The business environment has witnessed a major shift heightened by the COVID-19 pandemic which has compelled organizations to be more dependent on technology. With most businesses moving to the cloud and going digital, risk management approaches cannot remain the same. The question becomes, what is the role of risk intelligence in the emerging and dynamic competitive business environment?
The global society and business world are facing one of the most difficult and complex environments in recent memory. Amidst the pessimism, uncertainty and anxiety foisted by the pandemic, boards and leadership of corporate bodies owe to their investors and stakeholders the responsibilities of not only protecting but also creating value for their organizations.
In an increasingly interconnected corporate world, as most economies intensify efforts to emerge from socio-economic paralyzing effects of the pandemic, global competition for resources, human capital, returns and clients is becoming more intense than ever. Thus, as the society and business community face the reality of the ‘’new normal’’, new leadership styles, new ideas, new mindset, new thinking and re-thinking are required to take organizations through the current and emerging landmines characterized by low returns on investment and poor compensation for risk taking on the back drop of heightened regulatory risk and compliance costs, particularly for the financial services industry.
Boards and executive management teams must confront the above challenges and begin to ask questions about the continued relevance of organization’s strategic vision, structure, business model competitive positioning, and values in the new world order. The ability of businesses to innovate, remain competitive and sustain value creation in the ‘’new normal’’ will therefore require a structured risk decision making process that is both clearly predictive and robust.
This article argues that for institutions that seek to surmount the challenges in the new environment, they must embrace risk intelligence as a vital competitive tool.
This assertion seems to hold even more for the financial services industry where the business activities and models are built around risk taking. As argued by Leo Tilman in ‘’Financial Darwinism‘’, “the dominance of risk taking in financial business models suggests that possessing risk intelligence- thinking holistically about risk and uncertainty; speaking a common risk language and effectively using forward looking tools to make better decisions- has become a critical determinant of survival, success and relevance.” We cannot agree more.
Although the term ‘’risk intelligence’’ gained prominence in financial literature over four decades ago, the initial concept was more aligned to balancing risk and innovation using information and cognitive processes. This understanding has since shifted to that of ‘’understanding and problem solving’. Plainly explained, this is seeing risk intelligence as the set of processes for the conversion of risk data into meaningful and useful information for risk assessment, risk mitigation and strategic planning purposes.
In a very incisive article ‘Risk Intelligence, A Bedrock of Dynamism and Lasting Value Creation’ by Leo Tilman, he defined risk intelligence as ‘’The organizational ability to think holistically about risk and uncertainty, speak a general common risk language, and effectively use forward looking risk concepts and tools in making better decisions, alleviating threats, capitalizing on opportunities and creating lasting value’’
The above definition brings to the fore key elements of risk intelligence demonstrating that the concept is beyond traditional risk management.
Firstly, it prompts us to the new reality of a paradigm shift from risk management as a practice or process to risk intelligence. The new concept emphasizes collaboration among roles and units within the organization and causes a mindset change from seeing risk as an event that should be avoided or effectively ‘’policed’ ’to achieve a residual or acceptable risk position.
In the present situation, institutions are expected to shift from traditional risk management focused on reporting, survival, rules and compliance, policies and frameworks to a risk intelligent process that is forward looking and focused on innovation and strategic growth. Consequently, Risk Managers’ approach and skill sets are expected to change and focus more on strategic goals and objectives, risk driven value creation, and building a forward looking resilient and agile risk environment. Overall, organizations should be looking for risk managers that can turn crises and challenges into innovations and business opportunities on the basis of risk intelligence. The definition re-echoes the fusion of an organization’s strategy, business intelligence and competitive intelligence processes into the single concept of risk intelligence.
Risk intelligence is built around application of data using appropriate tools and systems to take forward looking decisions that supports the strategic actions of the organization such that risk-management becomes more of a competitive tool rather than activity based on remedial or defensive tactics. In an increasingly competitive landscape, intelligent data is not only important for effective competition but more so for predictive and informed decision making.
Benefits of Risk Intelligence as a Competitive Edge
Risk Intelligence provides predictive and prescriptive capability – forward looking insights on key business parameters and the competitive landscape. This supports an organization to take and implement operational and strategic initiatives ahead of their peers.
Executive Management at organizations are confronted with taking key decisions around the four marketing elements of 4Ps- product, price, positioning and place. Arriving at decisions in any of these elements could be a leap in the dark. Effective Risk Intelligence can be adopted to arrive at sound decisions.
