Internal theft, maritime investigations, risk assessment, security, voice, artificial intelligence

Ever since criminal networks have recognized the profit in oil and energy pipelines, the theft of hydrocarbon-based products has jeopardized the stability and security of global regions.  Although numerous pipelines run across land and below the oceans, tankers serve as the most efficient way of transporting crude oil and natural gas between continents.  This applied research study describes a novel AI-powered, a voice-based tool that identified human risk in a multi-national Southeast Asian energy company weakened by large-scale internal theft.  78.6 percent of completed automated interviews resulted in risk-positive evaluations.  Ground truth from testimonial interviews and an internal investigation verified 92.6 percent of scrutinized flags.  Previously undiscovered details were identified by the automated tool regarding the scope, size, and scale of crime issues, involving all job levels and local politicians.  Analyses provided evidence of the technology’s non-biased nature and demonstrated that its algorithm-generated outputs may be more dependable than observable behavioural cues. Findings (1) describe a potential decision support tool for detecting risk in situ, (2) contribute to employee fraud and internal theft literature, and (3) indicate that in the southeast Asian energy industry, approval for the approach described and recognition of its contribution are overwhelming.

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