurance business has also restructured how it is organised and delivered, affecting products, processes, and the tools employed. Key areas of focus include the role of data and the technologies enabling its use, alongside changes in the value creation chain and business models. In the new digital landscape, the insurance value chain often no longer follows a sequential form (Monkiewicz & Monkiewicz, 2023). Moreover, the competitive environment is shifting rapidly. FinTech companies are introducing new models, innovations, and services that challenge traditional banks and insurers. Today, these institutions compete not only with each other but also with agile, tech-driven start-ups that are reshaping the market by offering creative financial solutions. These forces established players to adapt quickly to avoid being left behind (Mehdiabadi et al., 2022).

Figure 1 Progression and maturity stages of bancassurance

Source: Authors contribution

At the foundation of bancassurance lies the conventional model, where banks distributed insurance products primarily through physical branches, face-to-face interactions, and manual paperwork. This approach was limited in reach, slow in processing, and heavily dependent on branch networks. The next stage reflected a transitional phase, where traditional bancassurance practices were supplemented with basic technological tools. This included early digital adoption such as online portals, call centres, and initial automation of back-end processes. Although more efficient than the base layer, this stage still retained strong reliance on manual operations. The apex of the bancassurance pyramid represents the current and future stage, driven by Insurtech innovations such as Artificial Intelligence (AI), Blockchain, Chatbots, Internet of Things (IoT), and advanced data analytics. This digital transformation has given rise to a customer-centric, fully digital, and scalable bancassurance model that offers personalized products, seamless integration, faster claims settlement, and broader financial inclusion.

Despite the opportunities, several challenges remain, particularly for insurance companies. A major issue is dealing with legacy information systems, as many insurers continue to rely on outdated databases and platforms, making it difficult to integrate new technologies smoothly. The key challenge lies in ensuring that old information can be effectively utilized to guide future decisions. Additionally, regulatory frameworks further complicate the adoption of advanced technologies. For instance, in Europe, artificial intelligence is subject to strict EU legislation, and solutions deemed “high-risk” under these rules become more expensive and difficult to implement, creating barriers for insurers seeking to adopt cutting-edge innovations (Vuohelainen, 2024). Moreover, future collaborators such as banks, GIC, and LIC continue to face a severe lack of IT culture. Although some progress has been made, this shift is both late and insufficient. Another disadvantage lies in the inflexibility of insurance products, which often cannot be tailored to the unique needs of consumers. Flexibility and adaptability are critical for bancassurance to flourish, as customers are more likely to engage with products that align with their requirements (Tyagi, 2021).

The persistent endeavour to scout for new technologies, innovative products, superior services, and fresh avenues of business generation has therefore become essential not only for the growth but also for the sustainability of the global banking system. In India, the challenge is further magnified by differences in working styles and cultures between commercial banks and insurance companies. A vast majority of banking operations are still carried out manually due to incomplete automation, unlike in many developed countries. This gap underscores the urgent need for digital transformation and closer alignment between banking and insurance to ensure long-term competitiveness and resilience.

Innovation in Bancassurance

AI and Machine Learning

Recent studies have explored how Artificial Intelligence (AI) is transforming the insurance and bancassurance industries through automation, predictive modelling, and enhanced customer engagement. (Almubarak, Elmubarak and Salim Babiker, 2024) demonstrate how underwriting in Saudi insurance companies, particularly car insurance, can be optimized through AI-driven predictive models that evaluate claims frequency, demographic factors, and vehicle types. By automating underwriting and claims processes, insurers can reduce bias, fraud, and errors while fostering consumer trust. Similarly, (Rao & Soofastaei, 2025) analyse successive digital waves in insurance, highlighting the integration of AI, machine learning, and big data in claims processing, risk management, and fraud detection, while also addressing ethical implications of digital transformation. From a consumer perspective, (Iqbal & Jan, 2025) emphasize AI-driven marketing analytics in bancassurance, illustrating how predictive models can enhance customer loyalty through better segmentation, personalized engagement, and retention strategies. (Kumar, 2024) provides a comprehensive review of machine learning applications in actuarial science, focusing on risk analysis, claims estimation, and premium determination while synthesizing findings from over seventy studies to map technical challenges and future opportunities. In the context of bancassurance, (Suresh & Monalisa, 2025) reveal how AI enhances digitalization and customer experience by offering tailored recommendations, automating underwriting, and improving decision-making, with empirical evidence from Chennai. Extending this perspective, (Loh & Soo, 2023) highlight AI opportunities across insurance functions including underwriting, sales, and lifestyle services, stressing the importance of data integration, regulatory compliance, and governance for successful adoption. Collectively, these studies underscore AI’s transformative role in shaping sustainable, consumer-centric insurance ecosystems.

