Volume 11 (2026-27)

In the fast-paced world of digital banking, the ability to modernise legacy systems while preserving operational resilience is essential. Financial institutions across the United Kingdom and Europe are increasingly confronted with ageing technology that, while historically reliable, now poses challenges in integration, cybersecurity and agility. This paper examines the intricacies of legacy system modernisation, including when to upgrade or retain legacy components, and strategies for achieving a balanced, risk-based transformation. Drawing on examples from major institutions and recent regulatory guidance, it offers practical insights for decision makers committed to technological renewal without compromising stability. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: legacy system modernisation; operational resilience; digital transformation; technical debt management; financial services technology

The value chain within the banking and payments sector of the European Union (EU) is undergoing a profound transformation, driven by digitalisation, the proliferation of innovative platforms and the emergence of new business models. As a result, financial institutions are increasingly turning to third parties for the marketing and distribution of financial services, leading to greater fragmentation and specialisation in the sector. Among these developments, white labelling has emerged as a widespread business model, allowing regulated firms to distribute products and services under the brand of (often) nonfinancial partners. According to recent data from the European Banking Authority, over a third of European banks utilise white labelling arrangements. White labelling presents numerous advantages, including cost reduction, expanded service offerings and enhanced financial inclusion, thereby fostering competition within the industry. The model, however, introduces new complexities, increasing operational and compliance risks and raising potential challenges for consumer protection and proper supervision. In particular, supervisory authorities face the challenge of overseeing these increasingly fragmented value chains and ensuring effective regulatory convergence across EU member states. The traditional boundaries between regulated institutions, technology firms and nonfinancial entities are dissolving, forcing supervisors to adapt their practices. This paper explores how these trends are fragmenting traditional value chains, enabling both incumbent financial institutions and nonregulated entities, including FinTechs and BigTechs, to enter the market and offer financial services and products in the EU. The paper focuses in particular on white labelling: it presents use cases, benefits and risks and analyses the resulting supervisory challenges. This article is also included in ‘The Business & Management Collection’, which can be accessed at https://hstalks.com/business/.
Keywords: innovation; white labelling; digital finance; payments

This paper explores the transformative potential of agentic artificial intelligence (AI) — autonomous, goal-driven artificial intelligence systems — within the banking sector. Building on the widespread adoption of generative AI (GenAI) as a standard tool for content creation and summarisation, the paper examines how agentic AI represents the next evolutionary step: moving from reactive assistance to proactive, autonomous execution of complex workflows. It outlines the crucial differences between GenAI and agentic AI, emphasising the latter’s ability to plan, coordinate and make decisions with minimal human input. The paper provides a comprehensive overview of agentic AI’s capabilities, its autonomy spectrum and its growing adoption across industries, with banking, financial services and insurance leading the way. Practical examples illustrate how agentic AI can transform processes such as loan approvals, fraud detection and compliance checks, while multi-agent systems enable collaborative automation of intricate tasks. The discussion also addresses crucial prerequisites for successful implementation, including workforce readiness, governance frameworks, technology architecture and robust data foundations. Readers will gain insights into the strategic implications of agentic AI, learn how to identify suitable use cases and understand the phased approach required for deployment in highly regulated environments. By the end of the paper, decision makers will be equipped with knowledge on aligning agentic AI with business objectives, mitigating risks and leveraging this technology to enhance operational agility, scalability and resilience — ultimately positioning their institutions for long-term competitiveness in an increasingly digital landscape. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: agentic AI; generative AI; autonomous AI systems; banking digital transformation; AI governance and regulation

The global promise of digital banking lies in the industry’s potential to combine efficiency, scale and inclusion. Yet, the reality in many emerging markets is more complex. Purely digital platforms often struggle to gain traction in cash-heavy economies where trust is limited and digital literacy uneven. At the same time, traditional branch–based banking remains too costly to extend to low-income and/or low-density communities, like peri-urban and rural areas, without state support or direct government ownership of the financial institution. Tyme, through its TymeBank in South Africa, pioneered a novel ‘phygital’ approach that bridges these extremes and then took this model to the Philippines for its GoTyme Bank. Tyme’s network of physical-meets-digital kiosks, brightly coloured and mobile, resembling ATM machines, embedded in high-footfall retail outlets — initially grocery stores and then fashion outlets — allows customers to open fully functional accounts in minutes, receive debit cards instantly and transact within familiar, trusted environments. This paper examines the kiosk model in depth, exploring its technological design, operational model, impact measured by gender, challenges and replicability. It posits that the kiosk is more than a distribution tool; it is a social and technological innovation that has redefined what digital banking means in contexts of embedded exclusion. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: banking; digital; financial inclusion; FinTech

