AI Regulatory Text Indexing for Real-Time Compliance Updates
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Solution Overview
Problem
The financial sector faces high costs and time inefficiencies in adapting to changing regulatory frameworks due to the need for manual compliance operations, which are costly and time-consuming.
Innovation Solution
An autonomous system utilizing artificial intelligence and neural networks to manage and update regulatory digital textual documents, enabling efficient extraction, recognition, and indexing of regulatory texts, and providing real-time updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual compliance operations are used to research, analyze, and update regulatory texts, then regulatory framework conformance can be achieved, but time consumption and economic costs increase significantly
Solution Approach 1:
The patent replaces manual mechanical operations (research, analysis, contextualization, and proposal of changes by trained staff) with an automated computer-implemented system that uses algorithms to process regulatory texts, extract modifications, and generate update proposals, thereby dramatically reducing time consumption while maintaining compliance accuracy
Solution Approach 2:
The system enables the regulatory framework to update itself automatically by monitoring official journals, detecting changes in regulatory texts, and generating proposed modifications without requiring continuous manual intervention, allowing the institution's regulatory framework to maintain itself autonomously
2Reliability
If manual compliance operations are used to research, analyze, and update regulatory texts, then regulatory framework conformance can be achieved, but economic costs increase significantly
Solution Approach 1:
The patent replaces expensive manual operations by trained staff with an automated computer-implemented system that performs regulatory text research, analysis, and update generation, thereby reducing economic costs while maintaining the same level of compliance accuracy
Solution Approach 2:
The system creates and manages digital copies of regulatory texts and their modifications, allowing multiple users to access and work with the same regulatory framework simultaneously without requiring physical document handling or repeated manual analysis, thereby reducing operational costs
3Productivity
If the system provides real-time updates and comprehensive regulatory text analysis, then accessibility and speed improve, but system complexity increases
Solution Approach 1:
The patent divides the regulatory text processing system into distinct functional modules: a monitoring module that tracks official journals, an analysis module that detects changes, a processing module that generates modifications, and a storage module that manages the regulatory framework. This segmentation allows each module to perform its function independently, improving overall productivity while managing complexity through modular design
Solution Approach 2:
The system is designed to handle multiple regulatory texts and official journals through a single unified platform that can process different types of regulatory documents using the same core algorithms and data structures, thereby improving productivity without proportionally increasing system complexity
Data Source
AI summary
It is provided a procedure for managing and updating regulatory digital textual documents, wherein the documents each define a textual structure including at least one or more textual portions, one or more reference parameters defined by at least one article and/or one paragraph, and one or more metadata, and wherein the process comprises acquiring a plurality of different documents from at least one external database, extracting the textual portions, the reference parameters and the metadata from each of the textual structures, recognising each textual structure by means of a first logic implementing an artificial intelligence based on a machine learning approach of supervised or zero-shot type, performing a multimodal analysis of the textual structure, by means of the first logic, labelling each of the textual portions, the reference parameters and the metadata to validate the extraction phase, identify the reference parameters and/or the metadata by means of a second logic implementing an artificial intelligence to produce a digital representation compliant with the Akoma Ntoso specifications or other standard for encoding normative texts, to index the textual portions by associating to each textual portion a respective reference parameter and/or a respective metadata by producing a plurality of indexed texts, to record separately each indexed text in an internal database accessible by a user, to logically link each indexed text whose reference parameters and/or metadata are mutually correlated within the database.