When we think of hacking we think of a network being hacked remotely by a computer nerd sitting in a bedroom using code she’s written to steal personal data, money or just to see if it is possible. The idea of a character breaking network security to take control of law enforcement systems has been imprinted in our psyche from images portrayed in TV crime shows however the real story is much more complex and simple in execution.
The idea behind a cognitive hack is simple. Cognitive hack refers to the use of a computer or information system [social media, etc.] to launch a different kind of attack. The sole intent of a cognitive attack relies on its effectiveness to “change human users’ perceptions and corresponding behaviors in order to be successful.” Robert Mueller’s indictment of 13 Russian operatives is an example of a cognitive hack taken to the extreme but demonstrates the effectiveness and subtleties of an attack of this nature.
Mueller’s indictment of an elaborately organized and surprisingly low-cost “troll farm” set up to launch an “information warfare” operation to impact U.S. political elections from Russian soil using social medial platforms is extraordinary and dangerous. The danger of these attacks is only now becoming clear but it is also important to understand the simplicity of a cognitive hack. To be clear, the Russian attack is extraordinary in scope, purpose and effectiveness however these attacks happen every day for much more mundane purposes.
Most of us think of these attacks as email phishing campaigns designed to lure you to click on an unsuspecting link to gain access to your data. Russia’s attack is simply a more elaborate and audacious version to influence what we think, how we vote and foment dissent between political parties and the citizenry of a country. That is what makes Mueller’s detailed indictment even more shocking. Consider for example how TV commercials, advertisers and, yes politicians, have been very effective at using “sound bites” to simplify their product story to appeal to certain target markets. The art of persuasion is a simple way to explain a cognitive hack which is an attack that is focused on the subconscious.
It is instructive to look at the Russian attack rationally from its [Russia’s] perspective in order to objectively consider how this threat can be deployed on a global scale. Instead of spending billions of dollars in a military arms race, countries are becoming armed with the ability to influence the citizens of a country for a few million dollars simply through information warfare. A new more advanced cadre of computer scientists are being groomed to defend and build security for and against these sophisticated attacks. This is simply an old trick disguised in 21st century technology through the use of the internet.
A new playbook has been refined to hack political campaigns and used effectively around the world as documented in an article March, 2016. For more than 10 years, elections in Latin America have become a testing ground for how to hack an election. The drama in the U.S. reads like one episode of a long running soap opera complete with “hackers for hire”, “middle-men”, political conspiracy and sovereign country interference.
“Only amateurs attack machines; professionals target people.”
Now that we know the rules have changed what can be done about this form of cyber-attack? Academics, government researchers and law enforcement have studied this problem for decades but the general public is largely unaware of how pervasive the risk is and the threat it imposes on our society and the next generation of internet users.
I wrote a book, Cognitive Hack: The New Battleground in Cybersecurity…the Human Mind to chronicle this risk and proposed a cognitive risk framework to bring awareness to the problem. Much more is needed to raise awareness by every organization, government official and risk professionals around the world. A new cognitive risk framework is needed to better understand these threats, identify and assess new variants of the attack and develop contingencies rapidly.
Social media has unwittingly become a platform of choice for nation state hackers who can easily hide the identify of organizations and resources involved in these attacks. Social media platforms are largely unregulated and therefore are not required to verify the identity and source of funding to set up and operate these kinds of operations. This may change given the stakes involved.
Just as banks and other financial services firms are required to identify new account owners and their source of funding technology providers of social media sites may also be used as a venue for raising and laundering illicit funds to carry out fraud or attacks on a sovereign state. We now have explicit evidence of the threat this poses to emerging and mature democracies alike.
Regulation is not enough to address an attack this complex and existing training programs have proven to be ineffective. Traditional risk frameworks and security measures are not designed to deal with attacks of this nature. Fortunately, a handful of information security professionals are now considering how to implement new approaches to mitigate the risk of cognitive hacks. The National Institute of Standards and Technology (NIST), is also working on an expansive new training program for information security specialists specifically designed to understand the human element of security yet the public is largely on its own. The knowledge gap is huge and the general public needs more than an easy to remember slogan.
