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In a world in which balancing competing strategic priorities and ever evolving risks is the norm, Chief Executive Officers (CEOs) and boards need confidence that executives throughout their organisation are making decisions consistent with risk appetite. They need guardrails and metrics in place to signal when risk appetite is being exceeded or changes to critical risks are occurring. This level of risk insight not only helps leaders mitigate risk, it enables them to make decisions that will increase risk-adjusted returns and turn risk into opportunity.
Companies are beginning to step up their risk analytics capability to mine actionable intelligence and provide insights of strategic business value. Take, for example, a Chief Financial Officer (CFO) that is looking at how to effectively manage shareholder expectations in an inflationary environment when the cost of living is escalating, and the CEO has made purpose-driven commitments to the market about keeping prices flat and to employees about providing an environment for growth. Suppliers are feeling squeezed and third-parties with a vested interest in the company’s profitability are applying pressure. These C-Suite executives need their risk analytics team to be aligned with strategic priorities and to be able to deliver insights that allow them to meet their objectives. Much of the responsibility for initiatives such as this lie with the Chief Risk Officer (CRO), but CEO support is critical to achieving the necessary transformation.
The CEO’s role in mining risk intelligence
A close relationship with the business and understanding of strategic challenges are fundamental to the risk analytics team’s successful mining of actionable risk intelligence. Risk analytics also needs to be part of the broader analytics ecosystem to make most efficient and effective use of resources. There is typically substantial cultural change needed across all parties to bring risk analytics into the strategic fold of the organisation. To that end, CEOs can help in numerous ways.
Principles to guide the journey
As organisations begin to elevate their risk analytics capability, certain guiding principles can help to ensure that the data mined and analysed produces actionable intelligence.
1) Ensure that risk analytics are led by business insight
In the past, risk analytics were often developed by risk professionals and technologists based on what they found interesting and what the tools were capable of, which often resulted in analytics the business didn’t necessarily require. The C-suite and risk analytics team should co-develop perspectives on what data sets they rely on for important decisions and therefore what analytics might help in decision making. It can be hard to move away from being a technology and “what if”-driven capability to a business-led capability. It requires a different vision, mindset and skill set from the team. But, translating business issues and needs into appropriate risk analytics is one of the most critical capabilities within the risk analytics team.
2) Deliver value quickly
Risk analytics teams can fall prey to spending a lot of time developing their operating model, building a team, getting tools and technologies, cleansing data, overlaying governance and building models. By the time they deliver insights to the business, the business has moved on and the value of the risk analytics work is greatly diminished. Teams must clearly balance getting value quickly in the hands of the enterprise and building capability simultaneously. One component of quick delivery is having trust in the business data, which is often a mindset shift for risk functions. Make sure the risk team is aligned to the data governance of the organisation, rather than creating its own. Then work with IT to determine what data is accessible, balancing what data is needed to drive the most valuable insights against the availability and ease of tapping into that data. Fold in external data to enrich risk understanding.
3) Crawl, walk, run
In alignment with the need to deliver value quickly, risk teams should start with foundational and basic elements of risk analytics such as defining key metrics and measures for risk appetite. This helps employees at all levels understand how much risk they can take and make trade-off decisions effectively. Once these fundamentals are in place, analytics can focus on root cause analysis, problem solving and diagnostic use cases, working closely with the business to ideate and prioritise what is needed most. Then as capabilities mature, more advanced predictive analytics, modelling scenario analysis, stress testing and forward-looking capabilities can be tackled. These more advanced efforts take time and investment that is more easily made once a track record of delivering business value is in place, and silos between risk and business teams are broken down.
Conclusion
To mine data and deliver actionable intelligence, the risk analytics team needs to bring more to the business than data scientists, tools and backward-looking analysis. They need a deep business and industry understanding, and an ability to build relationships. They must have the skills to bring people together to ideate on the problems the business is trying to solve and the analytics that will bring the most value to that effort. By providing the right support, CEOs can reap the benefit of having a panoramic view of risks across the organisation, with the metrics in place to understand and take advantage of changes in the risk landscape as they occur.
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