Today, data availability is limitless, technology is getting smarter and sharper, and business dynamics are more challenging than ever before. With this constantly increasing complexity and speed of change, harnessing the power of an effective risk management process has become imperative for the strategic and long-term success of an organization.
Traditional risk management approaches are based primarily on subjectivity and individual perceptions, which may not be the optimal way of dealing with the emerging risk landscape. Hence, the approach needs to evolve, rather transformed from risk management to risk enabled performance management (REPM). With REPM, the focus shifts to mapping the business drivers critical to achieving the objectives and helping business stakeholders identify relevant emerging risk trends and metrices for its effective monitoring. The effectiveness of this approach lies in granulating the business drivers into key strategies and tasks, without losing focus on the macro perspective.
Embedding data analytics and other technologies across the risk management process
With the rise of new risks, the use of data analytics and other advanced technologies has become more important than ever. Incorporating data analytics in risk management is key. The risk management approach must embed these technologies across the entire risk management process, starting from identification to assessment to mitigation to monitoring. Each step of the process presents a great opportunity for leveraging the power of analytics. Let’s look at the application across each of these stages: