Analyze financial data to detect irregularities in areas such as billing trends, financial relationships, and regulatory compliance procedures.

“Analyze financial data to detect irregularities in areas such as billing trends, financial relationships, and regulatory compliance procedures.” is a core task performed by Fraud Examiners, Investigators and Analysts. Among the occupation's 23 rated tasks, workers place it 11th by importance (#13 most important). About 88% of workers say it is relevant to their job.

This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.

Work activities this task rolls up to

O*NET groups concrete tasks into broader work activities shared across many occupations.

• Analyze business or financial data. in Analyzing Data or Information

AI exposure

The OpenAI / Eloundou “GPTs are GPTs” study rates this task E2. Exposure with tools — software built on top of a language model (not the model alone) could cut the time by at least half.

Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 0.50. Automation potential label: T3.

How AI is actually used on this kind of task

The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.

• 0.003% share of AI-use records mapped to this task

Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.

Other tasks in this occupation

• Gather financial documents related to investigations. · importance 4.8
• Interview witnesses or suspects and take statements. · importance 4.7
• Prepare written reports of investigation findings. · importance 4.7
• Document all investigative activities. · importance 4.6
• Create and maintain logs, records, or databases of information about fraudulent activity. · importance 4.6
• Lead, or participate in, fraud investigation teams. · importance 4.5
• Coordinate investigative efforts with law enforcement officers and attorneys. · importance 4.5
• Testify in court regarding investigation findings. · importance 4.4
• Prepare evidence for presentation in court. · importance 4.4
• Recommend actions in fraud cases. · importance 4.3
• Review reports of suspected fraud to determine need for further investigation. · importance 4.2
• Design, implement, or maintain fraud detection tools or procedures. · importance 4.2
• Maintain knowledge of current events and trends in such areas as money laundering and criminal tools and techniques. · importance 4.1
• Evaluate business operations to identify risk areas for fraud. · importance 4.1

See all tasks on the Fraud Examiners, Investigators and Analysts page.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-task-16057,
  title  = {Analyze financial data to detect irregularities in areas such as billing trends, financial relationships, and regulatory compliance procedures.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/tasks/task-16057}
}