Risk teams are under increasing pressure to move beyond blocking and tackling to providing strategic risk advice that can help their companies achieve sustainable resilience in the face of critical emerging risks, according to the report Material Improbabilities, Getting Practical with Emerging Risks from Marsh & McLennan Companies Global Risk Center.
Where the expectation isn’t already there, it ought to be and probably will be in due course. This shift is vital for firms and a boost for the standing of the risk function when resource levels are otherwise threatened by cost pressures, opportunities for activity automation, and greater confidence in global economic conditions.
However, strengthening corporate appreciation of complex uncertainties and emerging risks along the lines indicated in this report is no small challenge. To accomplish this, most risk leaders will need to bring about some adjustments to their function’s purpose and interactions. This transition may be underpinned by seven imperatives:
- Demonstrating stronger business or commercial acumen and engaging more intensely with the company’s strategic ambitions and major investments
- Setting and presenting the risk agenda more effectively, finding compelling ways to expose and overcome material biases and blind spots
- Developing more dynamic relationships with senior management and business heads, and deeper partnerships across the finance, planning, and treasury teams
- Nurturing adaptable analytic and advisory skills within the function that can be deployed in multiple contexts outside routine production requirements
- Building an accessible repository of intelligence on emerging risks that can be fed and accessed by Risk, Strategy, and the business units, and instituting more efficient data sharing across Finance and Risk
- Coming up with new ways of analyzing the possible impacts of complex, emerging risks, including the exploitation of new data (science) opportunities
- Leveraging automation opportunities to free up risk resources for engagement with complex uncertainties.