Risk management

Risk management is evolving rapidly due to technological advancements, regulatory shifts, geopolitical instability, and emerging threats. Businesses and risk professionals face new challenges and opportunities that redefine how risks are identified, assessed, mitigated, and monitored.

There are major challenges and opportunities for managers and professionals working in risk management. They are increasingy expected to know finance like an economist, law like a regulator, cybersecurity like a hacker, AI like a data scientist, and climate risks like an environmentalist. Each of these fields takes a lifetime to master, but the CRO is supposed to juggle them all. Although they do not use exactly these words, companies and organizations asking to hire a new Chief Risk Officer (CRO), are "seeking a fearless navigator to dodge financial, legal, cyber, AI, and climate catastrophes, sometimes all at once. Must predict the unpredictable, explain AI decisions to regulators, and keep the board from panic mode."

The Convergence of AI and Risk Management

Artificial intelligence (AI), machine learning (ML), and automation significantly impact risk management in many ways.

AI-powered analytics are transforming risk management by enabling organizations to predict, assess, and respond to potential earlier than ever. Instead of reacting to risks after they occur, businesses can now use real-time data, machine learning, and predictive modeling to anticipate risks and take proactive measures.

AI continuously gathers data from multiple sources, including internal data (records, logs, HR data, incidents), external data (market trends, news, social media sentiment, supply chain disruptions, economic indicators), and data from the IoT and sensors. AI analyzes historical and real-time data to identify unusual trends that may signal an impending risk. It triggers real-time alerts when risk thresholds are breached, allowing companies to take immediate action.

For example, AI in financial markets can flag high-risk transactions and automatically block them. AI-powered cybersecurity systems shut down suspicious network connections before an attack escalates.

AI-driven User and Entity Behavior Analytics (UEBA) systems can continuously monitor employees’ digital and physical activities, analyzing patterns to identify suspicious deviations from normal behavior. AI establishes a normal behavior profile for each employee based on historical activity.

As a very simple example, if an employee typically logs in between 9 AM - 5 PM and accesses specific systems, that pattern becomes their baseline. AI flags behaviors that deviate significantly from the baseline. If an employee suddenly accesses large amounts of sensitive data at midnight, it may indicate an insider threat. What was once the domain of intelligence agencies, sophisticated risk analysis, predictive modeling, and real-time threat detection, is now within reach for private sector entities.

As AI-driven risk management becomes a standard tool in corporate environments, legal teams play a critical role in ensuring compliance, mitigating liability, and addressing ethical concerns. Risk and legal teams most work together, to ensure they have a clear answer in many questions. For example:

- Does the organization have a valid legal basis for using AI to process employee, customer, or third-party data?

- Does AI involve data transfers from the EU to jurisdictions outside of the EU? If so, are they compliant with laws and regulations?

- Under GDPR Article 22, individuals have the right not to be subject to fully automated decisions with legal or significant effects. Does the AI provide human oversight?

- Has the entity conducted bias audits and algorithmic transparency assessments to prevent discrimination?

Year after year, AI-driven behavioral risk analytics are shaped by advancements in machine learning, deep learning, quantum computing, behavioral biometrics, and real-time automation.

With Hyper-Personalized Behavioral Models, AI will analyze not just general user behavior but individual-specific risk patterns for more precise detection.

With AI-Driven Response Mechanisms, future AI will not only detect threats but take automated actions.

With Advanced Behavioral Biometrics, AI will use keystroke dynamics, voice patterns, and facial recognition to detect impersonation attempts.

With Explainable AI (XAI), AI risk models (that currently may lack transparency), will explain why a risk alert was triggered, improving trust, decision-making and solving regulatory compliance challenges. XAI will explain what behavior triggered the alert, and recommend actions.

Explainable AI can address some legal challenges related to transparency, accountability, and compliance, but it does not eliminate all legal risks associated with AI-driven risk management. XAI cannot eliminate legal liability, it only provides evidence for legal defense. Courts may still hold organizations accountable for harmful AI outcomes.

Even if an AI system is explainable, it may still violate privacy laws and sector-specific regulations. XAI explains why AI makes decisions, but it does not control how data is collected, stored, or shared. Legal teams must still ensure compliance.

The Expanding Role of the Chief Risk Officer (CRO)

The CRO evolves from a compliance-focused role to a strategic leadership position. CROs are involved in business model resilience, climate risk assessments, and AI governance. Companies integrate risk management directly into decision-making processes at the Board level. CROs advise CEOs and Boards on risk-adjusted business expansion strategies, and digital transformation initiatives.