(Clement, 2025) emphasizes blockchain’s potential in fraud prevention through transparent ledgers, smart contracts, and secure identity verification, ensuring greater trust in insurance transactions. Similarly, (Trivedi, 2023) suggests a blockchain-based framework to improve efficiency, customer experience, and fraud reduction in the insurance sector. (Tarr, 2018) also underscores blockchain’s role in enhancing data quality, transparency, and fraud detection, though he warns of challenges such as governance, privacy risks, and scalability. In the context of bancassurance, (Verma & Kansra, 2022) stress the need for a customer-centric approach, combining digital and physical channels to enhance market reach. Further, (Verma, Kansra & Mahapatra, 2024) discuss blockchain’s advantages in bancassurance, including smart contracts and faster claim settlements, while acknowledging adoption challenges. Collectively, these studies reveal blockchain as a transformative tool for insurance and bancassurance, despite significant implementation barriers.

Conversational AI & Chatbots

(Yadav, Yadav & Nghiem, 2025) highlight how conversational AI enhances claims processing by improving efficiency, reducing costs, and boosting customer satisfaction through real-time support and personalized interactions. While automation accelerates resolution and reduces human error, challenges related to privacy, data security, and empathetic responses remain, with future advancements expected from integration with blockchain and IoT. Complementing this, (Mkass, 2024) explores customer perceptions of chatbots and AI-driven fraud detection in financial services, revealing that consumers value instant assistance and 24/7 availability, though concerns persist regarding privacy, transparency, and false flagging in fraud detection. Similarly, (Woger & Beinhauer) investigate chatbot limitations using a mixed-methods approach with Generation Z, emphasizing expectations of fast, accurate, and personalized services. Their findings suggest that trust, perceived usefulness, and ease of use strongly influence acceptance, and propose hybrid models where chatbots handle routine tasks while complex queries are transferred to human agents. From a broader perspective, (Malempati et al.,2023) focus on the financial and insurance ecosystems, identifying how Insurtech, automation, and digital trust services shape evolving risk management strategies and reinsurance markets. This work underscores the importance of scalable, autonomous systems and digital platforms in enhancing efficiency and stakeholder trust. Meanwhile, (Bokolo & Daramola, 2024) extend the discourse by highlighting security vulnerabilities in insurance chatbots, particularly risks related to spoofing, tampering, and privilege escalation, reinforcing the need for robust security frameworks in AI adoption. Collectively, these studies illustrate both the opportunities and limitations of conversational AI in advancing insurance innovation while safeguarding consumer trust.

The insurance industry is undergoing rapid digital transformation, driven by customer expectations for efficiency, personalization, and convenience. Subhashini et al. highlight the role of AI-powered chatbots in automating customer service, streamlining claim processes, and enhancing policy guidance through NLP and machine learning, thereby improving customer satisfaction and reducing operational costs. Similarly, (Patil, Kulkarni & Hudnurkar, 2024) emphasize the importance of humanoid chatbots, showing that anthropomorphism boosts optimism and innovativeness but raises concerns of insecurity, suggesting that customer readiness significantly affects adoption. (Pareek, 2024) extends this by proposing a comprehensive testing framework to ensure chatbot reliability, compliance, and empathetic engagement in life insurance. Broader digital strategies also play a critical role (Dalla Pozza, 2024) underscores the value of omnichannel delivery in creating trust, service integration, and reduced customer effort, while (Singh & Chavan, 2020) discuss the evolution of online insurance distribution in India, noting persistent consumer scepticism despite growing adoption. (Desikan & Devi, 2021) further argue that digital transformation enhances operational efficiency and customer experience, positioning insurers to stay competitive. Collectively, these studies reveal that AI chatbots, omnichannel integration, and digital platforms are reshaping insurance, though challenges of trust, compliance, and customer acceptance remain central.