A national debate is needed between industry leaders to tackle security. Silicon Valley and the tech industry, writ large, must also step up and play a leadership role in combatting these attacks by forming self-regulatory consortiums to deal with the diversity and proliferation of cyber threats through vulnerabilities in new technology launches and the development of more secure networking systems. The cost of cyber risk is far exceeding the rate of inflation and will eventually become a drag on corporate earnings and national growth rates as well. Businesses must look beyond the “insider threat” model of security risk and reconsider how the work environment contributes to risk exposure to cyberattacks.
Cognitive risks require a new mental model for understanding “trust” on the internet. Organizations must begin to develop new trust measures for doing business over the internet and with business partners. The idea of security must also be expanded to include more advanced risk assessment methodologies along with a redesign of the human-computer interaction to mitigate cognitive hacks.
Cognitive hacks are asymmetric in nature meaning that the downside of these attacks can significantly outweigh the benefits of risk-taking if not addressed in a timely manner. Because of the asymmetric nature of a cognitive hack attackers seek the easiest route to gain access. Email is one example of a low cost and very effective attack vector which seeks to leverage the digital footprint we leave on the internet.
Imagine a sandy beach where you leave footprints as you walk but instead of the tide erasing your footprints they remain forever present with bits of data about you all along the way. Web accounts, free Wi-Fi networks, mobile phone apps, shopping websites, etc. create a digital profile that may be more public than you realize. Now consider how your employee’s behavior on the internet during work connects back to this digital footprint and you are starting to get an idea of how simple it is for hackers to breach a network.
A cognitive risk framework begins with an assessment of Risk Perceptions related to cyber risks at different levels of the firm. The risk perceptions assessment creates a Cognitive Mapof the organization’s cyber awareness. This is called Cognitive Governance and is the first of five pillars to manage asymmetric risks. The other five pillars are driven from the findings in the cognitive map.
A cognitive map uncovers the blind spots we all experience when a situation at work or on the internet exceeds our experience with how to deal with it successfully. Natural blind spots are used by hackers to deceive us into changing one’s behavior to click a link, a video, a promotional ad or even what we read. Trust, deception and blind spots are just a few of the tools we must incorporate into a new toolkit called the cognitive risk framework.
There is little doubt that Mueller’s investigation into the sources and methods used by the Russians to influence the 2016 election will reveal more surprises but one thing is no longer in doubt…the Russians have a new cognitive weapon that is deniable but still traceable, for now. They are learning from Mueller’s findings and will get better.
Traditional risk frameworks, such as COSO ERM (1985), ISO 31000 (2009), and the Basel Capital Accord (1974) are modern inventions from the early 20th century formulated to respond to major failure in managing financial, operational, regulatory, and market risks. Traditional risk frameworks have been helpful in managing compliance risks with an emphasis on internal controls but lack the rigor to evaluate asymmetric risks that cause business failure.
It is the dead of winter in a lovely little village along the coastline of southern Maine and a sudden Nor’easter pounds New England. To escape the cold and quench their thirst three solitary figures decide to seek refuge in the only Irish pub open that night. Each of these figures has arrived, serendipitously, within 15 minutes of one another and are beginning to warm themselves near the fireplace next to the bar.
As they settle in all three decide to share a pint or two and order food before they depart along their separate journeys. Not surprisingly, one pint leads to another and before long the conversation has traversed solving world events and inevitably leads to their work and avocation.
The first figure pipes up, ”I am a mechanic! I have seven professional certifications and have been taught by master mechanics from around the world.” The second figure interjects, that’s really interesting, “I am an artist! I interpret the complex and make it simple for my audience to understand.” Without hesitation the third figure interrupts and exclaims, “I am a scientist! I research and explore the unknown.”
After several more pints of beer the conversation has grown even more verbose and an argument ensues. The artist asks the mechanic what types of mechanical repairs does she solve and the mechanic responds, “I am a risk mechanic!” I have been certified in all varieties of risks, policies and procedures, and frameworks and speak regularly on the topic around the world, says the mechanic.
