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AI can Help You Turn Digital Risk Management into Strategic Advantage

AI Can Help You Turn Digital Risk Management Into Strategic Advantage

In any organization, digital risk has rapidly emerged as one of the most pervasive and rapidly growing risks. A recent survey by Gartner indicates that digital risk is the foremost strategic business priority for corporate directors in 2022 and 2023. The dependence on digital technologies has accelerated, driven by investments made during and after the disruptive effects of the pandemic on the business landscape. Consequently, business leaders need to be prepared for even more significant investments in technology initiatives by their companies.

A survey conducted by PwC among CIOs reveals that 60% of companies are making significant investments in digital transformation technologies. Additionally, Deloitte reports a shift in the focus of digital initiatives from optimizing legacy processes to a complete reinvention of businesses as leaders strive to secure their position in a digital world.

Understanding the different kinds of risks and their implications

The reality is without taking risks, generating value is impossible. Likewise, organizations may encounter catastrophic consequences if risks are not managed effectively. However, it’s not just a matter of finding the right balance of risks but also understanding the distinction between the risks that should and should not be taken.

The stakes are incredibly high. In today’s business landscape, everything moves at an astonishing speed. In such a fast-paced environment, comprehending the nature and magnitude of different types of risks becomes a crucial initial step for any company serious about capitalizing on the volatility of the era of extensive digital transformation.

The organizations that will thrive in this new transformative era can discern the differences between three distinct categories of risks and navigate a path that leads to tangible value. However, achieving this requires a more comprehensive and nuanced understanding of how various risks impact the organization, its components, and the entire value chain. These risks manifest in the following three forms:

Risk Type 1 – Downside risks: These risks solely result in adverse outcomes for a company. Taking these risks does not generate value; their management focuses on preserving value or minimizing harm by eliminating, controlling, mitigating, or transferring them. These risks include information security and cybercrime, employee fraud, and regulatory compliance. It is essential to comprehend and reduce these risks thoroughly.

Risk Type 2 – Upside risks: These risks directly relate to an organization’s ability to execute its business strategy and objectives, offering positive opportunities for value creation and growth. Organizations can utilize risks to identify optimal ways to allocate capital for business expansion. This includes potential innovations to expand consumer bases, increase market share, or effectively acquire, manage, and derive value from new assets and talent. Upside risks should be evaluated with the organization’s strategy, determining which risks generate the most value.

Risk Type 3 – Outside risks: These risks can have positive and negative impacts but are unpredictable as they are beyond the organization’s control. They encompass actions by existing and emerging competitors and geopolitical, economic, demographic, and environmental megatrends that can directly or indirectly affect the organization. Businesses must be completely aware of these risks’ potential advantages or consequences and prepare to respond promptly. Effectively managing these risks necessitates shifting risk management tactics and cultural mindset.

Why the traditional approach to risk management is not enough! 

To understand the limitations of the existing framework, it is essential to understand the concept of risk and uncertainty. While risk is quantified based on the probability of an adverse event, uncertainty is characteristically unpredictable as it stems from dynamic, inter-relational systems and the business environment. This critical insight about the uncertainty is not rooted in the traditional risk processes and programs. Because of this, organizations cannot understand how traditional and emerging risks are interconnected, exposing them to uncertainties that cannot be foreseen.

Embracing risk and uncertainty is essential for organizations seeking radical growth and value creation. However, unthinkingly charging into the unknown is not the solution. The risk function must give strategic decision-makers the confidence to seize the upside of risk when it arises.

Building a digital risk management function that creates value for the digital transformation

Turning risk into a strategic business advantage using AI | iTechGRC

The digital risk management function must ensure its analysis is robust, respected, and trustworthy, even amidst the uncertainties of this era of rapid change. This transformation of the risk function involves several interconnected elements:

New ecosystems: Given the complex and interconnected nature of digital risk management, future risk functions must adopt an ecosystem-based approach to risk management. Different organizations, units within those organizations, and specialized third parties will have to share risk intelligence and coordinate responses as an interdependent network to keep pace with change. Utilities designed to gather data for third-party risk management and sharing cyber threat data already demonstrate this approach.

Optimized structures: Risk functions also face changes in their operational frameworks within organizations. While many organizations have adopted or are working toward the “three lines of defense” model risk management, which can feel restrictive in the face of rapidly evolving risks, there is a growing need to incorporate more agility to address high-velocity risks effectively.

Real-time risk reporting models and continuous monitoring may require adjustments to reporting structures for timely information delivery to relevant parties. There is also potential for convergence of functions and shifts in risk activities. As automation takes over certain risk functions and professionals focus on delivering strategic insights, there must be a cultural shift across the organization to ensure risk awareness becomes integral to everyone’s role.


