The use of generative artificial intelligence (AI) is poised to play a crucial role in the financial industry. However, due to regulatory constraints, the financial sector faces tighter limitations on its AI applications compared to other industries. Nevertheless, taking a broader view by examining processes in other customer-centric industries can offer valuable insights.
A new study from Lucerne University of Applied Sciences and Arts (HSLU) explores use cases for generative AI and examines what banks and insurance companies can learn from other industries in terms of the necessary processes and steps required to build such systems.
The paper, published by the Institute of Financial Services Zug (IFZ), highlights that financial service providers—whether banks or insurers—often face the same challenges as companies in retail, healthcare, or tourism. The study evaluates the extent to which these use cases can be transferred to financial institutions.
Experts classify the different application areas of generative AI on a spectrum. On one end, AI serves customers directly, while on the other, fully automated processes operate internally within the company, often unseen even by employees—a concept known as «dark processing» or straight-through processing (STP). In between, there are applications primarily aimed at internal operations, designed to enhance employee satisfaction and productivity, according to the paper.
AI’s Value in Marketing
Currently, AI’s most useful applications are seen in marketing, where there is significant potential in terms of the cost-benefit ratio. For example, AI can excel in drafting product descriptions, which is particularly relevant given the increasingly complex product landscapes in investment services and the growing complexity of global regulatory compliance.
The demand for personalization and individualization in marketing is also rising in the financial industry, and AI applications are proving effective in meeting these needs. Case studies from non-financial industries included in the study demonstrate the effectiveness of AI in this area.
Banks and insurance companies are actively exploring generative AI, conducting pilots, and rigorously testing applications. As experience with AI grows, so does interest in its use. The number of industry-specific AI use cases in the financial sector is steadily increasing, and the range of applications is expanding.
Regulatory Requirements Set Limits
At the same time, regulatory requirements act as a brake on AI adoption in the financial industry. Security and data protection concerns, as well as infrastructure challenges, such as on-premise or private cloud installations, highlight the limitations.
The study also examines how companies implement AI systems. It’s noteworthy that many companies were introduced to AI and potential applications through their external IT service providers. The approaches to implementing generative AI are diverse, and the study outlines best-practice process models to guide the introduction of AI systems across different levels within organizations.