At this the scientist asks the artist, “what does it mean that you interpret the complex and make it simple for your audience?” The artist says, “I study how people make decisions and help them manage risks by redesigning their work to solve complex problems!” The mechanic then elbows the artist and asks the scientist, well, what do you study? The scientist proudly explains that she is a researcher of complex risk phenomenon. I have eight patents on this topic.
As the storm outside subsides, the bartender, having overheard the arguments, has decided his three patrons have had enough to drink for one night. The bartender proposes a bet and asks the three to solve a complex risk problem with the winner’s tab paid.
Solve this riddle asks the bartender, “What does a rich man crave but can never buy? We chase it but can never find it. What makes fools of us all?”
Do you know the answer?
In this webinar we will look at cognitive security – the concept of using data mining, machine learning, natural language processing and human-computer interaction to mimic the way the human brain functions and learns – in order to help fight cybercrime.
If you spend any time on social media, viewing online news stories or read blog posts from pundits and self-described experts and consultants [present company included] you will notice that the ratio of “jargon” to information is rising rapidly. This is especially true in enterprise risk management, machine learning, artificial intelligence, data analysis and other fields where opinions are diverse because real expertise is in short supply.
This is a real problem on many fronts because jargon obscures the transfer of actionable information and makes it harder to make decisions that really matter. So I looked up the definition of “jargon”.
“Jargon: special words or expressions that are used by a particular profession or group and are difficult for others to understand.”
Well intended people use jargon to portray a sense of expertise in a particular subject-matter to those of us seeking to learn more and understand how to make sense of the information we are reading. The problem is that neither the speaker nor the listener is really exchanging meaningful information. In an era where vast amounts of misinformation is a mouse click away we must begin to speak clearly.
Critical thinking is the product of objective analysis and the evaluation of an issue to make an informed decision. However, because we are human what we believe can be based on biased information from peer groups, background, experience, political leanings, family experience and other factors both conscious and sub-conscious.
In an era where “truth” is malleable critical thinkers are more important than ever. This is especially relevant to risk professionals. The jargon in risk management is destroying the practice and profession of risk management.
Yes, these are strong words but we must be honest about what is not working. We, the collective “we”, use words like Risk Appetite, Risk Register, Risk Value, Risk Insights, or my favorite, “the ability to look around corners”; as if everyone understands what they mean and how to use these words to define some process that leads to awareness. The practice of risk management does not endow the practitioner with the ability to see the future. Done well, risk management, is the process of reducing uncertainty BUT only in certain situations!
Let’s stop expecting super human feats of wisdom in risk management that no one has ever demonstrated consistently over time.
We call risk frameworks a risk program when it is only an aspirational guide for what goes in a risk program not what you do to understand and address risks. The truth is the reason that there is so much jargon in risk management is because we know very little about how to do it well. Fortunately, the truth is much more simple than the jargon from uninformed pundits who would have you believe otherwise. Risk management is much more simple and less omniscient than the hype surrounding it. This may be disappointing to hear and many may argue against this narrative but let’s examine the truth.
Think of risk management as an Oak tree with one trunk but many branches. Economics is the trunk of the Oak tree of risk management with many branches of decision science that include the science of advanced analytics and human behavior among many others.
Economists and a Psychologist are the only ones who have ever won a Nobel Prize in the science of risk management.
Risk management was NOT invented by COSO ERM, consultants like McKinsey & Co. or applied mathematicians however many disciplines have played an active role in advancing the practice of risk management which is still in its infancy of development. Risk management is challenging because unlike the laws of physics which can be understood and modeled according to scientific methods the laws of human nature consistently defy logic. One look at today’s headlines is all you need to understand the complexity of risk management in any organization.
As the Oak tree of risk management grows new branches are needed such as data science, data management, cognitive system design, ergonomics, intelligent technology and many other disciplines. I created the Cognitive Risk Framework for Enterprise Risk Management and Cybersecurity to make room for the inevitable growth and diversity of disciplines that will evolve through the practice of risk management. It too is an aspiration of what a risk program can become. Risks are not some static “thing” that can be tamed into obedience by one approach, a simple focus on internal controls or the next hot trend in technology. Risk management must continue to evolve and so must those of us who are passionate about learning to get better at managing risks.