Integration of Insurtech and Bancassurance

The rapid integration of digital technologies has significantly transformed insurance and financial services, with embedded finance and Insurtech driving major shifts. (Luca, 2025) emphasizes that embedded finance, enabled through APIs, cloud computing, and open banking, integrates financial services seamlessly into non-financial platforms such as e-commerce and ride-hailing apps. While it provides convenience and innovation, it also raises concerns around data privacy, cybersecurity, and regulatory compliance, underscoring the need for robust governance and standardized APIs. In the insurance sector, (Tian, Todorovic & Todorovic, 2023) introduce a novel three-stage machine learning-based system to improve customer identification and cross-selling strategies, demonstrating superior predictive accuracy and business efficiency compared to baseline models. Complementing this, (Shi, 2025) explores multi-channel marketing in property insurance, showing how combining online and offline channels enhances customer acquisition, conversion, and loyalty, particularly when powered by AI, big data, and CRM systems. Broader structural changes in the industry are captured by (Stoeckli, Dremel & Uebernickel, 2018), who develop a grounded model of Insurtech innovations based on over 200 cases, revealing 14 transformational capabilities that disrupt traditional value creation and highlight the role of digital intermediaries. Similarly, (Scardovi, 2017) notes that while insurance weathered the global financial crisis more easily than banking, digital disruptions now pose unprecedented threats, requiring radical rethinking of business models. (Kaswan et al., 2022) stress how big data innovations enhance risk management and fraud detection, particularly in emerging economies. Finally, (Holland & Kavuri, 2024) contrast how new entrants exploit AI and big data to deliver innovative products, while incumbents adopt more defensive digital strategies, illustrating divergent pathways of digital transformation in insurance.

Customer-Centricity as the Core

The insurance industry is witnessing a profound transformation under the influence of Insurtech, digital innovation, and customer-centric strategies. (Kaur & Singh, 2025) emphasize that the adoption of digital technologies in the era of IR 4.0 has significantly improved customer satisfaction in life insurance, with online distribution and customer service management emerging as key predictors. Similarly, (Tikone & Patil, 2024) identify AI, blockchain, IoT, and data analytics as the core drivers of Insurtech, highlighting that these innovations enhance underwriting accuracy, claims management, and personalization. Their findings suggest that both technological adoption and regulatory support positively influence user satisfaction. (Sosa & Montes, 2022) take a broader perspective, identifying five driving capabilities and 15 types of innovations through an analysis of 150 Insurtech, illustrating how three waves of Insurtech innovation have reshaped the insurance sector into a dynamic, user-centric ecosystem. Beyond technological transformation, scholars stress the importance of customer-centricity for competitiveness. (Alli, 2025) finds that customer-centric innovation enhances competitive advantage in Nigerian insurance, particularly through customer engagement and service responsiveness. Similarly, (Oyomo, 2019) underscores that customer life cycle practices and customer experience strongly influence competitive intelligence in Kenyan firms. (Iddris, Dogbe & Kparl, 2023) further reveal that customer-centricity moderates the link between employee innovativeness and competitiveness, suggesting that leadership, self-efficacy, and customer focus are intertwined in driving organizational success.

Case-based insights also highlight practical transformations. (Vliet & Meer, 2023) document Aegon’s transition from a product-oriented to a customer-centric organization through radical business process changes, social media integration, and cloud-based systems, showcasing how cultural and technological shifts enable service excellence. Samuel stresses the strategic role of microservices in building user-centric interfaces, omnichannel models, and adaptive insurance ecosystems, while (Moodley, Vermaak & Govender, 2019) highlight the role of collaborative leadership in ensuring sustainable customer-centric transformation despite environmental volatility. (Babu & Babu, 2016) remind that customer engagement remains a cornerstone of insurance success, though achieving customer-centricity requires overcoming structural and cultural challenges. Collectively, these studies demonstrate that Insurtech and customer-centric innovation, reinforced by leadership and organizational agility, are reshaping insurance into a technologically advanced and user-centered industry, enhancing satisfaction, competitiveness, and long-term sustainability.

Opportunities of Insurtech-Enabled Bancassurance

The innovation in technology is not limited to some specific areas; its scope has a widespread reach and Bancassurance is also a service which can be highly benefitted from technological advancement. Bancassurance is an arrangement between banks and insurance companies for selling of insurance products through banks. Its success is heavily reliant on banks maintaining excellent customer relationships with the help of technological advancement.

Insurtech has a tremendous impact on risk assessment activities. Given, the increasing availability of data (e.g., risk data and customer’s behaviour data), data can be exploited to assess risks more precisely and accurately. For example, driving behaviour data may be gathered using driving recorders attached to cars (e.g., AXA Drive Recorder) and with location-based apps on the customer’s smartphone (e.g., Kroodle) Aside from increased efficiency in claims submissions, digital service provisioning provides transparent and timely status updates of claims and policies. Policies are either digitized or the corresponding details are made available digitally, thus, providing customers with possibilities to have an overview of their policies, to query the covered benefits and to make policy adjustments (Stoeckli, 2018). differentiation occurs through highly customized insurance products and coverage of insurance niches. As such, understanding customer needs and developing products and services accordingly offers opportunities to achieve competitive advantages through differentiation.