Data insights: Data is the organization’s most critical asset, and it is challenging to derive value and secure it due to the complex technology landscape and the constant threat of cybercrime. Data aggregators, analytics, and machine learning technologies are increasingly providing a structural foundation that empowers other data-related activities. Boards and C-suites expect risk functions to simplify vast amounts of data into predictive insights they can rely on to influence strategic decisions.

Latest technologies: Future-ready risk professionals will leverage new digital technologies and products to generate insights that inform business outcomes. Robotic process automation (RPA) will free up analysts for more strategic work, drones will enable physical audits of inventory and operations, and chatbots will offer efficient channels for customer engagement. The emergence of advanced artificial intelligence and connected technology will expand the toolkit available to risk professionals, facilitating predictive analytics and insights by modeling future scenarios, conducting planning and hypothesis testing, and proactively intercepting issues.

Updated skill sets: Leveraging the latest tools, structures, and ecosystems requires a new breed of risk analysts. They must be aware of broader political, financial, and environmental macro trends and capable of operating in diverse roles within the business, engaging with the C-suite, the board, and vertical managers across the supply chain. They should possess the soft skills to influence risk culture by promoting risk awareness and strategic insights throughout the organization. Intellectual curiosity is crucial due to the velocity of risks. Future risk professionals need to be digitally savvy and data-smart.

Successfully managing the balancing act of channeling intelligence from enriched data analytics and automated processes into strategic insights that unlock new value opportunities will become the “art” of risk management. Agile risk professionals of the future, capable of seizing opportunities while containing risks, will contribute to building ecosystems, business models, and corporate standards that inspire trust and confidence.

How an integrated risk management (IRM) solution can assist businesses in preparing for systemic risks

The challenge of dealing with systemic risk lies in the uncertainty and limited visibility of an organization’s actual risk posture. An integrated risk management solution helps establish a seamless and unified risk framework throughout the organization. It provides contextualized insights that enhance risk oversight and the decision-making process. The following are ways in which IRM software can benefit CIOs and CROs:

Enabling collective risk intelligence:

The COVID-19 pandemic has highlighted the significance of non-traditional risks, such as climate change, health hazards, data privacy threats, and geopolitical conflicts, which were previously not given sufficient attention by most companies. The pandemic-induced disruptions have compelled organizations to reassess their risk prioritization. With an IRM solution, organizations can incorporate information from regulatory bodies, social media, geo-disaster probabilities, benchmark agencies, and data providers. These combined insights can then be evaluated in conjunction with business strategies.

Simplifying the complex data landscape:

Organizations have made dispersed investments to address specific risks or compliance requirements over the years, resulting in increased data volume and fragmented risk insights. IRM enables organizations to establish an infrastructure consolidating unstructured and structured data from internal and external sources. This framework serves as a single source of truth for all risk-related data, enabling the deciphering of interconnected risks, regulations, issues, and audit results that guide business strategy and performance.

Facilitating an agile risk framework:

Systemic events like the COVID-19 pandemic expose businesses to more significant risk vulnerabilities, necessitating a re-evaluation and modification of business strategies, operations, investments, and structures. In such an environment, having an agile, comprehensive, and coherent risk framework becomes crucial for organizations to assess, understand, and mitigate risks efficiently. An AI-driven integrated risk management framework, through governance structures, processes, and metrics, enables informed decision-making with real-time insights. It promotes agility in risk-based decision-making by providing a unified view of top risks, ensuring effective risk mitigation actions.

Harnessing advanced analytics, artificial intelligence (AI), and automation:

Organizations can leverage collective insights to identify unknown trends and emerging risks. The availability of integrated and centralized repositories of risk data, as well as datasets and benchmarks, offers opportunities to utilize AI and machine learning-based analytics for detecting unknown risks. Risk response strategies can be formulated based on this intelligence.

With a structured and streamlined cohesive risk framework, organizations can quickly adopt robotic process automation (RPA) tools for automating risk assessments or control monitoring. Moreover, engaging with frontline staff through AI chatbots enables capturing observations on risks and issues, which can then be analyzed for patterns and trends. These insights provide valuable information for identifying emerging risks and developing proactive response plans.

Conclusion: IRM powered by AI, analytics, and automation transforms risk into a strategic business advantage

In an increasingly digital world, human decision-making speed is outpaced by the speed of digital transactions. Real-time analytics are employed to make decisions. An integrated risk management approach supported by analytics and automation equips organizations with a clearer view and actionable insights into existing and future risks, facilitating the assessment of their impact on the business. With this data, organizations can navigate crises with agility and responsiveness, enabling proactive risk-aware decision-making.

Risk managers can utilize an integrated risk management solution like IBM OpenPages with Watson. It integrates datasets and benchmarks from popular regulatory feeds such as Thomson Reuters Regulatory Intelligence, Ascent, Wolters Kluwer, and Reg-Track. It enables opportunities to utilize AI and machine learning-based analytics for detecting unknown risks and formulating risk response strategies.

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