Risk Management Future Directions

An Outline

Continuous change is a universal principle. The universe is endlessly changing, so is our world and everything in it. What was yesterday is not today, and what is today, won’t be tomorrow. Consequently, the scenery of risk and risk management is rapidly changing as well. So, new strategies are constantly required to assess and control risk.

Albinson, Blau, and Chu (2016) published a generic report across industries about future risk management tendencies. They argue that organisations would respond to risk change by using cognitive technologies to supplement and, at times, even replace human decision-making. Also, they would deploy widespread controls as part of their operations to monitor and manage risk in real time. In addition, improvements in behavioural sciences would help to comprehend risk insights, influence risk behaviours, and improve risk decision making. Moreover, organisations would realise that 100% risk prevention is impossible, so investment in detecting risk events as they happen as well as containing and reducing the impact of risk events, would increase. Finally, risk transfer instruments would progressively be used to protect organisations from a wider range of risks, e.g. cyber-attacks, climate change, geopolitical risks, terrorism, business disruptions, etc.

The report also claims that risk change would influence changes within organisations. For example, the marketplace would reward organisations that take on strategic, high-risk inventions. Or, as risks become more measurable and tangible, organisations would be more able to determine an accurate upside value of risk.

Lastly, as businesses engage more deeply with a large number of external stakeholders, they would rely more heavily on them to identify, manage, and reduce risks together. The constant threat of disruption resulting from emerging technologies, business model transformations, and ecosystem changes, will force executives to make significant strategic choices to drive organisational success. In order to survive in a hyper-connected world, the organisation leaders would proactively address the accelerated and amplified risks for their reputations.

Another generic study addressing future research directions in management control systems (MCS) was published by Chenhall (2003). This article presented a critical review of findings from contingency-based studies over the past 20 years, resulting in proposals for applying MCS into organisational frameworks. The author argues that recent developments, including strategic risk management, are only just beginning to be understood by researchers. Likewise, product life cycles place demands for new product initiatives and alter cost structures. So, decreasing life cycles increases operating risk and requires increased capital investment. Understanding how MCS innovations can assist management from these perspectives would probably become more and more important. Also, recent MCS research has recognized that managers have ‘strategic choice’ in order to position their organizations in particular environments. For example, if the current product range is too uncertain, they may need to reformulate the product strategy in a more predictable market. This may limit potential opportunities and may require the organisation to study its approaches on the trade-off between potential returns and acceptable risk.

Alexander (2005) discussed the future aspects of Financial Risk Management. The author claimed that current research on financial risk management focuses on the truthful assessment of individual market and credit risks. So, there is comparatively little theoretical or applied econometric research on other types of risk, aggregation risk, data incompleteness, and optimal risk control. The paper discussed that the model risk originating from crude aggregation rules and insufficient data could lead to a new class of reduced-form Bayesian risk assessment models. Logically, these models should be set within a common factor framework that allows proper risk aggregation methods to be developed. The paper explained how such a framework could also provide the essential links between risk control, risk assessments, and the optimal allocation of resources.