03447ntm a22005177i 4500 000723075 CZ-PrVSE 20250614131007.0 m d cr n|||||||||| 250614s2025 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Harník, Martin ISIS:162272 dis Použití umělé inteligence pro extrakci textu z dokumentů a jeho integraci do aplikace pro úvěrovou analýzu. eng Applying AI for Text Extraction from Documents and Its Integration into a Credit Analysis Application / Martin Harník 2025 ?? stran : digital, PDF soubor Vedoucí práce: Soňa Karkošková Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2025 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2025 This thesis explores the use of artificial intelligence for automating data extraction from unstructured financial documents, with a focus on credit analysis reports in the banking sector. Credit analysts routinely produce detailed reports when evaluating loan applications, but the information contained in these documents is rarely reused due to a lack of structured integration. To address this inefficiency, the thesis develops and validates a proof-of-concept pipeline that extracts both structured and unstructured data from PDF documents and integrates it into a centralized SQL database that powers a credit analysis application. The solution combines Azure OpenAI GPT-4 Omni for processing free-text narratives with Azure AI Document Intelligence for extracting structured data. The thesis follows the CRISP-DM methodology and is contextualized using the three-axis maturity framework, which evaluates the organization’s readiness across analytics, data, and IT dimensions. The implementation is iteratively refined based on feedback from credit analysts, ensuring alignment with real-world workflows. The results demonstrate the feasibility and business value of integrating cognitive AI into document-heavy processes and lay the foundation for future expansion of AI capabilities within the bank’s credit risk management systems. Způsob přístupu: Internet data a analytika pro business [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas Azure AI Document Intelligence Document processing GPT-4 Omni SQL Data extraction Karkošková, Soňa ISIS:53698 ths Potančok, Martin vse20201071395 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/90352/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/90352 Hlavní práce https://insis.vse.cz/zp/90352/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/90352/posudek/oponent/86359 Oponentura https://insis.vse.cz/zp/90352/podrobnosti dc:identifier NEPOSILAT VSKP vse90352 250613 90352