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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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FRAUD AND DISINFORMATION PREVENTION – FINANCIAL INSTITUTIONS AND NEWS OUTLETS USING AI TO VERIFY THE AUTHENTICITY OF MEDIA (SPOTTING AI-DOCTORED VOICES OR VIDEOS IN SCAMS AND ELECTIONS), THEREBY PRESERVING TRUST AND SAFETY

Authors: Nicolas Guzman Camacho;

FRAUD AND DISINFORMATION PREVENTION – FINANCIAL INSTITUTIONS AND NEWS OUTLETS USING AI TO VERIFY THE AUTHENTICITY OF MEDIA (SPOTTING AI-DOCTORED VOICES OR VIDEOS IN SCAMS AND ELECTIONS), THEREBY PRESERVING TRUST AND SAFETY

Abstract

The emergence of artificial intelligence (AI) has posed some tremendous challenges in fraud and disinformationdetection and deterrence, especially in financial organizations and media houses. With the advent of AI technologiessuch as deep fakes, voice synthesis and manipulated video content becoming more and more advanced, the necessityof a well-developed system of media verification has never been so acute. The present paper discusses the purpose ofAI in authenticating the authenticity of media with reference to its use to promote financial fraud prevention andcounter electoral disinformation. The paper is a review of the existing AI technology employed by financial institutionsto implicit frauds, such as AI voice and face recognition, and AI-based deepfake detection technologies used by newsoutlets to maintain media integrity. The results imply that although AI is an important factor to protect trust, there areissues regarding its accuracy, scale, and ethics. The paper is summarized in the conclusion with a highlight on thepossible use of AI in authenticity and transparency, in addition to demanding further innovation and regulation tocounter any emerging threat in the fast changing digital environment.

Keywords

AI verification; Deepfake detection; Media authenticity; Financial fraud prevention; Disinformation; Election security; Voice synthesis; Media integrity

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green