Cognitive technologies, Future of Risk


Cognitive technologies augment human decision-making

Future of risk series: Trend one

​Advancements in cognitive technologies, artificial intelligence, and data analytics are helping organizations go beyond traditional ways of managing risks by using smart machines to detect, predict, and prevent risks in high-risk situations. Autonomic computing combines automation and cognitive technologies to make systems self-managing—and potentially self-defending and self-healing against risks.

What forces are driving this trend?

Massive growth in the volume of data available to organizations
Emergence of new and advanced artificial intelligence (AI)-based algorithms
Expanding pool of data science talent
Adoption of behavioral analytics* in risk management

* Behavioral analytics is the tracking, collection, and assessment of user data and activities using monitoring systems to understand interactions and dynamics between different elements.

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What are the opportunities?

  • Identify use cases that are well-suited for cognitive technology solutions: Where the risk area is critical, large amounts of data are available, and current solutions aren’t effective
  • Use visualization to analyze and communicate information in a human-friendly way to enable rational decision-making
  • Upskill employees so that they are able to more effectively use cognitive technologies to extract insights from data

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cognitive technologies

What are potential threats and pitfalls?

  • Difficulty in implementing complex cognitive tools
  • Overhyped technologies unable to deliver on promises
  • Lack of trust and assurance mechanisms for AI
  • Inability to source the right data
  • Human backlash against automated decision-making
  • Unintended consequences of mistaken predictions

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Case studies: Where is this trend already in play?

Warwick Analytics’ early warning and prevention system looks hours, days, and months ahead to try to predict when and how products in the field (such as aircraft and vehicles) will require maintenance. Identifying the root causes of failure helps engineers take corrective action, such as remanufacturing and redesigning products. Economic benefits can include enhanced efficiency of plant or production line, reduced energy bills, and increased product life cycle.1

Hong Kong-based venture capital firm Deep Knowledge Ventures has appointed a software algorithm, “VITAL,” to its Board of Directors. Just like other members of the board, VITAL gets to vote on whether the firm should make an investment in a specific company or not. It makes its decisions by scanning prospective companies’ financing, clinical trials, intellectual property, and previous funding rounds.2

Nexgate is a provider of Deep Social Linguistic Analysis (DSLA) technology and natural language processing (NLP) based social media risk management tools. Its major solutions scan social networks to try to discover and track an organization’s accounts; detect fraudulent social media accounts, unauthorized changes, and anomalous behavior on social account profiles; reduce potential liability from inadvertent posting of sensitive data; and demonstrate compliance with more than 35 standards and industry regulations.3

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Explore the future of risk trends:


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1 Warwick Analytics, “Industries – Manufacturing,”

2 Rob Wile, “A venture capital firm just named an algorithm to its board of directors – here’s what it actually does,” Business Insider, May 13, 2014,

3 Nexgate, “Nexgate – Overview,”; “LinkedIn selects Proofpoint’s Nexgate division for Certified Compliance Partner Program,” Nexgate, January 14, 2015,

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