Let me leave you with one new word of jargon that is growing rapidly. Signal. The word Signal is being used in Big Data conversations to distinguish how to separate out the noise of Big Data from real insights to understand what customers want, identify trends and insights in data, and understand risks. How is that for a multi-jargonistic sentence?
Not surprisingly, McKinsey has jumped on this band wagon to tell the listener they too must separate the signal from the noise. Like all jargon, few tell you how only that you must do these things. What only a few will tell you is that the challenge of identifying the signal, insight, value or substitute whatever jargon you like is to develop a multi-disciplinary approach.
The cognitive risk framework for enterprise risk and cyber security was developed to start a conversation about how to begin the “how” of the evolution of risk management into what it will become not some imaginary end state of risk management.
Cognitive Hack addresses an area of cybersecurity that has not been vastly explored—the human element. Most cybersecurity authors focus on how technology can be used and/or adapted to make an enterprise’s infrastructure secure. Bone, a risk advisory consultant and an editor, aims “to introduce readers to the evolution of emerging technologies …” and to “address what some believe to be the weakest link in cybersecurity—the human mind.”
The author examines six distinct areas: understanding various vulnerabilities, exploring advances in situational awareness, “the cyber paradox,” the risk of relying solely on industry reports, delving into a hacker’s mind, and providing a “cognitive risk framework” for cybersecurity. In each of these topics, Bone uses real-world examples of security breaches and how the human element effected the severity of the breach. He also supplies ways the human element could have been mitigated in the breach, thus lessening the severity. In addition, Bone explains that cognitive hacking is in its infancy, and much work and research still needs to be completed. For those interested in the topic, he lists several areas where further research is needed.
–T. Farmer, Arkansas State University
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“Intelligent Automation” is such a new term that you won’t find it in Wikipedia or Merriam-Webster. However, we are clearly in the early stages of a technological transformation that’s no less dramatic than the one spurred by the emergence of the Internet.
A new age in quantitative and empirical methods will change how businesses operate as well as the role of traditional finance professionals. To compete in this environment, finance teams must be willing to adopt new operating models that reduce costs and improve performance through better data. In short, a new framework is needed for designing an “intelligent organization.”
The convergence of technology and cognitive science provides finance professionals with powerful new tools to tackle complex problems with more certainty. Advanced analytics and automation will increasingly play bigger roles as tactical solutions to drive efficiency or to help executives solve complex problems.
But the real opportunities lie in reimaging the enterprise as intelligent organization — one designed to create situational awareness with tools capable of analyzing disparate data in real or near-real time.
Automation of redundant processes is only the first step. An intelligent organization strategically designs automation to connect disparate systems (e.g., data sources) by enabling users with tools to quickly respond or adjust to threats and opportunities in the business.
Situational awareness is the product of this design. In order to push decision-making deeper into the organization, line staff need the tools and information to respond to change in the business and the flexibility to adjust and mitigate problems within prescribed limits. Likewise, senior executives need near-real time data that provides the means to query performance across different lines of business with confidence and anticipate impacts to singular or enterprise events in order to avoid costly mistakes.
Financial reporting is becoming increasingly complex at the same time finance professionals are being challenged to manage emerging risks, reduce costs, and add value to strategic objectives. These competing mandates require new support tools that deliver intelligence and inspire greater confidence in the numbers.
Thankfully, a range of new automation tools is now available to help finance professionals achieve better outcomes against this dual mandate. However, to be successful finance executives need a new cognitive framework that anticipates the needs of staff and provides access to the right data in a resilient manner.
This cognitive framework provides finance with a design road map that includes human elements focused on how staff uses technology and simplifying the rollout and implementation of advanced analytical tools.
