Human-Centred AI Transforms Finance, Personalising Services and Enhancing Security.

Human-Centred AI demonstrably enhances financial services by enabling personalised products and improved user experiences. Data analytics and machine learning reveal detailed customer insights, facilitating tailored investment recommendations via robo-advisory services. AI also strengthens fraud detection, risk assessment and regulatory compliance, creating a more secure financial landscape.

The convergence of artificial intelligence and financial technology, commonly known as FinTech, presents both opportunities and challenges for delivering genuinely user-focused services. Recent developments demonstrate the potential of applying human-centred AI, a design and development philosophy prioritising human needs and capabilities, to enhance financial products and improve customer experiences. Festus Adedoyin and Huseyin Dogan, researchers at Bournemouth University, explore this intersection in their paper, “Human-Centred AI in FinTech: Developing a User Experience (UX) Research Point of View (PoV) Playbook”. Their work examines how data analytics and machine learning, core components of artificial intelligence, are being utilised to personalise financial services, strengthen security measures, and improve regulatory compliance, all while advocating for a strategic framework incorporating user experience research to ensure alignment with both user needs and business objectives.

Human-Centred Artificial Intelligence (HCAI) demonstrably refines financial services through increased personalisation and adaptability, improving both products and services. HCAI facilitates a deeper understanding of customer needs, preferences and behaviours, allowing financial institutions to deliver tailored solutions and enhance user experience. This is achieved through the application of machine learning, a subset of artificial intelligence enabling systems to learn from data without explicit programming, and advanced data analytics, the process of examining raw data to draw conclusions about that information. A key application lies in AI-powered robo-advisory services, which offer customised investment strategies aligned with individual risk tolerances and financial goals, actively managing portfolios and adapting to market fluctuations to potentially enhance investment outcomes.

Research highlights the crucial role of AI in bolstering fraud detection mechanisms, strengthening risk assessment protocols and ensuring adherence to regulatory requirements, collectively fostering a more secure and resilient financial ecosystem. Financial institutions increasingly integrate User Experience Research (UXR) perspectives into development processes, ensuring alignment between technological capabilities and genuine user needs, thereby maximising the effectiveness and adoption of innovations. UXR focuses on understanding user behaviours, needs, and motivations through observation and feedback, informing the design and development of user-friendly and effective products. Researchers have created a publicly available UX POV Playbook, supporting the implementation of this user-centric methodology within the FinTech domain, providing a framework for conducting user-centred research and translating insights into actionable recommendations.

Future work should investigate the long-term effects of HCAI on financial inclusion, particularly for underserved populations, exploring how HCAI can overcome barriers to access and promote financial literacy. Further investigation into the interplay between HCAI and evolving regulatory landscapes is also warranted, ensuring that innovation proceeds within a robust and adaptable legal framework. Expanding the scope of UXR to encompass a broader range of user needs and preferences will further enhance the effectiveness of HCAI solutions, ensuring they are truly user-centric and inclusive.

The study reveals that a proactive focus on ethical considerations, including the mitigation of bias and promotion of fairness, is paramount when deploying HCAI in finance. This builds trust and ensures responsible innovation, preventing discriminatory outcomes and fostering equitable access to financial services. Algorithmic bias, where AI systems perpetuate existing societal biases present in the data they are trained on, represents a significant challenge requiring careful attention and mitigation strategies.