Aller au contenu principal
Accès ouvert déclaré 2026 article

ARTIFICIAL INTELLIGENCE-ENABLED REGTECH FOR KYC, FINANCIAL COMPLIANCE, AND REGULATORY REPORTING: APPLICATIONS, RISKS, AND FUTURE DIRECTIONS

0Citations signalées, ce qui n’est pas une note de qualité
2Institutions déclarées
1Pays d’affiliation déclarés

Rattachement africain : cn. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Financial institutions face growing volumes of customer, payment, ownership, and regulatory data while remaining accountable for risk-based compliance decisions. Artificial intelligence-enabled regulatory technology can assist this work by combining digital identity services, entity resolution, rules, machine learning, graph analytics, natural language processing, and workflow automation. This narrative review explains the technical architecture of such systems and examines their use in know-your-customer procedures, financial compliance monitoring, investigations, and regulatory reporting. The technology can improve data reconciliation, prioritise alerts, reveal relationships that are difficult to detect in isolated records, retrieve evidence, and automate repeatable reporting steps. Its value, however, is constrained by incomplete labels, severe class imbalance, concept drift, adversarial adaptation, opaque models, privacy risks, fragmented rules, legacy systems, and dependence on external vendors. A lower false-positive rate does not by itself demonstrate improved monitoring effectiveness, and a suspicious transaction or activity report should be understood as an indicator for further review rather than definitive evidence of non-compliance. Responsible implementation therefore requires a layered architecture in which traceable controls preserve explicit regulatory requirements, models are validated against operational objectives, consequential decisions receive documented human oversight, and every data transformation, model version, explanation, override, and report remains auditable. Future development is likely to centre on privacy-preserving collaboration, temporal graph models, machine-readable regulation, and source-grounded generative assistants. AI-enabled RegTech should be treated as governed decision support, not as an autonomous substitute for legal interpretation, customer due diligence, investigation, or regulatory accountability.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
ARTIFICIAL INTELLIGENCE-ENABLED REGTECH FOR KYC, FINANCIAL COMPLIANCE, AND REGULATORY REPORTING: APPLICATIONS, RISKS, AND FUTURE DIRECTIONS
Date Crossref
07/09/2026
Éditeur
Upubscience Publisher
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Blockchain Technology Applications and SecurityFinTech, Crowdfunding, Digital FinanceImpact of AI and Big Data on Business and Society

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.