Abstract: A method for automating a software development lifecycle by using artificial intelligence is disclosed. The method includes receiving a request to generate software components, the request including requirements in a natural language format; determining, by using a first model, tasks to generate the requested software components based on the request, each of the tasks including a sequence of subtasks, an acceptance criterion, and a predicted effort level; generating, by using a second model, sets of software code based on the tasks, the sets of software code corresponding to the requested software components; generating, by using a third model, unit tests for each of the sets of software code; initiating the unit tests for each of the sets of software code; and releasing, by using a fourth model, the sets of software code based on a result of the corresponding unit tests.

Abstract: A method and a system for detecting abnormal and/or anomalous rejections of requests for quotes for foreign exchange transactions are provided. The method includes: receiving a request for quote (RFQ) that relates to a proposed foreign exchange (FX) transaction; retrieving first information that relates to a financial capability of the requester to conduct the proposed FX transaction; applying a first algorithm that is designed to make an initial determination as to whether the RFQ is acceptable, based on the RFQ and the first information; when the initial determination indicates that the RFQ is not acceptable, applying a second algorithm that uses an artificial intelligence (AI) technique to determine a potential reason that the initial determination has indicated that the RFQ is not acceptable; and generating a report that includes information that relates to the potential reason that the initial determination has indicated that the RFQ is not acceptable.

Abstract: A method and a system for automating a due diligence process are provided. The method includes: receiving identification information that relates to a customer; selecting, from a global set of due diligence questions based on the received identification information, a group of due diligence questions to be applied to the customer; determining a document source via which documents containing relevant information about the customer are accessible; retrieving, from the document source, a set of documents that relate to the potential customer; extracting, from the retrieved documents, information that is relevant to the selected group of due diligence questions with respect to the customer; and outputting the extracted information. Each of the determination of the document source, the retrieval of the set of documents, and the extraction of the relevant information is performed automatically by executing artificial intelligence algorithms that implement machine learning techniques.