Risk-adjusted business expansion strategies involve evaluating and managing potential risks associated with growth opportunities to ensure sustainable, profitable, and resilient expansion. Organizations integrate risk assessment and mitigation measures into their expansion decisions, balancing opportunities with potential threats. Before expanding, organizations must identify, quantify, and manage risks that can impact success.

Market risks, demand uncertainty, competitive risks, customer preferences, and much more must be extensively analysed and AI-driven predictive analytics must be used to assess changes. Stress testing models will simulate financial outcomes in different scenarios, and recommend hedging strategies.

By leveraging AI-driven risk analytics, scenario planning, and robust risk governance, businesses can expand strategically while safeguarding their financial stability, reputation, and compliance integrity.

From cyber risk to hybrid risk

Cyber threats become more sophisticated, with AI-powered cyberattacks, ransomware-as-a-service (RaaS), and deepfake frauds increasing. Cyber insurance premiums rise as companies struggle to mitigate systemic cyber risks.

Regulations like the NIS 2 Directive and DORA in the EU push organizations to implement stricter cybersecurity governance. The rise of quantum computing challenges traditional encryption methods, forcing companies to adopt post-quantum cryptography controls and to adapt to a new era.

There are still companies and organisations that consider cyber risk a technical risk. But even the most advanced organizations must adapt and build their risk management framework on the foundation that we now operate in a fundamentally different world, one where cyber risk is a core component of hybrid risk. The old mindset is dangerously outdated. Today, cyber operations are embedded in economic warfare, political conflict, supply chain disruption, and military strategy. Cyber risk is not just about protecting networks, it’s about protecting societies from hybrid threats.

A hybrid risk management framework should identify primary cyber threats, map their cascading effects on financial, legal, and business operations, and develop cross-functional response strategies.

For centuries, Newtonian mechanics was considered a complete and stand-alone framework for understanding motion and forces. It worked well for most practical applications but failed to explain phenomena at very small (quantum) or very large (cosmological) scales. Eventually, the theory of relativity and quantum mechanics showed that Newtonian physics was just a subset of a much broader and more complex reality.

Similarly, cyber risk has traditionally been seen as a stand-alone issue, much like Newtonian mechanics. However, just as physics evolved to integrate quantum and relativistic perspectives, cyber risk must now be understood as part of the larger hybrid risk environment, where cyber operations interact with economic, political, military, and psychological dimensions.

Instead of thinking “cyber risk”, decision-makers should think “hybrid risk with a cyber component”, to develop a more realistic and effective response strategy. Governments and organizations must recognize that cyber risks are part of a larger conflict strategy, not standalone risks. Defense strategies must address the full spectrum of hybrid threats, not just cybersecurity in isolation.

The Convergence of Physical and Digital Risk

The convergence of physical and digital risk refers to the increasing interdependence between cybersecurity threats and physical security risks. Traditionally, organizations treated physical security (building access control, asset protection) separately from digital security (cyberattacks, data breaches, ransomware). However, with the rise of IoT, smart infrastructure, and cyber-physical systems, these risks are increasingly interconnected.

Organizations now develop integrated risk management strategies that account for blended threats, where cyberattacks lead to physical damage and physical security breaches enable cyber intrusions.

Governments and regulators already require cybersecurity and physical security integration in many industries, including finance, energy, and healthcare. Cyber threats targeting power grids, oil refineries, and water treatment plants can cause physical disruptions. Drones and AI-powered surveillance tools are being used for cyber and physical surveillance and espionage.

Cyber-physical integration risk management is the process of identifying, assessing, mitigating, and responding to threats that impact both digital and physical security. As businesses and governments integrate IT (Information Technology) with OT (Operational Technology), they increase exposure to hybrid threats where cyber incidents can cause real-world disruptions and vice versa.

The convergence of cyber and physical threats requires a fundamental shift in risk management strategies. Organizations must break down silos between cybersecurity, physical security, and geopolitical risk teams to address hybrid threats effectively.

Climate Risk and ESG change risk management

Climate risk refers to the financial, operational, and strategic risks businesses face due to climate change and environmental factors. It is broadly categorized into physical risks (direct impacts from climate change, such as extreme weather events, rising sea levels, wildfires, and droughts), transition risks (arising from regulatory, technological, market, and reputational changes associated with the shift to a low-carbon economy), and liability risks (legal risks arising from failure to address environmental impact, including lawsuits from regulators, investors, or affected communities).

