Harnessing Analytics to Streamline and Automate Your Control Environment In an increasingly complex business landscape, organizations confront mounting challenges linked to their operating models and cost management. These pressures are prompting a discernible shift in focus towards streamlining and simplifying controls to cut costs, boost responsiveness and enhance the control environment. Central to this evolution is recognizing that a well-structured control environment can drive risk management efficiency and effectiveness. Topics Risk Management and Regulatory Compliance In the face of these demands, organizations are exploring innovative strategies, such as using text analytics to simplify control taxonomy, re-baselining control taxonomy based on industry best practices and operational risk management (ORX) control data, and leveraging automation for control monitoring and risk specialist task reallocation. The shift towards automated reporting with visualization tools and advanced analytics is also gaining momentum, offering nuanced insights and enhancing decision-making capabilities across the organization. This article articulates our perspective on these critical transformations. It delves into how organizations can leverage these strategies to navigate the challenges of the modern business landscape and boost control effectiveness. The strategies and solutions presented here are not theoretical but rather are backed by our proprietary control optimization tool and a wealth of practical implementation experience, offering a roadmap towards a more streamlined, responsive and effective control environment. Industry challenge: The Three Lines of Defence (3LOD) model, a time-tested approach to managing risks within organizations, is under mounting pressure. This pressure stems from the need to navigate new risks, streamline costs and enhance the control environment, all of which are challenging tasks in the rapidly evolving business landscape. The universe of risks that organizations need to manage is expanding at an unprecedented rate, driven by technological advancements, geopolitical changes and evolving regulatory requirements. This expanding risk universe of non-financial risks necessitates the implementation of new controls, adding layers to the already complex control stack. Therefore, managing the effectiveness of control frameworks across organizations becomes increasingly time-consuming and costly. The management of financial risks, which are well-integrated within most organizations, continues to rely heavily on manual processes in some instances. These manual processes are labour-intensive, less reliable and prone to human error, further complicating the task of effective risk management. At the same time, with new regulations and industry standards emerging, there's an increasing demand for control environments to be more responsive and adaptable. Failing to meet such requirements could result in non-compliance, financial penalties and a damaged reputation. These challenges, while daunting, are not insurmountable. Mature organizations demonstrate that with strategies such as control taxonomy simplification, re-baselining, automation and enhanced reporting, it is possible to streamline the control environment, boost responsiveness and ultimately drive better risk management. Enabling the step change: Mature organizations are responding to these challenges by focusing on: Image How we can help: Our team is equipped with a proprietary control optimization tool and a rich repository of proven implementation experience, both of which position us perfectly to assist organizations aspiring to make substantial improvements in their control effectiveness. Our tool has been designed to identify potential areas of control enhancement, streamline control taxonomy and facilitate automation where possible. The outcomes are twofold: first, risk specialists are freed from routine tasks to focus on value-added activities, and second, organizational responsiveness is notably increased. Complementing our tool, our team brings a wealth of implementation experience to the table. Having worked with diverse clients across sectors, we understand the unique challenges of control optimization and can provide tailored solutions. We leverage best practices, insights and lessons learned from our diverse portfolio to inform our approach and drive successful control optimization. Our accompanying video provides a detailed illustration of our techniques at work. You can gain a first-hand understanding of our methods and their effectiveness, based on how we have helped other clients on their control optimization journey. Contact us: Please feel free to contact us if you have any further questions or would like to see our control optimization case studies. Leadership Hafsa Jada Hafsa has over 10 years experience specializing in helping clients to meet cost and compliance objectives. Her experience spans across the three lines of defense on a range of topics including controls, assurance, data, conduct and transformation. Hafsa’s core strengths ... Learn More Alex Psarras Alex is an Associate Director in Internal Audit and Financial Advisory at Protiviti UK. Since 2010, he has been working closely with clients to align Internal Audit and GRC functions with their objectives, helping them bridge the gap between risk, data, and technology. ... Learn More Key terms: Text analytics: This involves using systems to read and understand human-written text for business insights. In this context, text analytics identifies keywords within a control name and control descriptions to pinpoint opportunities for simplification and automation. Control environment: A framework of standards, processes and structures providing the foundation for managing risks and threats to an organization. MI: Management information refers to data and graphical visuals utilized to demonstrate the effectiveness of controls. MI supports informed decision-making processes, providing real-time insights into control efficiency and areas of potential enhancement. CCM: Continuous controls monitoring, a methodology for automated, real-time testing of the performance and effectiveness of an organization's control environment. By shifting from periodic, sample-based testing to full-population monitoring, CCM offers comprehensive, “always-on” assurance of control robustness. RPA: Robotic process automation, a technology application that allows for the automation of repetitive, rule-based tasks within a control environment. RPA, by automating these tasks, enables risk specialists to focus on more strategic, value-adding activities, thus enhancing overall control effectiveness and operational efficiency.