Technologies: Python, NLP, Machine Learning
Duration: 3 months
Our client builds a financial software (named ‘CF Engine’) in order to model complex financial products (RMBS, ABS, CLO, etc.). The main goal of the project is to extend this software using feature that allows users to review the related legal documents based on the information from the model. The developed model needs to check if specific doc corresponds to one of the created models.
For example, if processed document is mortgage than model:
— parses mortgage document (from PDF, Word, plain text format);
— checks if document contains all required information (all parties are specified and described correctly, property is described, interest rate is specified, all information required by law is provided and so on);
— if document fits the model then system extracts important information (parties, property description, interest rates and so on) and provides it as summary for user review.
System supports different formats of input documents and different types of documents, such as mortgages, car loans, commercial loans and so on. Also system supports different countries of operating, i.e. different structure of document for each country and different languages.