Environmental, Social, and Governance (ESG) Risks are the challenges businesses face in managing environmental, social, and governance-related factors that impact financial performance, reputation, and regulatory compliance. It includes environmental risks (pollution, resource depletion, deforestation, carbon emissions, regulatory compliance with sustainability laws), social risks (human rights violations, product safety, community impact), and governance risks (ethical misconduct, corruption).

Both climate risk and ESG risk require organizations to integrate sustainability considerations into risk management frameworks.

Financial institutions and corporations must conduct climate stress tests to assess portfolio exposure to climate-related financial risks, simulate different climate scenarios (2°C vs. 4°C global warming), and report findings to regulators and investors. For example, banks with operations in the EU must assess how their mortgage portfolio is exposed to flooding risks under different climate scenarios, as required by European Central Bank (ECB) stress testing guidelines.

Climate risk and ESG are fundamentally reshaping risk management by expanding risk frameworks beyond traditional financial considerations. Organizations must adapt or face financial, regulatory, and reputational consequences.

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What is risk management?

Risk management is both an institutional mechanism and a formally established system that includes documented and continuously improving policies, procedures, and processes designed to ensure the lawful, prudent, and transparent management of uncertainty.

As an institutional mechanism, it is part of the organization’s overall governance framework, ensuring that the board of directors and executive management discharge their statutory and fiduciary duties of care, diligence, and prudence.

As an operational system, it translates these governance obligations into practical and auditable measures for establishing context, identifying, assessing, evaluating, mitigating, monitoring, and reporting risks that may affect the achievement of lawful, regulatory, and strategic objectives.

Establishing context refers to the process of defining the internal and external parameters that determine how risk management operates within an organization. It ensures that all risk related decisions are made within a defined framework that sets the boundaries of responsibility, authority, and compliance before any risk is identified or assessed.

This stage answers questions such as:

1. What are the legal and regulatory obligations applicable to the organization?

2. What fiduciary, contractual, or statutory duties apply to directors and management?

3. What are the organization’s strategic objectives and critical success factors?

4. Which stakeholders (regulators, customers, shareholders, employees, suppliers) have rights, expectations, or claims that must be considered?

5. What is the organization’s structure, operating model, and decision-making hierarchy?

6. What is the organization’s declared risk appetite and tolerance?

In legal and regulatory terms, risk management is a demonstrable process through which an organization fulfills its duty to act responsibly, to anticipate and manage risks, and to maintain operations within its defined risk appetite and tolerance.

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Risk governance and risk management.

Risk governance is the system by which the board and senior management direct, authorize, and oversee how an enterprise confronts uncertainty. It defines who decides, on what basis, with which information, subject to which constraints, and accountable to whom.

In legal terms, risk governance expresses the duties of care, loyalty, and prudence through structures, mandates, and evidence. It determines the organization’s risk appetite and tolerance, approves the framework and resources for control, establishes the criteria for escalation and exception, and ensures independent assurance of effectiveness.

Risk management is the set of processes that operate within this system. It is the disciplined, repeatable, and continuously improving execution of policies, procedures, and controls for establishing context, identifying, assessing, evaluating, mitigating, monitoring, and reporting risks.

Risk governance allocates decision rights among the board, executive management, risk and compliance functions, business lines, and internal audit. It defines the independence and remit of second-line challenge, the scope of third-line assurance, and the conditions under which decisions must be escalated to a higher authority. Risk management then acts within those delegations to perform analyses, run scenarios, select and operate controls, and monitor indicators. When a tolerance threshold is breached, the governance design compels escalation and review. The management system provides the data, impact analysis, options, and recommendations.

Culture is principally a governance matter. The board and senior leadership shape incentives, tone, and consequences that determine whether issues surface early or are suppressed, and whether challenge is encouraged or penalized. Governance sets the conflict-of-interest policies and expectations for transparency and remediation. Risk management translates cultural intent into training, attestations, surveillance, disciplinary processes, and measurable indicators. When regulators or courts evaluate culture, they look for governance documentation that shows design, and for risk management evidence that shows operation.

Risk governance defines the perimeter of responsibility, including subsidiaries, joint ventures, and outsourced service providers. It designs audit rights, regulatory cooperation clauses, notification duties, data localization requirements, and termination strategies in contracts and intra-group service agreements. It also defines the oversight model for critical providers and shared services, including reporting obligations and consequences for breach. Risk management conducts due diligence, risk assessments, continuous monitoring, and testing in accordance with the risk governance requirements. If a vendor failure leads to a regulatory breach, the question is whether controls functioned, but also whether governance adequately designed the contractual and oversight environment.

