Predicting Financial Figures using OCR and Machine Learning: Automated Extraction from Arabic Annual Reports

الموضوعات

إدارة

الملخص

This thesis explores the application of Optical Character Recognition (OCR) and machine learning techniques to extract financial key figures from Arabic scanned annual reports and predict future net profit values using the annual reports for the Palestinian banks listed in the financial market as the data source (six banks for the years from 2012 to 2021). The key figure values were extracted using a series of preprocessing steps and a two-step rule-based extraction approach using Tesseract and OpenCV as supportive tools. The research achieves an extraction accuracy of 85% for the Net Profit key figure and 91.9 𝑅2 for net profit forecasting using the XGBoost algorithm. The thesis overcomes challenges related to Arabic script complexity, document layout, table structure, and image quality issues by leveraging OCR, Natural Language Processing (NLP), and Machine Learning (ML) technologies. The OCR approach can be used as a knowledge base for related or more complex data extraction use cases, and the trained ML models provide proof of concept for predicting net profit with a high volume of data, offering valuable insights for financial analysts, investors, and decision-makers.

روابط وملفات

الوثيقة في المستودع الخارجي عرض في AskZad

التعريف والنوع

رقم الوثيقة: 024e4198-5d2f-4b06-b40b-e8cd70f02a6b
رقم العقد: 0
نوع الوسائط: Crawler
نوع المحتوى: الرسائل العلمية
صيغة المصدر: رسائل ماجيستير
نوع الملف: pdf text
أسماء الملفات: 2441666_1.pdf

بيانات النشر

ألقاب المؤلفين: [{"name_ar":" Batool Nidal Mohammad Derieh","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"سامي صدير","title_ar":"اشراف","title_en":"Supervision"}]
اللغة: English

المصدر والدورية

اسم المصدر: Predicting Financial Figures using OCR and Machine Learning: Automated Extraction from Arabic Annual Reports

المحتوى والصفحات

عدد الصفحات: 0
كلمات الباحثين: annual reports, financial data extraction, table detection, optical character recognition, OCR, image processing, text mining, natural language processing, scanned documents, page classification, Tesseract, OpenCV

إشراف وإعداد

الإشراف: سامي صدير
الإعداد: Batool Nidal Mohammad Derieh

الاقتباسات الببليوغرافية

APA

Batool Nidal Mohammad Derieh و سامي صدير. (2023). Predicting Financial Figures using OCR and Machine Learning: Automated Extraction from Arabic Annual Reports. أطروحة(رسائل ماجيستير). كلية الدراسات العليا-الجامعة العربية الأمريكية. فلسطين.

MLA

Batool Nidal Mohammad Derieh و سامي صدير. Predicting Financial Figures using OCR and Machine Learning: Automated Extraction from Arabic Annual Reports. 2023. كلية الدراسات العليا-الجامعة العربية الأمريكية، رسائل ماجيستير.