Automated Regulatory Compliance Checking via Semantic Model Mapping

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Solution Overview

Problem

Organizations face increasing compliance costs and challenges in keeping up with changing regulatory requirements, leading to a need for efficient automated regulatory compliance checking systems.

Innovation Solution

The development of a method and system for automated regulatory compliance checking that involves obtaining a semantic model of regulatory rules, extracting logical specifications in DR-Prolog language, and generating queries to extract relevant data from physical databases for comparison against logical specifications, utilizing model-to-text transformation and schema mapping.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If organizations invest in separate silos of compliance technology for each regulation, then regulatory compliance is ensured, but compliance costs increase significantly

Engineering Contradiction:

Improveregulatory complianceVSAvoidcompliance technology architecture

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements a universal compliance checking platform that can handle multiple regulations through a common architecture. The system uses a standardized semantic model and rule extraction engine that works across different regulatory domains, eliminating the need for separate technology silos for each regulation while maintaining comprehensive compliance coverage

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent segments the compliance checking process into modular components: semantic model acquisition, logical specification extraction, schema mapping, query generation, and rule checking. This segmentation allows the system to handle different regulations by configuring specific semantic models and rules rather than requiring separate technology stacks, reducing overall system complexity

Inventive Principle:

Principle #1Segmentation

2Reliability

If extensive reporting requirements are implemented, then regulatory compliance is achieved, but compliance costs as percentage of expenditure increase

Engineering Contradiction:

Improveregulatory complianceVSAvoidcompliance expenditure

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The patent implements automated self-service compliance checking where the system automatically extracts data from organizational databases, transforms it into the appropriate semantic models, and performs rule checking without requiring extensive manual reporting efforts. The automated query generation and data extraction processes eliminate the need for manual data collection and reporting, significantly reducing compliance expenditure while maintaining comprehensive regulatory compliance

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical reporting processes with automated computational systems. The system automatically performs data extraction, transformation, and compliance checking through software-based processes, substituting the manual mechanical efforts that previously drove up compliance costs as a percentage of expenditure

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If manual compliance checking processes are used, then flexibility in understanding regulations is maintained, but the process becomes cumbersome and inefficient

Engineering Contradiction:

Improveregulation interpretation flexibilityVSAvoidcompliance checking efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent implements a dynamic rule extraction engine that can adapt to different regulatory requirements by automatically extracting logical specifications from semantic models. The system dynamically generates appropriate query structures and checking rules based on the specific regulation being implemented, maintaining flexibility in regulation interpretation while achieving high productivity through automated processes

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent introduces semantic models as an intermediary layer between natural language regulations and automated checking processes. This intermediary enables the system to capture the nuanced meaning and flexibility of regulatory requirements in a structured format that can be automatically processed, bridging the gap between human interpretation flexibility and machine execution efficiency

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10339537B2System and method for automated regulatory compliance checking for organizations

Publication Date: 2019.07.02 TATA CONSULTANCY SERVICES LTD

AI summary

A system and method for automated regulatory compliance checking for organizations is disclosed. The present subject matter discloses a method for generating queries to extract relevant data from an organization that with respect to the regulatory rules and subsequently performing automated compliance checking for the organization. In an embodiment, the system captures regulatory rules provided by a regulatory body for an organization and extracts logical specification of rules from the semantic model in DR-Prolog language. The system further extracts a conceptual data model from the semantic model and obtains mapping between the conceptual data model and plurality of physical database. The system generates queries and translated the queries on to physical database schema to extract relevant data from the organization. The extracted data is transformed into ground facts in DR-Prolog and compared with logical specification of rules to perform automated regulatory compliance checking.