In a time of profound ecological, technological, and regulatory change, banks, financial institutions, and capital markets are facing a dual transformation: On the one hand, there is growing pressure to systematically integrate sustainability aspects into business models, risk management, and financing. On the other hand, new developments in the field of artificial intelligence---in particular generative AI and AI agents---are opening up completely new possibilities for information processing, decision support, and process automation.

This connection is becoming increasingly relevant, especially in the context of sustainable finance and transition finance. Today, banks have to process large amounts of heterogeneous and often unstructured information: sustainability reports, corporate transition plans, regulatory requirements, industry analyses, customer information, climate scenarios, and qualitative disclosures. This information is crucial for assessing transformation paths, climate risks, and sustainability-related financing decisions---yet its complexity means that traditional methods can only be used to a limited extent.

Technological advances in generative AI, large language models, and agentic AI systems are creating new perspectives in this area. They make it possible to structure extensive text collections, extract relevant information from documents, reveal connections between sustainability goals, financing requirements, and risk drivers, and provide more intelligent support for decision-making processes. This opens up new potential---from the analysis of ESG and climate data to the evaluation of transition plans and support for credit decisions, portfolio management, and customer advisory services.

The symposium will discuss the following questions, among others:

• How can GenAI and AI agents support banks in analyzing ESG data, sustainability reports, and transition plans?
• What role do AI-based systems play in assessing transformation risks and opportunities in companies and industries?
• What are the limits of AI when dealing with complex sustainability and transition information?
• How can unstructured information be made usable for credit assessment, risk management, and portfolio management?
• How can banks use AI effectively to support customers in their sustainable transformation?
• What requirements arise in terms of governance, traceability, data protection, and regulatory compliance when using GenAI in the financial sector?

The aim of the 29th Banking Symposium is to bring together active researchers and practitioners interested in the transformation of the banking and finance industry. The program will include several academic presentations and insights from invited experts from the business community.

We will reimburse travel costs and accommodation for presenters. Please direct questions to bankensymposium@uni-due.de. 

The symposium directly preceeds the 32nd DGF Jahrestagung in Düsseldorf (September 24-26, 2026). It is possible to reach Düsseldorf by subway or train within 30 minutes.

In an increasingly data-driven world, banks, financial institutions, and capital markets are undergoing a profound transformation. A growing share of available information is unstructured – including textual data from analyst reports, social media feeds, voice recordings from client conversations, financial disclosures, news articles, and visual content such as satellite imagery and videos.

While traditional financial analysis has relied heavily on structured numerical data, a significant portion of valuable insights now lies beyond the boundaries of conventional databases. The ability to capture, process, and extract knowledge from unstructured data is rapidly becoming a strategic advantage.

Recent advances in Natural Language Processing (NLP), machine learning, and big data analytics have opened new possibilities to systematically leverage these vast and diverse data sources. This creates exciting opportunities--from early detection of financial risks to alternative credit scoring and investor behavior analysis.

Among others, we aim to discuss the following questions at the symposium:

• How can unstructured data sources be effectively utilized for financial analysis?
• Which technological tools and models have proven useful in finance?
• What is the role of AI and machine learning in extracting insights from text, images, and audio?
• How is risk assessment and forecasting transformed by incorporating alternative data?
• What regulatory, ethical, and data protection issues arise from using unstructured data?
• How can the integration of unstructured data improve efficiency and transparency in the financial sector?

The aim of the 28th Banking Symposium is to bring together active researchers and practitioners interested in the transformation of the banking and finance industry. The program will include several academic presentations and insights from invited experts from the business community.

We will reimburse travel costs and accommodation for presenters. Please direct questions to bankensymposium@uni-due.de. 

The symposium directly preceeds the 31th DGF Jahrestagung in Hagen (September 18-20, 2025). It is possible to reach Hagen by train within 90 minutes.