Error and Anomaly Detection in finance leverage AI and ML to identify errors, mistakes, or unusual activity, as well as violations of internal policies, compliance rules, and accounting standards. These tools report anomalies and errors in real-time or via periodic batch processing, allowing users to take investigative or corrective actions on findings. These tools can be leveraged as on-premises, cloud-based or stand-alone solutions; or integrated with accounting and reporting systems (e.g., ERP). The typical users of these tools are risk management teams, fraud, and financial analysts, IT security teams, and compliance officers.
Gartner defines operational technology (OT) as “hardware and software that detects or causes a change, through direct monitoring and/or control of industrial equipment, assets, processes and events”. OT security includes practices and technologies used to protect them, but these practices and technologies are now evolving into distinct categories to address the growing threats, security practices and vendor dynamics.