The Online Insurance Market in India Market size in terms of premium value is expected to grow from USD 2.09 billion in 2025 to USD 3.71 billion by 2030, at a CAGR of 12.2% during the forecast period (2025-2030, Mordor intelligence report on insurance-market-in-India, 2025)

Challenges and Risks of Insurtech-Enabled Bancassurance

(Koprivica M., 2018) Entrance of Insurtech innovators to the insurance market imposes distinct challenges for traditional insurance companies. Faced by technology-led disruption, incumbents are under increasing pressure to evolve and reinvent their business processes and attitude toward customers (Cernit, Moroi & Margineanu,2024) One of the most significant emerging risks is climate change.

The increasing frequency and intensity of natural disasters, such as floods, storms and forest fires, directly affect the insurance sector, in particular through increased claims requirements and increased financial risks. Increasingly stringent environmental regulations also add additional pressure on insurance companies, which need to adjust their portfolios and adopt more sustainable practices. In this regard, there is increasing emphasis on developing insurance products that reflect environmental risks and on responsible investment strategies. Another major risk is cybersecurity. In the context of the accelerated digitalization of financial services, insurance companies are becoming increasingly attractive targets for cyber-attacks, given the large volume of sensitive data they manage. Cyber fraud and data breaches can affect not only the reputation of insurers, but also their financial stability. In this regard, data protection and investments in cybersecurity are becoming fundamental priorities for insurance companies, which need to develop effective solutions for preventing and managing cyber risks. the insurance sector must also cope with economic and geopolitical risks. Global economic instability, financial crises, inflation and currency fluctuations can directly affect the activity of insurance companies, causing them to adjust their pricing strategy and diversify their portfolios.

(Braun & Jia, 2025) it should focus on the transformative potential of data and advanced analytics in gaining deeper customer insights, both in the context of life and health as well as P&C insurance. Wearables, telematics devices, and smart home sensors generate vast amounts of data that can enable insurers to design personalized coverage and preventative measures tailored to individual behaviours and needs. , the integration of IoT data into insurance raises critical privacy concerns, making it a vital area for academic investigation the emergence of blockchain technology introduces opportunities for disintermediation, promising to streamline processes and reduce reliance on intermediaries.

(Lin & Chen, 2020) The accuracy of data should always be a concern. Any bias in the data could affect the validity of a model, algorithm and outcome and, hence, the outputs of a trained system data dependence come at a price. Data presents many opportunities for Insurtech companies, but an ever-growing reliance on data means they must also manage a new form of risk: data veracity. Inaccurate, biased, or manipulated information threatens to compromise the accuracy of insights used by insurance companies to plan, operate and grow their businesses. An unfavourable regulatory environment can be a significant barrier to entry for Insurtech newcomers and onerous regulatory requirements may lead to a slow, uphill and capital-intensive burnout for these start-ups.

Research Questions -

1. a) How does Insurtech-driven innovation transform traditional bancassurance models?
2. b) What integrated conceptual framework can be developed to connect innovation, integration, and customer centricity in order to address the missing link in existing bancassurance research?

Research Gap

Figure 2 Gap Analysis Diagram

Bancassurance has evolved considerably over the past three decades, transitioning from a traditional, branch-based distribution model to a hybrid and now digitally enabled framework. Existing literature highlights the benefits of bancassurance in expanding insurance penetration, enhancing revenue streams for banks, and improving customer convenience (Verma & Kansra, 2022). Parallelly, Insurtech studies emphasize the transformative role of technologies such as artificial intelligence, blockchain, and IoT in digitalizing insurance services, streamlining claims, and improving transparency (Almubarak et al., 2024; Clement, 2025; Kaur & Singh, 2025).