The framework is composed of five pillars, each designed to complement the others in the implementation of intelligent automation and the development of an intelligent organization:
- Cognitive governance
- Intentional control design
- Business intelligence
- Performance management
- Situational awareness
Cognitive governance is the driver of intelligent automation as a strategic tool in guiding organizational outcomes. The goal of cognitive governance, as the name implies, is to facilitate the design of intelligent automation to create actionable business intelligence, improve decision-making, and reduce manual processes that lead to poor or uncertain outcomes.
In other words, cognitive governance systematically identifies “blind spots” across the firm then directs intelligent automation to reduce or eliminate the blind spots.
The end game is to create situational awareness at multiple levels of the organization with better tools to understand risks, errors in judgment, and inefficient processes. Human error as a result of decision-making under uncertainty is increasingly recognized as the greatest risk to organizational success. Therefore, it is crucial for senior management create a systemic framework for reducing blind spots in a timely manner. Cognitive governance sets the tone and direction for the other four pillars.
Intentional control design, business intelligence, and performance management are tools for creating situational awareness in response to cognitive governance mandates. A cognitive framework does not require huge investments in the latest big data “shiny objects.” It’s not necessary to spend millions on machine learning or other forms of artificial intelligence. Alternative automation tools for simplifying operations are readily available today, as is access to advanced analytics, for organizations large and small, from a variety of cloud services.
However, for firms that want to use machine learning/AI, a cognitive framework easily integrates any widely used tool or regulatory risk framework. A cognitive framework is focused on a factor that others ignore: how humans interact with and use technology to get their work done most effectively.
Network complexity has been identified as a strategic bottleneck in response times for dealing with cybersecurity risks, cost of technology, and inflexibility in fast-paced business environments. Without a proper framework, improperly designed automation processes may simply add to infrastructure complexity.
There is also a dark side to machine learning/AI that organizations must understand in order to anticipate best use cases and avoid the inevitable missteps that will come with autonomous systems. Microsoft learned a hard lesson with “Clippy,” its Chatbot project, which was shelved when users taught the bot racist remarks. While there are many uses for AI, this technology is still in an experimental stage of growth.
Overly complicated approaches to intelligent automation are the leading cause of failed big data projects. Simplicity is the new value proposition that should be expected from the implementation of technology solutions. Intelligent automation is one tool to accomplish that goal, but execution requires a framework that understands how people use new technology effectively.
Simplicity must be a strategic design imperative based on a framework for creating situational awareness across the enterprise.
James Bone is a cognitive risk consultant; a lecturer at Columbia University’s School of Professional Studies; founder of TheGRCBlueBook.com, an online directory of governance, risk, and compliance tools; and author of, “Cognitive Hack: The New Battleground in Cybersecurity … the Human Mind.”
To see the post in CFO magazine click the link above
This marcus evans event will enable banks to establish an effective IRRBB framework to gain competitive ground. The meeting will explore how banks can steer the balance sheet to defend against interest rate risk sensitivities, advancements to systems and behavioural models under the IRRBB, developments in the IRRBB EBA guidelines and stress testing requirements and the separation between the banking and trading book.
In my previous articles, I introduced Human-Centered risk management and the role that Cognitive Risk Governance should play in designing the risk and control environment outcomes that you want to achieve. One of the key outcomes was briefly described as situational awareness that includes the tools and ability to recognize and address risks in real time. In this article, I will delve deeper into how to redesign the organization using cognitive tools while reimagining how risks will be managed in the future. Before I explore “the how” let’s take a look at what is happening right now.