Risk Intelligence can be beneficial in prioritizing goals and strategic objectives given the enormous insights provided by its analytical output.
Proactive identification of risks and opportunities in the business environment is a further edge organization get by adopting risk intelligence in their corporate practices. There is an increasing premium placed on timely and factual information. This provides competitive intelligence that is useful to confer a leadership position on the institution in its chosen space by providing first mover advantage.
Risk Intelligence, if appropriately implemented, improves agility and resilience of an organization by strengthening its capacity to challenge basic business assumptions.
Furthermore, it helps the capacity of organizations to reason holistically about risk and uncertainty, collaborate across roles and functional units and reach a common understanding that supports quality decision making.
Risk Intelligence provides boards and executive management with a 360-degree view of the business environment over a reasonable time horizon to support decision making that goes beyond the next monthly, quarterly targets or short-term outlook.
Lastly, it helps leadership at organizations shift from a dogmatic short-term outlook to embracing a longer-term business perspective. This enables organizational dynamism across strategic decisions in relation to key performance indices like resource allocation, capital management as well as re-calibrations of the enterprise-wide portfolio of risk.
Implementing Effective Risk Intelligence-Core Requirements
The building and implementation of a risk intelligent driven institution does not happen without purposeful effort and commitment of resources. Therefore, the following elements are very vital:
- Quality data/Information- Risk Intelligence is built around factual information. It is therefore vital that sources and the reliability of information obtained is verified and validated to ensure the quality of decisions emanating from the process. It is vital that we filter the noise of irrelevant information overwhelming critical data and focus on information pertinent to business decisions and objectives.
- Leadership – The Board of Directors and Executive Management’s desire to link the organization’s strategic vision, business model, and value proposition to risk must be communicated in unambiguous terms. Given the understanding that risk intelligence is a fusion of strategy, business intelligence and competitive intelligence, it is therefore imperative that the linkages across the enterprise are created and sustained for building a risk intelligent organization. Clearly there must be an enterprise-wide alignment in the broadest understanding spanning vision, culture, communication and risk.
- Risk Culture – The risk culture within the organization is a vital factor in ensuring the success of risk intelligence. We can mirror the culture from two dimensions, first the tone from the board and executive management and secondly from the governance structure that empowers professionals at all the three lines of defense to detect threats, manage risks, and contribute to lasting value creation.
Limitations of Risk Intelligence
- Dearth of quality data – One of the main barriers to implementing risk intelligence is the dearth of quality data. Data is often found in silos and in an inconsistent format. Businesses are therefore faced with the challenge of optimizing the output of the information using Risk Intelligence. It is therefore suggested that organizations seeking the adoption of Risk Intelligence should have very clear strategy from the outset for mining relevant and quality data that Risk Intelligence will require.
- Cost – Some businesses whilst recognizing the immense opportunities they could derive from adoption of Risk Intelligence tend to be discouraged by the enormous resources required for its implementation, particularly where there is limited skill or knowledge internally and there is a need to outsource. Due to their complex nature, smart applications can be expensive and can lead to the incurring of further costs for regular maintenance, upgrading and training data models etc. Implementation time of Risk Intelligence solutions may be lengthy and depending on how deep or complex the business wishes to go, this could further extend implementation cost. However, this cost is no different from other software applications like machine learning, artificial intelligence or the use of robots. What we recommend is that businesses need to be deliberate with very clear business objectives.
- Required skill set – Another key challenge to Risk Intelligence adoption is the limited availability of required skill-sets given the technological complexity. The technical knowledge necessary to effectively deploy and operate Risk Intelligence solutions are still relatively short in supply particularly in emerging economies. Appropriate skills and human capacity affects how we process and apply large data to solve problems or execute tasks with output from AI.
- System integration – In most cases, Risk Intelligence solutions need to be integrated or connected with other existing systems and platforms in the As simple as this may sound, it poses a significant challenge of potential risk (data compromise) and cost without precise dimensioning of operability and usability with other systems.
Conclusion
In adapting to the new paradigm, businesses will need to more than ever, position themselves to effectively navigate the profound complexity and uncertainty confronting them. By embracing risk intelligence as an integral part of enterprise-wide language, strategy and culture; articulating the direct connection between risk and dominant aspects of business performance, innovation, resilience and value creation, risk intelligence naturally becomes an important competing tool.