-д хадгалсан:
| Үндсэн зохиолч: | |
|---|---|
| Формат: | Recurso digital |
| Хэл сонгох: | |
| Хэвлэсэн: |
Zenodo
2020
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| Нөхцлүүд: | |
| Онлайн хандалт: | https://doi.org/10.5281/zenodo.17638989 |
| Шошгууд: |
Шошго нэмэх
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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Агуулга:
- <p><span lang="EN-GB">The financial services industry operates under some of the most demanding regulatory frameworks in the world, requiring constant oversight, detailed reporting, and precise recordkeeping. Institutions must process immense volumes of structured and unstructured data, including contracts, regulatory filings, KYC records, transaction reports, and audit trails. Traditional compliance workflows, built on manual data entry and rigid rule-based systems, often lead to inefficiencies, increased operational costs, and heightened exposure to compliance failures. By 2020, however, a technological inflection point emerged with the convergence of deep learning, streaming orchestration, and cloud-native architectures. These innovations enabled the development and operational scaling of document intelligence platforms. This article explores the transformation of compliance operations from static OCR-based processes to AI-native frameworks, emphasizing how modern orchestration technologies enable continuous monitoring and providing practical reference architectures for deploying deep learning pipelines in regulated financial environments.</span></p>