Automated Regulatory Risk Identification System

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Solution Overview

Problem

Businesses in heavily-regulated industries face challenges in manually identifying and managing regulatory risks, leading to time-consuming and error-prone processes for logging and addressing potential violations, which can result in missed risks and reputational or regulatory damage.

Innovation Solution

A system incorporating a scraping module to access enforcement information, a comparator module to match regulatory citations with risk data, and a notification service to alert relevant stakeholders of discrepancies, facilitating automated risk assessment and management within a cloud-based architecture.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual methods are used to identify and manage regulatory risks, then businesses can log and address potential violations, but the process becomes time-consuming and error-prone

Engineering Contradiction:

Improveaccuracy of risk identificationVSAvoidtime required for risk management

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical processes with an automated computer-based system that uses web scraping, natural language processing, and machine learning algorithms to identify and assess regulatory risks, eliminating human error and significantly reducing processing time

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service risk management by automatically monitoring regulatory sources, identifying relevant citations, assessing risks, and generating reports without requiring manual intervention, allowing businesses to independently manage their regulatory compliance

Inventive Principle:

Principle #25Self-service

2Reliability

If manual risk management processes are used, then businesses can address violations, but errors and missed risks increase

Engineering Contradiction:

Improvecompleteness of risk coverageVSAvoidefficiency of risk management

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The automated system uses AI-driven natural language processing and machine learning models to comprehensively analyze regulatory texts and identify all relevant risks, ensuring complete coverage while operating continuously without fatigue or error

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system provides continuous automated monitoring of regulatory sources and real-time risk assessment, ensuring uninterrupted surveillance of compliance requirements and immediate detection of new risks without gaps or delays

Inventive Principle:

Principle #20Continuity of useful action

3Productivity

If automated systems are implemented for risk identification, then efficiency improves, but system complexity increases

Engineering Contradiction:

Improvespeed of risk identificationVSAvoidcomplexity of management system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The complex risk management system is divided into distinct modular components including web scraping modules, natural language processing modules, risk assessment modules, and reporting modules, each handling specific tasks independently to manage overall system complexity

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces intermediary layers including pre-trained language models and classification algorithms that bridge the gap between raw regulatory text and risk assessments, simplifying the processing pipeline and making the system more manageable

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11669795B2Compliance management for emerging risks

Publication Date: 2023.06.06 CAPITAL ONE SERVICES LLC

AI summary

Disclosed herein are system, method, and computer program product embodiments for identifying and managing emerging risks. Businesses, such as those participating in regulated industries, may need to regularly monitor enforcement actions that are cited in a variety of sources. Embodiments disclosed herein provide for scraping information from those sources and comparing it to existing risk events in order to determine possible discrepancies that should be assessed.