Deloitte has launched Risk Clarity, an AI-native solution designed to support organisations across the enterprise risk life cycle through agentic capabilities.
The offering is delivered through Ascend, Deloitte’s AI-enabled service delivery platform.
Go deeper with GlobalData
Access deeper industry intelligence
Experience unmatched clarity with a single platform that combines unique data, AI, and human expertise.
Risk Clarity aims to improve consistency, clarity and visibility across enterprise processes, risks and controls, while reducing manual work.
It includes six modules and more than 25 agents covering automated testing, control optimisation, issue management, key risk indicators, process mapping, reporting and risk assessment.
Deloitte said the platform gives clients a single point of access to its industry experience, proprietary data, agentic workflows and alliance technologies.
It can be used throughout the delivery life cycle, from strategy and design to programme management, code generation, data validation and testing.
The company said organisations can use Risk Clarity to replace fragmented and manual risk activities with a more connected, agile and data-driven operating model.
Deloitte Global and US Regulatory, Risk and Forensic leader Gina Primeaux said: “Organisations are under growing pressure to understand risk clearly, act faster, and do so across increasingly complex environments.
“Risk Clarity brings together Deloitte’s deep risk experience, AI-powered intelligence and a modular set of capabilities to help clients modernise how they manage, execute and oversee risk across the enterprise.”
The company added that the modules allow organisations to start with selected use cases and scale deployment over time.
The capabilities include translating regulations into actionable requirements; linking process documentation directly with risks, regulations and controls; and automating risk identification alongside effectiveness scoring.
They also cover reviewing and rationalising controls, automating control testing, and supporting issue creation, early data-quality detection and thematic root-cause analysis.
Human-in-the-loop validation remains part of the process, allowing risk teams to focus on higher-value work and more informed decision-making.