This concept is not some futuristic state! On the contrary, this is happening in real-time. BNY Mellon, one of the oldest firms on Wall Street has started a transformation to a cognitive risk governance environment. Mellon is not the only Wall Street titan leading this charge. JP Morgan, BlackRock, and Goldman Sachs are hiring Silicon Valley talent among others to transform banking, in part, to remain competitive and to strategically reduce costs, innovate and build scale not possible with human resources. The banks have taken a very targeted approach to solve specific areas of opportunity within the firm and are seeking new ways to introduce innovation to customer service, new product development and create efficiencies that will have profound implications for risk, audit, compliance and IT now and in the foreseeable future
As these early stage projects expand the transformation that is taking place today will position these firms with competitive advantages few can anticipate. I do not know the business plans of BNY Mellon, JP Morgan, BlackRock or Goldman Sachs but it is safe to say that each of these firms will see the benefits of implementing targeted solutions with smart systems to augment decision-making and drive growth. They may also reduce risks in the process. However, as these firms grow their smart technology portfolio it will become obvious that a strategic plan must include an overarching Cognitive Risk Governance program that goes deeper than IT efficiencies, investment management and one-off cost savings in contract reviews. I applaud the approach these firms are taking but these are low-lying “tactical fruit”, but one must start somewhere!
The real question is what role will risk management, audit, and compliance play in this new cognitive risk era? Will oversight functions continue to be observers of change or leaders in change with a risk framework that contemplates an enterprise approach to smart systems? Will oversight functions seek opportunity in this new cognitive risk era or choose to ignore the growth of these advances?
The Cognitive Risk Framework for Enterprise Risk Management has been presented in earlier articles as a set of pillars that include human elements integrated with technology because technology alone is not enough! Smart systems will reduce costs, in some cases, redundant staff and in other cases reduce the need to add people to build scale and more. However, without a more comprehensive approach the limits of a technology-only strategy will become obvious as soon as the cost savings decline.
If firms truly want to create a multiplier effect of cost savings and scale the transformation must include technology that assists humans to become more productive!
If operational and residual risks represent the bulk of inefficient bottlenecks or have limited a firm’s ability to respond quickly to changes in the business environment a well-designed cognitive risk framework offers firms the ability to free up the back and middle office environment. How so?
Introduction to Intentional Control Design, Machine Learning & Situational Awareness
First, automation trumps big data analytics!
I know that Big Data, Predictive Analytics, Machine Learning and Artificial Intelligence sound sexy, seems cool and is the future! But let’s work in the real world for a moment. Google has made great advances in machine learning but if you actually take the time to read their research literature (since about 1% or less of the pundits do) you will find that the actual use cases have been limited. The real opportunities involve routine processes with very large pools of data that is well defined.
You can’t teach a machine to be smart with dumb data
If you have unlimited resources or simply want to throw away money then start a Big Data project with unstructured, random data! Some may argue the benefits of this approach but consider this. Most firms produce petabytes of structured data every single day in production environments that are rarely leveraged to its full capacity. Why not start with a good data source, automate the processes that produce this data to assist humans in getting their jobs done more efficiently? Want to ensure internal controls work flawlessly? Automate them! Want to ensure compliance with regulatory mandates? Automate it! Want to produce real-time audit sampling and monitoring? Automate it!
Design the risk, compliance, IT and audit outcomes that you need! Intentional Control Design takes advantage of machine learning in the most efficient manner through the corpus of data that exists in production data.
Once you do that you have your big data projects solved! Need audit data to test compliance? Done! Need risk assessments with real data? Done! Need to check fraudulent activity? Done!
If you want to create situational awareness for how your firm is operating in real time design it! Automation trumps Big Data analytics, but most get this backwards!
Unstructured data requires human annotation, which increases costs exponentially so why start there? It may not be sexy but the money that you save will make you feel better than the money you lose chasing the glamor projects that add little value.
Automation gives you situational awareness through true transparency! Transparency gives the Board and senior management the ability to adjust in a more timely manner. If you want a no surprise business environment consider designing one……. It doesn’t happen by accident nor does it happen by threatening staff to not make mistakes!
Cars are safer today than 40 years ago because of design! Airline travel is safer today because of design. Amazon, Facebook, Google, and Apple have overtaken traditional business models by design!
There are a number of residual benefits that I haven’t discussed in detail yet like reduction in cyber risks, employee burnout, increased staff productivity and many more. I saved these for last because we always forget that humans are the real engines of business growth.
If you are still an unbeliever just take at look at the store closings in the retail industry by not listening to the change created by the internet and firms like Amazon. I understand that change is hard but without change it will be harder to keep up and survive in an environment that moves in nanoseconds!