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Cyber’s Human Side

People are often tired, distracted and overworked. They are bound to make mistakes, inadvertently overlook policies and procedures and have quick lapses in judgement—forgetting hours and hours of training.

Human error is a significant problem when it comes to managing cyber exposures. Most cyber surveys point to people as the root cause of a breach.

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The Information Commissioner’s Office (ICO) compiles statistics about the main causes of reported data security incidents. In its first 2018 quarterly report, four of the five top causes reported to them involved human errors:

  1. Loss or theft of paperwork – 91 incidents
  2. Data posted or faxed to incorrect recipient – 90 incidents
  3. Data sent by email to incorrect recipient – 33 incidents
  4. Insecure web page (including hacking) – 21 incidents
  5. Loss or theft of unencrypted device – 28 incidents

James Bone, author of the “Cognitive Hack: The New Battleground in Cybersecurity…the Human Mind,” will lead a RIMS webinar Aug. 23 that explores the cognitive risk framework. Bone asks: are risk professionals considering the “human element” in their cyber risk management plan?

According to Bone, “The purpose of creating the cognitive risk framework is to begin to educate risk professionals about the need to incorporate the human element into their risk programs, to identify areas where human error or lapses can cause significant damage, and then design effective solutions.”

Bone points to the airline and automotive industries as examples where the value of human element risk management planning has already been realized. “Automation in cockpits, navigation systems, lane assistance technology and, even something as simple as the seatbelt demonstrate organizations’ and industries’ attention to human error risk mitigation.”

“All of us have a limit in our ability to work and focus at a very detailed level for long periods of time,” Bone said. “The ability to design a work environment that simplifies the work that people do will help reduce risk.

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And, while human error is a piece of the cyber risk management puzzle, it isn’t the only human element cyber concern. Human routine, tendencies and employee processes are constantly monitored by cyber predators. “A sophisticated hacker can spend up to 18 months to two years setting their strategy to attack your organization,” he said. “They are studying the rhythm of the workflow and the movement of data across the firm. They gain a tremendous advantage by just sitting silently and watching.

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Implementing a cognitive risk framework is no easy task. The key is data. “A lot of data is mislabeled, making it difficult for risk professionals to see the connection between an end result and the human behavior that caused it. In order to use data to its fullest, it needs to be properly categorized with descriptors that allow risk professionals to be able to leverage it,” Bone said.

Organizations with risk frameworks that fail to incorporate the human element are, in his opinion, acting on assumptions. “They are assuming people will be able to follow thousands of policies and procedures with perfect accuracy every time,” he explained. “We shouldn’t assume that people won’t be distracted at work and click on phishing emails. We shouldn’t assume that people will change their passwords as frequently as we want them to. We shouldn’t and can’t be afraid to incorporate new ideas and solutions to improve routines or, at least, make them more difficult to track.”

People are the common denominator. They are not perfect by any means, but incorporating a cognitive risk framework can be a valuable advantage that allows organizations to stay ahead of human element risks while identifying opportunities to improve processes and increase productivity.

Total Cost of Risk Drops for Fourth Straight Year, RIMS Finds

The risk management profession is proving its resiliency. Even in the face of major hurricanes, technological influence and the seemingly common threat of international trade wars, 2017 saw the total cost of risk (TCOR) decline for the fourth consecutive year, according to the 2018 RIMS Benchmark Survey, which was jointly published by RIMS and Advisen.

Despite these uncertainties, the TCOR per $1,000 of revenue continued to drop, the survey revealed, ending at $9.75 in 2017. The main drivers were declines in liability costs (8%), by decreases in property, liability, workers compensation, management liability, and professional liability costs, as well as overall risk management administration costs. TCOR is defined in the survey as the cost of insurance, plus the costs of the losses retained and the administrative costs of the risk management department.

The survey encompassed industry data from 590 organizations and contains policy-level information from 10 coverage groups, subdivided into 90 lines of business.

Advisen Co-Founder and Chief Strategy Officer David Bradford said market conditions are favorable for insurance buyers. “A competitive insurance market resulting from a chronic overabundance of risk capital strongly contributed to TCOR decreasing steadily since 2013,” he said. “Not even record catastrophe losses in 2017 could derail the downward trend.”