In enforcement and litigation, authorities and courts ask who owned the risk, what information was presented to decision-makers, and how the organization responded to warning indicators. Risk governance provides the policies, procedures, minutes, and decision memoranda that demonstrate prudence, proportionality, and timeliness. Risk management provides the records of what has happened. An organization that can show both layers, sound governance directing sound management, has a defense grounded in process and execution.

Risk governance makes decisions between growth and safety, speed and control, innovation and compliance. It sets the policy for model risk, data ethics, and the responsible use of artificial intelligence, determining what uses require heightened scrutiny, human-in-the-loop oversight, or outright prohibition. Risk management operationalizes the policy by cataloguing models, implementing monitoring for drift and bias, and enforcing change control.

The Three Lines Model is useful in understanding how risk governance and risk management interact in practice. Governance is the architecture of these lines and their interfaces, defining authority, responsibility, and assurance that connects operational execution to strategic oversight. It is through this architecture that an organization demonstrates the integrity of its control environment and the transparency of its accountability chain. The board of directors, as the ultimate governing body, establishes and maintains this structure, ensuring that each line operates with clarity of purpose, independence of function, and coherence of reporting.

The first line of defense includes those who own and manage risk as part of their day-to-day responsibilities. In this line are the business units, operational functions, and service providers who make decisions, design and deliver products or services, and operate the systems and processes that expose the organization to risk. Their primary duty is to identify, assess, and control risks within their activities, to adhere to approved policies and risk tolerances, and to report exposures and incidents accurately and promptly.

The second line of defense provides the standards, policies, and methodologies that ensure the first line performs its responsibilities in a controlled and consistent manner. This line includes the risk management and compliance functions. They establish the framework for risk assessment, monitor adherence to limits, evaluate the effectiveness of controls, and provide thematic reviews and expert interpretation of legal and regulatory requirements.

The independence of the second line is both a governance and a legal necessity. It must be sufficiently separate from the business it oversees to challenge it objectively, but also sufficiently integrated to understand its context.

The third line of defense, internal audit, provides independent and objective assurance to the board and senior management regarding the adequacy and effectiveness of both the first and second lines. It evaluates whether policies and procedures are followed, but also whether they are designed appropriately to achieve lawful and effective risk control.

The third line operates under a direct reporting line to the audit committee or the board, ensuring functional independence from executive management. Its work provides evidence of accountability, documenting whether the control environment functions as intended, and whether the risk governance system remains fit for purpose. In regulatory and legal terms, internal audit answers the question of verification, the ability of the organization to demonstrate that its risk management system is not only well designed, but also verified by an independent function.

Effective risk governance ensures that the interfaces between these lines are neither blurred nor fragmented. It defines where one line’s responsibility ends and another’s begins, avoiding both duplication and gaps.

Risk governance is the whole design, the architecture of authority, accountability, and assurance that defines how an organization exercises control under uncertainty. Within this design, the Three Lines Model provides a practical expression of structure. Risk management is located primarily within the second line of defense, functioning as the central oversight and coordination mechanism.

However, while risk management resides institutionally within the second line, it interacts continuously with all others. The first line executes the organization’s core activities and carries direct responsibility for adhering to risk policies and tolerances set by the second line. The second line defines the methodologies, metrics, and escalation thresholds that ensure operational conduct remains within appetite and compliant with law. The third line independently evaluates the effectiveness of both, explaining to the board if the governance system functions as designed.

In simple words, risk governance is the entire design, including board oversight, organizational structure, policies, culture, reporting lines, and assurance mechanisms. Risk management represents a critical component within that design. Governance gives the system legitimacy and authority, and risk management gives it operational coherence.

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Risk management, an art and a discipline.

Risk management has long been regarded as both an art and a discipline, a bridge between foresight and control, prudence and ambition. Throughout history, philosophers, economists, and modern regulators have observed that risk is inevitable, but mismanaging it is not. The wisdom captured in the words of those who have studied uncertainty reveals that risk management is a reflection of judgment, ethics, and governance.

According to Frank H. Knight, writing in the early twentieth century, risk is measurable uncertainty. Uncertainty is unmeasurable risk. Knight’s insight is reflected in modern regulatory doctrines of proportionality and due diligence, which accept that not all future events can be predicted, but require that organizations take reasonable, documented steps to anticipate and control foreseeable harms.

