Geospatial Data and Multimodal Fact-Checking for Validating Company Data

The statistics department of the Deutsche Bundesbank offers high-quality data to analysts, researchers, and the public to assess the financial system and support policymaking. However, company master data, which is crucial for analyses at the microeconomic level, originates from several sources and may contain gaps, inconsistencies, and a lack of standardization. Accurate information, such as the sector classification and regional location of companies are essential for meaningful analyses and valid conclusions. Incorrect sector classification can often be recognized with the help of additional data, such as satellite images, cartographic data, and company reports. For example, such data can help determine whether a company operates in the manufacturing, agriculture, or energy supply sector. However, performing these manual checks to ensure data consistency and reliability is costly. This project aims to automate these data quality checks using multimodal LLMs. By proposing a system architecture for combining and processing geospatial data from images, texts, and digital twin data within a multimodal fact-checking approach, we aim to demonstrate the potential of multimodal fact-checking to enhance data quality and integrity. Furthermore, this paper highlights the integration challenges and discusses the potential for generating multimodal, data-driven insights.