However, most research treats bancassurance and Insurtech as separate domains, with limited focus on their convergence and the resulting transformation of financial services. Specifically, gaps exist in understanding how Insurtech-driven innovation can restructure bancassurance beyond traditional product bundling toward more customer-centric, personalized solutions. While several studies have examined AI in underwriting (Kumar, 2024; Suresh & Monalisa, 2025), blockchain in fraud prevention (Trivedi, 2023; Verma et al., 2024), and chatbots in customer support (Yadav et al., 2025), empirical evidence on their integrated application within bancassurance ecosystems remains underexplored. Furthermore, research on digital bancassurance often emphasizes operational efficiency, but relatively fewer studies address its implications for financial inclusion, especially in underserved and rural populations where mobile insurance could bridge protection gaps. Another underdeveloped area is the customer-centric paradigm in digital bancassurance. While studies stress personalization, omnichannel delivery, and customer engagement (Pozza, 2024; Alli, 2025), they seldom examine how combining technological innovation with integration strategies fosters trust, transparency, and long-term sustainability in bancassurance. Additionally, issues of regulatory complexity, data privacy, and cybersecurity risks though widely recognized (Cernit et al., 2024; Lin & Chen, 2020) require deeper investigation in the specific context of digital bancassurance models. Thus, the existing body of work leaves a significant gap in developing a conceptual framework that unites innovation, integration, and customer-centricity to explain how Insurtech-enabled bancassurance can enhance service delivery, financial inclusion, and sustainable competitiveness in a digital economy.

Objectives of the study

• To examine how Insurtech-driven innovations are transforming traditional bancassurance models.
• To develop an integrated conceptual review of innovation, integration, and customer centricity in bancassurance.

Conceptual Framework

Figure 3 Conceptual Framework

Implications for Practice and Policy

The study enriches the existing body of knowledge by integrating Insurtech innovations with the traditional bancassurance framework, offering a new conceptual understanding that merges financial services with advanced technology. It highlights how innovation, integration, and customer-centricity function as pillars that redefine bancassurance beyond distribution into a strategic, digital-first ecosystem. By focusing on customer-centricity, the study contributes to sustainability literature, positioning bancassurance as a tool for broader financial inclusion and social security, particularly in emerging economies. The study links Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) frameworks with customer adoption of Insurtech-driven bancassurance, emphasizing trust, personalization, and convenience as critical determinants of acceptance.

Banks and insurers should adopt Insurtech solutions (AI, blockchain, IoT, chatbots, and big data analytics) to streamline processes, enhance claims management, and deliver seamless customer experiences. Managers must prioritize personalized products, proactive communication, and integrated financial planning tools to build stronger trust and loyalty. The shift should be from a product-push approach to a solution-driven approach. The findings suggest that banks and insurers should co-create digital platforms that enable end-to-end services (from policy issuance to claim settlement), ensuring ease of access and operational efficiency. Insurtech-enabled bancassurance can help banks target underserved and rural populations with micro-insurance and on-demand products, improving both social impact and revenue streams.

This conceptual study demonstrates that the convergence of bancassurance and Insurtech has the potential to fundamentally reshape the delivery of financial services. By tracing the transformation from traditional branch-based models to digital ecosystems, the study highlights how emerging technologies such as artificial intelligence, blockchain, IoT, and conversational AI can enhance bancassurance practices. These innovations extend beyond efficiency improvements to foster personalization, transparency, and accessibility, positioning bancassurance as a customer-centric, digitally enabled ecosystem.

The framework developed in this study anchored in innovation, integration, and customer-centricity addresses a critical research gap by offering a holistic lens through which to understand Insurtech-enabled bancassurance. It illustrates that successful digital bancassurance relies not only on technological adoption but also on the seamless integration of banking and insurance systems to ensure a unified customer journey. More importantly, it underlines that the ultimate goal of these advancements should be enhanced customer experience and broader financial inclusion, particularly for underserved populations who stand to benefit most from digital financial solutions. At the same time, the study recognizes challenges such as regulatory complexities, data privacy concerns, cybersecurity risks, and the digital divide, which can hinder the realization of these opportunities. For bancassurance to achieve sustainable growth, stakeholders including banks, insurers, regulators, and technology providersmust collaborate to design responsible frameworks that balance innovation with consumer protection.

Looking forward, the integration of Insurtech into bancassurance has the potential to move beyond efficiency gains toward transformative financial inclusion, offering affordable, transparent, and tailored insurance solutions. If carefully managed, digital bancassurance could become a cornerstone of sustainable financial ecosystems in the digital economy.

Future Recommendation

The study of Insurtech-enabled bancassurance opens new avenues for both academic research and practical implementation. For future research, the conceptual framework of innovation, integration, and customer-centricity can be empirically tested across different regions and customer segments. Scholars may explore adoption patterns, the role of digital literacy, and the impact of Insurtech-driven bancassurance on financial inclusion, particularly in rural and underserved markets. Longitudinal studies could also assess how evolving technologies such as generative AI, blockchain-based smart contracts, and embedded finance platforms reshape customer trust and long-term engagement.

