Brownbag Seminar Series

Speaker: Klaus Buddeberg & Johanna Husting, Universität Hamburg

Abstract: The OECD's PIAAC study (Programme for the International Assessment of Adult Competencies / Survey of Adult Skills) reports on the basic skills and everyday practices of adults. Everyday mathematical (numerical) skills and basic financial skills are not identical, but they are related in terms of content.

The research project ‘Everyday Financial Practices of Adults’ evaluates the PIAAC results with regard to questions of financial education. For the brown bag lecture, we will give a brief insight into the concept of the PIAAC study and then compile selected results on the everyday mathematical skills of different population groups. The proportion of adults with very low everyday mathematical competence is around 20 per cent, but the proportion is much higher for adults with low formal education, immigrants and older adults. Differences along socio-demographic and socio-economic characteristics are also apparent in everyday practices (e.g. calculating prices and budgets or searching for financially relevant information). When selecting the groups of people, we orient ourselves as far as possible towards the target groups of the other projects in the funding line.

Speaker: Carmela Aprea, Ronja Baginski, Matheus Zago

Abstract: Targeted monitoring is an essential foundation for the evidence-based design and evaluation of programmes aimed at promoting financial competence. The Financial Competence Monitor (FinKomp-Monitor) project seeks to establish such a foundation for the continuous monitoring of the financial competence of the adult population in Germany across all stages of life. This requires the development of suitable approaches to competence modelling and measurement, which will be discussed in this brown bag seminar. In addition to providing an overview and critical assessment of existing competence frameworks, we will present our ideas on the definition, modelling, and measurement of financial competence within the FinKomp-Monitor project in order to discuss them with the brown bag participants from the funding line.

Speaker: Andrej Gill

Abstract: We study how explainable AI (XAI) influences the behavior of individuals who are evaluated by algorithmic systems but do not operate them. Using an incentivized online experiment based on a modified investment game, we examine whether algorithmic predictions shape repayment behavior, how individuals strategically manage the disclosure of these predictions, and whether explainability alters these responses. Consistent with prior work, we find that predictions act as self-fulfilling prophecies: reciprocal predictions increase repayments, while non-reciprocal predictions reduce them, independent of subjects’ true behavioral type. Participants also use disclosure strategically, paying to reveal favorable predictions and conceal unfavorable ones. Explainability moderates these patterns: compared to the AI condition, XAI subjects show more hesitant and cautious disclosure behavior and adjust their willingness-to-pay once they observe their personalized explanations. Our results highlight that explainability not only informs evaluated individuals but also alters their strategic incentives, with implications for transparency regulation and the design of algorithmic decision systems. These findings show that interacting with algorithmic assessments is itself a behavioral challenge—one that increasingly shapes real financial decisions. As AI tools become embedded in consumer finance, effective financial education must prepare individuals not only to make financial choices, but also to understand and navigate AI-generated predictions and explanations.

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Speaker: Jana Franke, Bernd Remmele

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Speaker: Stephan Friebel-Piechotta, Miriam Reußner, Janike Romppanen

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Speaker: Liane Platz, Annika Kretschmer, Christian Bentsche

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