This paper examines the role of artificial intelligence (AI) in modernising enterprise workflows within legacy-dependent banking environments. It identifies structural limitations in traditional banking systems, including siloed architectures, limited interoperability and reliance on manual processes, which constrain efficiency, scalability and responsiveness. To address these challenges, the paper proposes an AI-driven integration framework that combines machine learning, natural language processing and robotic process automation within a modular, middleware-based architecture. The framework enables intelligent data extraction, automated decision making and real-time workflow orchestration across legacy and modern systems. It introduces AI-enabled middleware connectors and agent-based orchestration to support seamless interoperability while preserving existing infrastructure investments. The study evaluates the framework across digital lending and accountopening processes, demonstrating substantial improvements in operational performance, including reduced processing times, decreased manual intervention and enhanced compliance accuracy. The findings highlight the potential of AI to transform enterprise workflows by enabling dynamic, data-driven operations and improving risk detection and regulatory adherence. The paper also addresses implementation challenges, including data governance, model interpretability and integration risks, emphasising the need for robust architectural design and explainable AI. Overall, it provides a practical, scalable approach to achieving digital transformation in complex banking ecosystems and improving longterm operational resilience. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: AI-driven workflow automation; legacy system integration; banking modernisation; robotic process automation (RPA); natural language processing (NLP); mainframe integration; enterprise architecture; digital transformation; compliance automation; financial services innovation

This paper examines the digitalisation of the Thai capital market and outlines the strategy of the Securities and Exchange Commission Thailand to support this transition. It identifies persistent inefficiencies, including fragmented data, manual processes, high costs and inconsistent standards, which limit efficiency and transparency. The paper presents the digital securities ecosystem, designed to enable end-to-end digital processes across issuance, trading, settlement and custody. It discusses the application of distributed ledger technology, block chain and smart contracts to improve data sharing, automation and real-time settlement.1 Supporting measures include legal reform to enable digital securities, regulatory sandboxes for innovation testing,2 and enhanced supervision using data-driven tools. The paper emphasises investor readiness, governance and standardisation as crucial to adoption and trust. It argues that digitalisation can enhance liquidity, reduce costs, increase transparency and support financial inclusion. Overall, it provides a policy and implementation perspective on enabling digital transformation while maintaining market integrity and investor protection, and offers practical insights into aligning innovation with regulatory objectives effectively. It also notes the importance of interoperability, data standards and cross-sector collaboration in delivering scalable outcomes, as well as highlights initiatives and pilot projects that demonstrate practical use cases in the Thai capital markets. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: capital market; digitalisation; digital securities; digital securities ecosystem; technology

Many economies have been leveraging real-time electronic payment systems to drive financial innovation and inclusion. This paper assesses whether data from Sistema De Pagos Electronicos Interbancarios (SPEI), an interbank electronic funds transfer system owned and operated by Banco de Mexico, can improve the timeliness and accuracy of Mexico’s gross domestic product (GDP) forecasts by acting as a complementary indicator of economic activity. In addition to being almost immediately available to the Central Bank, SPEI data is extremely comprehensive and about 168 times larger than credit and debit card transactions. The paper presents a cointegrated forecasting model using SPEI as the sole predictor of GDP. In the next stage, they build an auto regressive integrated moving average (ARIMA) model using the residuals of the cointegrated model. Compared to much more sophisticated, data-intensive models, the paper shows that using a complementary indicator like SPEI can be a parsimonious forecasting alternative, especially during highly volatile periods when it can mitigate information gaps. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/ business/.
Keywords: nowcasting; forecasting; Mexico; GDP; ARIMA; error modelling; electronic payment systems; Sistema De Pagos Electronicos Interbancarios; SPEI; complementary indicator