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How US Intelligence Services analyse global risks like Covid-19

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Based on decades of research and practice, US Intelligence Services have a field-tested framework to analyse with global risks. This framework is well-documented and available, but Steve Lindo, Lecturer and Course Designer, MS in Enterprise Risk Management, Columbia University, observes that there is little uptake in the private sector. In this article, Lindo explores the practices that could benefit financial risk managers and the challenges of adopting these practices.

In the intelligence world, volatile, uncertain and high-stakes risks occur 24/7

Terrorism, war, cyber-attacks, drug cartels – these are just some of the volatile and uncertain risks which confront US Intelligence Services every day. The teams of professionals tasked with analysing these global risks face a herculean task, sifting through mountains of inconclusive and sometimes conflicting data, as well as expert opinions, emotions and cognitive biases, all under intense time pressure. In order to address these challenges, over the course of the last 25 years US Intelligence Services have developed and implemented a suite of analytical methods specifically designed to produce rigorous, objective, and transparent assessment of complex, high-stakes situations such as these.

Structured analytic techniques

The methods used by US Intelligence Services are known as Structured Analytic Techniques (SAT’s). Their origin stems from the cognitive and behavioural research which came to prominence in the 1980’s, overlaid by a vast trove of actual intelligence analysis and outcomes. The framing and practice of these methods by US Intelligence Services began in earnest in the 1990’s, was endorsed by the 9/11 Commission Report and incorporated as mandatory for high stakes decisions where there are multiple possible outcomes in the 2004 Intelligence Reform and Terrorism Prevention Act.

Today, this suite of methods encompasses more than 50 distinct techniques, which fall into three main categories:

  • Diagnostic: Techniques aimed at making analytic arguments, assumptions and inferences more transparent and objective
  • Contrarian: Techniques which explicitly challenge current thinking
  • Imaginative: Techniques which aim at developing new insights, different perspectives and/or alternative outcomes

All of these methods share field-tested characteristics designed to improve the outcomes of complex analysis. In particular they:

  • Lever diverse views and expertise,
  • Encourage evidence-based assessments,
  • Slow down thinking,
  • Expose group-think and corner-cutting,
  • Respect, and test, intuition and gut feelings,
  • Document the analytical process for review and future learning,
  • Are explicitly endorsed by each agency’s executive leadership.

Importantly, these methods don’t pre-empt the way that each agency makes its decisions, but rather strengthen the existing decision-making process by adding diagnostic, contrarian, or imaginative analytics appropriate to each situation.

The private sector has no equivalent

In spite of the extensive, publicly available documentation of these analytical practices, there is no evidence of their adoption in the private sector. One reason is a domain transfer barrier: businesses typically don’t look to government for best practices in decision-making or risk management. Another, more practical reason, is that most businesses confront volatile, uncertain, and high-stakes risks only rarely. When they do, they typically call upon the same fast and efficient decision-making practices which have served them well in familiar situations, where data, models, and expert judgment are known to be reliable. Only when these fast-thinking decision-making methods prove disastrously wrong, have private sector organisations recognised the need to develop slow-thinking decision-making practices like the ones used by US Intelligence Services.

The new normal – managing unpredictable risks

During the last 25 years, the risk management profession has come a long way, in terms of developing methods and processes to measure, analyse and manage predictable risks. However, the sudden onset of Covid-19 is now demanding a crucial pivot to analysing and managing unpredictable risks. Levering the hard-won analytical experience of the US Intelligence Services is a lifeline that should not be ignored.

Join Steve Lindo at RiskMinds Americas where he will assess the decisions made during the Covid-19 pandemic through the lens of US Intelligence methods.

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About the author

Steve-Lindo-ccbf3cee2408b47bd0fdcecc35968bccSteve Lindo is a financial risk manager with over 30 years’ experience managing risks in ALM, funding,banking and trading portfolios. His current role is Lecturer and Course Designer at Columbia University’s School of Professional Studies, teaching Financial Risk Management to graduate students in Columbia’s MS in Enterprise Risk Management program. He is Co-Principal of Intelligent Risk Management LLC, an executive education and advisory partnership which shows organisations how to test their high-stakes decisions using analytical methods pioneered by the U.S Intelligence Services, and Principal of SRL Advisory Services, an independent consulting firm specialising in risk governance, education and strategy, financial technology innovation, risk data management, regulatory expertise, information risk management and financial litigation support. Mr. Lindo is a regular presenter at conferences, webinar host and author of risk management articles and case studies. He has a BA and MA from Oxford University and speaks fluent French, German, Spanish and Portuguese.

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