Configuration-Driven Rules Engines: Scalable MultiMarket Regulatory Reporting In Enterprise Data Warehouses—An Implementation Framework With Healthcare Case Studies.
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| Title: | Configuration-Driven Rules Engines: Scalable MultiMarket Regulatory Reporting In Enterprise Data Warehouses—An Implementation Framework With Healthcare Case Studies. |
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| Authors: | Baddam, Ramgopal |
| Source: | Journal of International Crisis & Risk Communication Research (JICRCR); 2025 Supplement, Vol. 8, p18-28, 11p |
| Subject Terms: | REGULATORY compliance, INFORMATION storage & retrieval systems, AUTOMATIC control systems |
| Abstract: | Configuration-driven rules engines signify a groundbreaking architectural framework for governing multi-market regulatory reporting in enterprise data warehouse contexts. Healthcare and financial firms increasingly face growing complexity in regulatory compliance as jurisdictions implement unique reporting requirements, validation rules, and submission methods that often change. Traditional implementations that are market-specific generate architectural redundancy, demonstrated through shared codebases, inconsistent validation logic, and disparate maintenance procedures, resulting in technical debt while increasing compliance risk. Configuration-driven architectures engage these concerns by delineating business logic from implementation code with metadata-based rule definitions that are applied dynamically at run time, which affords organizations the ability to consolidate codebases and create jurisdictional variations through the use of parameterized functions. This architectural paradigm takes advantage of parallel processing, automated orchestration frameworks, and hierarchical metadata to create scalable compliance responses. Empirical healthcare implementations demonstrate configuration-driven architectures achieving error rate reductions from 2.8% to 0.6%, processing throughput improvements reducing monthly compliance cycles from 18 to 4 days, and operational cost reductions of 35–40% through consolidated validation logic and automated orchestration, while reducing full-time staff allocation for regulatory report maintenance by 45–55%. This continued evolution from embedded or hard-coded rules to flexible, metadata-driven configurations affords rapid responses to regulatory change while ensuring an audit trail for compliance review. An emerging class of technologies, notably artificial intelligence, blockchain, and cloud-native architectures, expands the configuration-driven capabilities, positioning these technology systems as foundational infrastructure for mapping multiple jurisdictional regulatory demands on organizations and individuals as they face the growing complexity of compliance. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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Nájsť tento článok vo Web of Science | Abstract: | Configuration-driven rules engines signify a groundbreaking architectural framework for governing multi-market regulatory reporting in enterprise data warehouse contexts. Healthcare and financial firms increasingly face growing complexity in regulatory compliance as jurisdictions implement unique reporting requirements, validation rules, and submission methods that often change. Traditional implementations that are market-specific generate architectural redundancy, demonstrated through shared codebases, inconsistent validation logic, and disparate maintenance procedures, resulting in technical debt while increasing compliance risk. Configuration-driven architectures engage these concerns by delineating business logic from implementation code with metadata-based rule definitions that are applied dynamically at run time, which affords organizations the ability to consolidate codebases and create jurisdictional variations through the use of parameterized functions. This architectural paradigm takes advantage of parallel processing, automated orchestration frameworks, and hierarchical metadata to create scalable compliance responses. Empirical healthcare implementations demonstrate configuration-driven architectures achieving error rate reductions from 2.8% to 0.6%, processing throughput improvements reducing monthly compliance cycles from 18 to 4 days, and operational cost reductions of 35–40% through consolidated validation logic and automated orchestration, while reducing full-time staff allocation for regulatory report maintenance by 45–55%. This continued evolution from embedded or hard-coded rules to flexible, metadata-driven configurations affords rapid responses to regulatory change while ensuring an audit trail for compliance review. An emerging class of technologies, notably artificial intelligence, blockchain, and cloud-native architectures, expands the configuration-driven capabilities, positioning these technology systems as foundational infrastructure for mapping multiple jurisdictional regulatory demands on organizations and individuals as they face the growing complexity of compliance. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 25760017 |
| DOI: | 10.63278/jicrcr.vi.3407 |