Peter Drucker observed that “the greatest risk is not taking one.” His point was not an endorsement of recklessness, but a reminder that enterprise itself is an act of reasoned risk-taking. In the modern risk and compliance environment, this means that a lawful business cannot be risk free. Drucker’s observation finds its modern legal counterpart in the principle of risk appetite, the explicit statement of how much risk an organization is willing to bear in pursuit of its objectives.

Charles Tremper added a practical point: The first rule of risk management is to avoid doing things that make you look stupid. Stripped of its humor, this remark is valuable, as it explains in simple words that a risk decision may be technically defensible but reputationally indefensible. Regulators increasingly evaluate not only legality but conduct too, whether actions appear consistent with the standards of integrity, fairness, and accountability expected of a prudent enterprise. In the European Union, this approach underlies the expanding concept of conduct risk, which links governance failures, cultural weaknesses, and reputational harm to the legal obligations of management.

Nassim Nicholas Taleb introduced another interesting perspective: Risk is what’s left over when you think you’ve thought of everything. His warning expresses a familiar truth that is sometimes ignored, the limits of foresight. Even the best risk management frameworks and programs cannot eliminate the unknown. An organization is not liable for failing to predict the unpredictable, but it must prove that it had processes designed to recognize, evaluate, and respond to risks. The regulatory emphasis on scenario analysis, stress testing, and reverse stress testing shows the recognition that resilience, not prediction, is the ultimate goal of risk management.

Christine Lagarde, reflecting on her experience as a global policymaker, has said: Good risk management is not about predicting the future, but about preparing for it. Her words have been adopted in spirit by many regulatory frameworks, including the European Union’s Digital Operational Resilience Act and the NIS 2 Directive. These instruments shift the focus from static compliance to adaptive capability, requiring organizations to demonstrate that they can maintain critical operations and legal compliance even under severe disruption.

Risk management, when understood correctly, is neither a mathematical exercise nor a bureaucratic ritual. It is a disciplined system of foresight, governance, and lawful control. It includes the fiduciary principles of prudence and diligence, the managerial principles of accountability and transparency, and the ethical principles of integrity and proportionality. It protects organizations from loss, but also sustains public confidence in the fairness and stability of the markets and institutions.

Risk cannot be abolished, but it can be governed. To govern risk lawfully and effectively is to transform uncertainty from a source of vulnerability into a domain of responsibility. The mark of a mature institution, public and private, is the presence of a robust, documented, and transparent system for understanding and managing risk.

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When bullets fly or regulators ask why, the same risk management principles apply.

Whether the mission is to defend a position or defend a decision, the principles of risk management do not change. In war and in governance, the objective is the same, to act decisively under uncertainty, to protect critical assets, and to accomplish the mission within defined and lawful limits.

In the military, this means preserving lives and achieving strategic objectives. In the world of corporate law, risk, and compliance, it means safeguarding reputation, integrity, and legal standing. In both realms, the discipline is similar, identify the threat, assess its likelihood and impact, evaluate the options, implement the controls, monitor the outcome, and report with accountability.

In the U.S. Department of Defense, the doctrine of risk management is embedded in command itself. Commanders are trained to understand that every decision is a calculation about what must be done, what could go wrong, how severe the consequence, and what measures will bring the risk to an acceptable level. The same logic governs corporate governance and compliance frameworks. Boards and executives, like military commanders, operate under pressure, constrained by time and information. Their duty is to act with diligence and good faith, understanding the risks, controlling what is controllable, and accepting residual risks knowingly and lawfully.

The environment may differ, one marked by the sound of gunfire, the other by the sound of regulation, but both demand clarity of objective, unity of command, and transparency of accountability. Both recognize that failure is the result of unrecognized or unmanaged risk. In military doctrine, it is often called situational awareness. In corporate compliance, it is called due diligence.

When regulators investigate a failure, they ask the same questions a field commander would ask after an operation. What was known? What was done to prevent it? Who was responsible? Were controls in place, and were they effective? The difference is only in vocabulary, not in principle. The discipline that keeps a unit alive under fire is the same that keeps an institution lawful under scrutiny.

The battlefield and the boardroom share the same moral foundation, that responsibility cannot be delegated to chance. In both domains, uncertainty is not an excuse but a condition of leadership. The commander and the corporate executive stand in parallel positions, entrusted with lives, assets, and reputations, empowered to decide, and bound by duty to foresee and control what can be controlled. Chance will always have its part, but responsibility begins where chance ends. The essence of command, whether military or corporate, lies in the conscious acceptance of accountability for outcomes under uncertainty.

In war, commanders are taught that no plan survives contact with the enemy. In business and governance, no strategy survives untested by reality.

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