Risk Intelligence Revolution: Shifting Perspectives for Revenue and Success
Written By
Victor Meyer || Supply Wisdom
•
Blogs
In antiquity, the Roman god Janus stood at the threshold of past and future. One face scrutinized the lessons of the past, learning from history’s mistakes and triumphs. The other face stared out to an uncertain horizon, anticipating challenges and opportunities. History is the record of decisions based on looking in one direction or the other, weighing the risks of each, and acting.
Today’s decision makers disproportionately focus on financial risk, seemingly ignorant or indifferent to the historical record, which shows the greatest financial losses are consequences of non-financial risk events – the COVID-19 pandemic, Bernie Madoff’s Ponzi scheme, the FTX collapse, Wells Fargo’s fraudulent account opening scandal; the Russia-Ukraine and Israel-Hamas conflicts, the Chernobyl and Fukushima Daiichi nuclear disasters; the list goes on and on.
The process is driven by an almost algorithmic approach: “Is my potential return commensurate with the downside risk?” “Is that relationship linear, and if not, what is the mathematical relationship?” And especially, “How do I consider risk with ‘unique characteristics?”
Is there merit in a different approach? What if I could shift what drives and informs my decisions and reliably predict the non-financial risks, avoiding the downside consequences while exploiting the upside potential? Since the financial crisis, regulators have required real time management of markets and liquidity. The technology exists to do this, and it can be applied to non-financial risk for competitive advantage.
By operationalizing this risk management philosophy into the core strategy of the company, businesses are not just protecting their current assets, they are positioning themselves for future growth and increased revenue opportunities.
For example, what if I was able to detect early indications of a disease outbreak to both prepare my Operational Resilience response and hedge vulnerable debt and equity positions before the market prices that information? Or as a manufacturing firm, what if I used the intelligence to buy forward contracts on key raw materials, or even better, use location risk information to diversify my supply chain away from countries with poor public health infrastructure? Or remain in the low-cost location but add the capacity to deliver the health care organically?
Once the proper framework is established, the mechanisms for intelligence sharing at the process level can be put in place and enshrined in decision making. Naturally, not every signal is actionable, but every single data point represents an incremental change in the risk profile of a location, a third-party, or a counterparty. Some of these signals represent improvements to a given profile and others represent deterioration. When these signals reach a defined point creating a pattern or trend, they require active risk management. At that point they may also present opportunities to seize the first mover advantage.
This is far from theoretical – the benefits are tangible. Indeed, some companies are already employing state-of-the-art AI-enabled intelligence tools. The following are a few use cases for which there are actual supporting case studies:
Third-Party Risk Management (TPRM) lifecycle efficiency and cost reduction. The right risk intelligence tooling can effectively streamline the process of identifying, analyzing, and mitigating risks during the vendor onboarding process potentially reducing the inherent risk assessment process by 50% or more. And third-party continuous monitoring can be used to base point-in-time periodic reviews on risk appetite threshold triggers instead of relying on complete refreshes of the risk profiles of existing suppliers on an annual or bi-annual basis.
Managing geographic and service concentration risk. Operational risks have a nasty habit of both concentrating and cascading. There are numerous instances of businesses being 100% concentrated for an important business service in one Business Process Outsourcing (BPO) location, only to have that location be subject to a catastrophic natural hazard event, or gradual deterioration in the risk profile across numerous indicators. There have been more than a few examples of this error being fatal to firms.
Using risk data as leverage to negotiate contracts or contract renewal. Supplier performance is often used as leverage in contract negotiations. But what if you used risk intelligence to take that to the next level? What if your tooling was able to generate a real-time scorecard comprising multiple risk and performance indicators for your commercial negotiations, giving you an information asymmetry; you know more about a supplier than they know about themselves?
Operational Resilience stress testing. Risk exposures identified by continuous monitoring can used to perform pre-mortem scenario-based exercises or leveraged by financial services firms to perform a third-party portfolio-level stress test as required by the Digital Operational Resilience Act (DORA) in the EU. For large financial services firms, this data can be leveraged to improve regulatory and economic capital calculations, resulting in more precise Operational Risk capital calculations.
Monitoring costs in Business Process Outsourcing (BPO) locations. Many firms use labor arbitrage through both captive and third-party BPO locations. What if you were able to use location intelligence to plot the trajectory of labor and real estate costs and determine not only the break-even point, but the next suitable location candidates for a BPO function?
Janus looks forward and back, but he is also the god of passages and frames, thus he is the god of context. By embodying this duality of hindsight and foresight, Janus guides us to understand and navigate risk with confidence, outmaneuver competitors, and seize and exploit the future.