From a practical perspective, the findings suggest that banks and insurers need to invest in seamless digital platforms, data-driven personalization, and robust cybersecurity systems. Policymakers and regulators must anticipate emerging risks by creating adaptive regulatory frameworks that balance innovation with consumer protection and ethical AI practices.

1. Alavudeen, R., & Rosa, K. D. (2015). Growing role of bancassurance in banking sector. Bonfring International Journal of Industrial Engineering and Management Science, 5(2), 10–16. https://doi.org/10.9756/BIJIEMS.8072
2. Almubarak Ali, M. A., Elmubarak, Y. A., & Salim Babiker, M. A. (2024). The role of artificial intelligence in risk management and underwriting optimization in the insurance industry. Pakistan Journal of Life and Social Sciences, 22(2), 90–100.
3. Babu, R. H., & Babu, N. G. (2016). Customer engagement in insurance: A journey to enhance customer relationships. Primax International Journal of Marketing, 5(1), 65–72.
4. Bhardwaj, G. (2021, November). Analysis of digitization, IoT and blockchain in bancassurance. In 2021 International Conference on Technological Advancements and Innovations (ICTAI) (pp. 506–509). IEEE. https://doi.org/10.1109/ICTAI53825.2021.9643203
5. Bokolo, Z., & Daramola, O. (2024). Chatbots security: STRIDE-based elicitation of security threats and vulnerabilities in insurance chatbots. Information Systems Frontiers. Advance online publication. https://doi.org/10.1007/s10796-024-10506-2
6. Braun, A., & Jia, R. (2025). InsurTech: Digital technologies in insurance. The Geneva Papers on Risk and Insurance – Issues and Practice, 50(1), 1–7. https://doi.org/10.1057/s41288-024-00354-4
7. Cernit, R., Moroi, T., & Margineanu, A. (2024). Emerging risks and strategic challenges in the insurance sector. Journal of Accounting and Management, 14(3), 52–61.
8. Clement, M. (2025). The role of blockchain in fraud prevention in life insurance. International Journal of Blockchain and Applications, 3(1), 44–55.
9. Dalla Pozza, I. (2024). Creating customer value through omnichannel service delivery: A study of the French insurance market. Journal of Financial Services Marketing, 29(2), 392–405. https://doi.org/10.1057/s41264-024-00195-2
10. Desikan, J., & Devi, A. J. (2021). Digital transformation in Indian insurance industry – A case study. International Journal of Case Studies in Business, IT, and Education, 5(2), 184–196. https://doi.org/10.47992/IJCSBE.2581.6942.0119
11. Falautano, I., & Marsiglia, E. (2003). Integrated distribution of insurance and financial services and value creation: Challenges ahead. The Geneva Papers on Risk and Insurance – Issues and Practice, 28(3), 481–494. https://doi.org/10.1111/1468-0440.00272
12. George, A. S. (2024). Finance 4.0: The transformation of financial services in the digital age. Partners Universal Innovative Research Publication, 2(3), 104–125.
13. Holland, C. P., & Kavuri, A. S. (2024). InsurTech strategies: A comparison of incumbent insurance firms with new entrants. The Geneva Papers on Risk and Insurance – Issues and Practice, 50(1), 78–98. https://doi.org/10.1057/s41288-024-00356-2
14. Iddris, F., Dogbe, C. S. K., & Kparl, E. M. (2023). Transformational leadership, employee self-efficacy, employee innovativeness, customer-centricity, and organizational competitiveness among insurance firms. International Journal of Innovation Science, 15(5), 756–775. https://doi.org/10.1108/IJIS-01-2023-0015
15. Iqbal, M. N., & Jan, M. T. (2025). AI-powered business strategies for enhancing consumer behavior and brand loyalty in the bancassurance sector. In M. K. Malik & A. S. Qureshi (Eds.), Elevating brand loyalty with optimized marketing analytics and AI (pp. 101–132). IGI Global. https://doi.org/10.4018/9781668478950
16. Kaswan, K. S., Dhatterwal, J. S., Sharma, H., & Sood, K. (2022). Big data in insurance innovation. In S. S. Gill, A. Bala, & A. Shukla (Eds.), Big Data: A game changer for insurance industry (pp. 117–136). IGI Global. https://doi.org/10.4018/9781799895962
17. Kaur, P., & Singh, M. (2025). Exploring the impact of InsurTech adoption in Indian life insurance industry: A customer satisfaction perspective. The TQM Journal, 37(2), 457–483. https://doi.org/10.1108/TQM-06-2023-0182
