Ensuring Operational Compliance in Critical Data-Driven Industries through Robust Software Infrastructure Risk Reporting
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| Titel: | Ensuring Operational Compliance in Critical Data-Driven Industries through Robust Software Infrastructure Risk Reporting |
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| Autoren: | Joseph Aaron Tsapa |
| Verlagsinformationen: | European Journal of Advances in Engineering and Technology |
| Publikationsjahr: | 2021 |
| Bestand: | Zenodo |
| Schlagwörter: | Operational compliance, risk reporting, software infrastructure, data-driven industries, regulatory compliance, real-time analytics, scalability, AI, online monitoring, proactive decision-making, security strategies, the culture of compliance, adaptable solutions, regulatory complexities, machine learning, blockchain, resilience |
| Beschreibung: | This paper examines the challenges and good practices in building, deploying, and using robust software infrastructure risk reporting systems for industries like fintech, utilities, and healthcare, whose activities depend highly on data. Spending such a significant amount of data on the overall big picture of modern industries' performance is the key to the reliability and competitiveness of this operation. Practical and robust reporting systems, a cornerstone in dealing with compliance challenges, are provided via real-time analytics, scalability, and fragmented data. The software architecture meshes analytics, AI, and data monitoring facilities to clarify information, eliminate corruption, and enhance system resiliency against ever-evolving threats. Comprehensive risk reporting areas should be developed, allowing one to make proactive decisions, strengthen security strategies, and grow compliance cultures. Since creative and flexible choices allow one to be very original, complicated issues of regulations can be resolved, and long-lasting success can be achieved. The use of these advanced technologies, such as AI, machine learning, and blockchain, will help move regulatory compliance to the next level. |
| Publikationsart: | article in journal/newspaper |
| Sprache: | unknown |
| Relation: | https://zenodo.org/records/11100567; oai:zenodo.org:11100567; https://doi.org/10.5281/zenodo.11100567 |
| DOI: | 10.5281/zenodo.11100567 |
| Verfügbarkeit: | https://doi.org/10.5281/zenodo.11100567 https://zenodo.org/records/11100567 |
| Rights: | Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode |
| Dokumentencode: | edsbas.F602A78B |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | This paper examines the challenges and good practices in building, deploying, and using robust software infrastructure risk reporting systems for industries like fintech, utilities, and healthcare, whose activities depend highly on data. Spending such a significant amount of data on the overall big picture of modern industries' performance is the key to the reliability and competitiveness of this operation. Practical and robust reporting systems, a cornerstone in dealing with compliance challenges, are provided via real-time analytics, scalability, and fragmented data. The software architecture meshes analytics, AI, and data monitoring facilities to clarify information, eliminate corruption, and enhance system resiliency against ever-evolving threats. Comprehensive risk reporting areas should be developed, allowing one to make proactive decisions, strengthen security strategies, and grow compliance cultures. Since creative and flexible choices allow one to be very original, complicated issues of regulations can be resolved, and long-lasting success can be achieved. The use of these advanced technologies, such as AI, machine learning, and blockchain, will help move regulatory compliance to the next level. |
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| DOI: | 10.5281/zenodo.11100567 |