18. Koprivica, M. (2018). InsurTech: Challenges and opportunities for the insurance sector. In Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture (pp. 619–624). Atlantis Press. https://doi.org/10.2991/icatema-18.2019.129
19. Kumar, S. (2024). Applications of machine learning in actuarial pricing and underwriting – A review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4993732
20. Lin, L., & Chen, C. (2020). The promise and perils of InsurTech. Singapore Journal of Legal Studies, 2020(1), 115–137.
21. Malempati, M., Pandiri, L., Paleti, S., & Singireddy, J. (2023). Transforming financial and insurance ecosystems through intelligent automation, secure digital infrastructure, and advanced risk management strategies. Journal of Financial Innovation, 7(4), 211–230.
22. Mehdiabadi, A., Shahabi, V., Shamsinejad, S., Amiri, M., Spulbar, C., & Birau, R. (2022). Investigating Industry 5.0 and its impact on the banking industry: Requirements, approaches and communications. Applied Sciences, 12(10), 5126. https://doi.org/10.3390/app12105126
23. Monkiewicz, J., & Monkiewicz, M. (2023). Digitalisation of insurance: New values, new challenges. In J. Monkiewicz & M. Monkiewicz (Eds.), The digital revolution in banking, insurance and capital markets (pp. 131–143). Routledge. https://doi.org/10.4324/9781003356754
24. Moodley, T., Vermaak, A., & Govender, K. (2019). Evaluating leadership collaboration within an emerging customer-centric insurance organisation. Journal of Banking, Insurance and Management Sciences, 25(1), 55–70.
25. Oyomo, A. A. (2019). Customer centricity and competitive intelligence performance in the insurance industry in Western Kenya, East Africa. European Journal of Business and Management, 11(10), 62–75.
26. Pareek, C. S. (2024). Beyond automation: A rigorous testing framework for reliable AI chatbots in life insurance. Language, 4(2), 122–135.
27. Patil, K. P., Kulkarni, M. S., & Hudnurkar, M. (2024). Enhancing service quality in the insurance industry with AI-powered humanoid chatbots. The TQM Journal, 36(5), 913–928. https://doi.org/10.1108/TQM-07-2023-0200
28. Popli, G. S., & Popli, R. (2015). Bancassurance business opportunities, problems and challenges in India. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2570484
29. Rao, A. S., & Soofastaei, A. (2025). Artificial intelligence in insurance: Transforming risk management and customer experience. In Advanced analytics for Industry 4.0 (pp. 309–324). CRC Press. https://doi.org/10.1201/9781003306827
30. Scardovi, C. (2017). Transformation in insurance. In Digital transformation in financial services (pp. 163–185). Springer. https://doi.org/10.1007/978-3-319-66945-0_8
31. Shi, W. (2025). Impact of multi-channel marketing on property insurance sales performance. Economics and Management Innovation, 2(2), 8–14.
32. Singh, R. K., Singh, A., & Chavan, S. (2020). Distribution channels in life and general insurance: A conceptual analysis. Studies in Indian Place Names, 40(27), 590–609.
33. Sosa, I., & Montes, Ó. (2022). Understanding the InsurTech dynamics in the transformation of the insurance sector. Risk Management and Insurance Review, 25(1), 35–68. https://doi.org/10.1111/rmir.12198
34. Stoeckli, E., Dremel, C., & Uebernickel, F. (2018). Exploring characteristics and transformational capabilities of InsurTech innovations to understand insurance value creation in a digital world. Electronic Markets, 28(3), 287–305. https://doi.org/10.1007/s12525-018-0304-7
35. Suresh, A., & Monalisa, M. A. (2025). Proximate determinants of artificial intelligence acceptance on bancassurance growth and management in India. Journal of Finance, Accounting and Management, 16(1), 1–11.
36. Tarr, J. A. (2018). Distributed ledger technology, blockchain and insurance: Opportunities, risks and challenges. Insurance Law Journal, 29(3), 254–268.
37. Tian, X., Todorovic, J., & Todorovic, Z. (2023). A machine-learning-based business analytical system for insurance customer relationship management and cross-selling. Journal of Applied Business and Economics, 25(6), 65–76.
38. Tikone, A. R., & Patil, A. (2024). Transforming insurance landscapes: Exploring user adoption and user satisfaction in the era of InsurTech. Future Proofing Business, 5(2), 120–136.
39. Trivedi, S. (2023). Blockchain framework for insurance industry. International Journal of Innovation and Technology Management, 20(6), 2350034. https://doi.org/10.1142/S0219877023500347
40. Tyagi, A. (2021). Bancassurance in India: Issues and challenges. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3980539
41. van Vliet, R., & Meer, J. T. (2023). From product-oriented insurance company to customer-centric service provider. In Digital enterprises: Service-focused, digitally-powered, data-fueled (pp. 33–51). https://doi.org/10.1007/978-3-031-18418-6_3
42. Verma, D., Kansra, P., & Mahapatra, S. K. (2024). Economic impact of perceptible benefits and adverse sides of blockchain in bancassurance along with cybersecurity. In G. Kaur, N. N. Dalei, S. K. Mahapatra, & V. Kandpal (Eds.), Cybersecurity, law, and economics: The case of India (pp. 91–102). Routledge.
43. Vuohelainen, R. (2024). Artificial intelligence (AI) and robotic process automation (RPA) in the insurance business [Master’s thesis, Centria University of Applied Sciences]. Theseus. https://urn.fi/URN:NBN:fi:amk-2024121937704
44. Woger, M., & Beinhauer, M. D. R. (2016). The future of customer service chatbots in the Austrian finance and insurance industry.
45. Yadav, R., Yadav, M., & Nghiem, X. H. (2025). The influence of conversational AI on enhancing customer satisfaction in insurance claims handling. In P. M. Kumar (Ed.), Intersecting natural language processing and FinTech innovations in service marketing (pp. 489–504). IGI Global. https://doi.org/10.4018/9781668492611.ch025
46. Моллели, Т. С. (2020). Bancassurance as an effective tool for promoting insurance penetration and creation of insurance services awareness in Tanzania. In Digital Finance 2020 (DF2020) (pp. 270–284). Moscow: Financial University.
47. Babu, R. H., & Babu, N. G. (2016). Customer engagement in insurance: A journey to enhance customer relationships. Primax International Journal of Marketing (PIJM), 2(2016), Article/Issue 2.
48. Clement, M. (2025). The role of blockchain in fraud prevention in life insurance.
49. George, A. S. (2024). Finance 4.0: The transformation of financial services in the digital age. Partners Universal Innovative Research Publication, 2(3), 104–125.
50. Kaur, N., & Kaur, R. (n.d.). Revolution in bancassurance business: A study on its digital model.
51. Lin, L., & Chen, C. (2020). The promise and perils of InsurTech. Singapore Journal of Legal Studies, (2020), 115–142.
52. Luca, C. (2025). Risks, regulatory challenges, and the future outlook.
53. Malempati, M., Pandiri, L., Paleti, S., & Singireddy, J. (2023). Transforming financial and insurance ecosystems through intelligent automation, secure digital infrastructure, and advanced risk management strategies. Educational Administration : Theory & Practice, 29(4), 4777–4793.
54. Mkass, N. (2024). AI integration in the financial industry: Customer perspectives on chatbots and fraud detection mechanisms. Master’s thesis / conference paper.
55. Samuel, A. (n.d.). Microservices and customer-centric digital insurance experiences. Unpublished manuscript / ResearchGate posting. Retrieved from ResearchGate.
56. Suresh, A., & Monalisa, M. A. (2025). Proximate determinants of artificial intelligence acceptance on bancassurance growth and management in India. Journal of Finance, Accounting and Management, 16(1), 1–11.
57. Tarr, J. A. (2018). Distributed ledger technology, blockchain and insurance: Opportunities, risks and challenges. Insurance Law Journal, 29(3), 254–268.
58. Tian, X., Todorovic, J., & Todorovic, Z. (2023). A machine-learning-based business analytical system for insurance customer relationship management and cross-selling. Journal of Applied Business & Economics, 25(6), 65–76.
59. Tikone, A. R., & Patil, A. (2024). Transforming insurance landscapes: Exploring user adoption and user satisfaction in the era of InsurTech. In Future Proofing Business.
60. Woger, M., & Beinhauer, M. D. R. (n.d.). The future of customer service chatbots in the Austrian finance and insurance industry. Unpublished report / manuscript.
61. Molleli, T. S. (2020). Bancassurance as an effective tool for promoting insurance penetration and creation of insurance services awareness in Tanzania. In Digital Finance 2020 (DF2020) (pp. 270–284). Proceedings of DF2020.