Key findings from this year’s RIMS Benchmark Survey include:

  • TCOR fell despite record-high natural catastrophe losses such as hurricanes Maria, Irma and Harvey, as well as wildfires and mudslides in California.
  • While TCOR per $1,000 of revenue fell for most industries, four—healthcare, government & nonprofit, information technology and consumer staples—saw rising TCOR in 2017.
  • As predicted in the 2017 survey, the percentage of companies buying cyber insurance continued its increase since 2011, ending at 65% in 2017.
  • In 2017, the percentage of companies buying cyber insurance increased to 65%. This trend has continued upward since 2011. Additionally, the cost of cyber insurance per $1,000 of revenue increased 33% from 2016.
  • The adoption of new technologies such as machine learning and blockchain, political instability in several parts of the world, globalization, terrorism and cyber threats are expected to further shape the risk landscape in 2018 and beyond.

Bradford noted that the traditional insurance pricing cycle may seem broken, but that term is more likely a new normal resulting from a more efficient insurance market. “The factors contributing to this more efficient market are varied and complex, but the upshot is that a hard market like that last seen in 2001-2002, when commercial insurance rates shot up 50 percent, may simply never occur again,” he said. “Prices may rise, but most likely they will be quickly beaten down by fresh capital flowing into the market. That is good news for risk managers.”

“As the tools, resources and technologies that facilitate the exchange of ideas and experiences continue to improve, risk management professionals have become better equipped to strengthen their risk financing programs and apply cutting-edge, cost-cutting strategies,” said RIMS CEO Mary Roth. “The year-over-year data available in the RIMS Benchmark Survey allows professionals to accurately set expectations, and achieve goals while designing competitive but fair insurance programs for their organizations.”

To order a copy of the 2018 RIMS Benchmark Survey, visit www.advisenltd.com/media/reports/rims-benchmark-survey/ or www.RIMS.org/book.

Calif. Carr Fire Claims 6 Lives

Just when it seemed like things couldn’t get any worse in California, the Carr wildfire ignited, claiming six lives so far. The fire in Northern California near the city of Redding has been burning since July 23 and is now one of the largest in the state.

Almost 90,000 acres have burned, destroying more than 500 homes and commercial buildings and damaging 135 structures. Firefighters, who are working 24- to 36-hour shifts with little rest in between, said they are making progress and are now on the offense rather than in a defensive mode.

“Although it’s too early for credible insured loss estimates, the current California wildfires could noticeably impact exposed insurers’ 3Q 2018 earnings,” KBW said in a statement today.

Wildfires are also burning in Mariposa County California. The Ferguson Wildfire has closed large parts of Yosemite National Park, the Risk Management Monitor reported. That fire began July 13 at about 8:30 p.

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m. and by July 15 had nearly doubled to 9,300 acres. By July 27 it had burned 45,000 acres and was contained 5%, according to NOAA.

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While authorities have not declared an official cause for that fire, Colin Gannon, senior data analyst at Four Twenty Seven, which studies the economic risk of climate change, said weather and environmental conditions are certainly contributing factors.

The Associated Press reported that hotter weather attributed to climate change dries out vegetation, allowing for more intense, faster-spreading wildfires. Another issue is expansion of subdivisions into previously undeveloped areas.

“There are just places were there should not be subdivisions,” Kurt Henke, a former fire chief in Sacramento who now serves as a consultant to fire organizations told the AP. “We’re not talking about a single family who wants to build a house in the woods.

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I’m talking about subdivisions encroaching into the wild land urban interface that put them in the path of these destructive fires.”

Henke said that more funding needs to come from the state legislature to position firefighters in areas where conditions are ripe for fast-moving fires—so they can be respond quickly if a blaze breaks out.

Gov. Jerry Brown said last year that drought and climate change mean California faces a “new reality” where lives and property are continually threatened by fire.

The state is experiencing longer periods of warm temperatures and dry conditions that are making major fires nearly a year-round possibility, said Daniel Swain, a climate scientist at the University of California, Los Angeles.

On July 28 President Trump signed an emergency declaration for California and authorized federal aid for disaster relief.

Why Visibility Into Contracts is Crucial for Procurement Pros

Risk is a topic of pervasive and growing concern in supply and sourcing management. Procurement itself is no longer just about acquiring products and services for the best price and controlling expenses. Instead, purchasing and supply professionals are under tremendous pressure to drive out costs and ensure that procurement strategy is in line with wider business objectives, including how personally identifiable information is handled.

That scrutiny means that the procurement function is often the external face of an organization, especially today’s competitive enterprise, acting as an early-detection system for spotting anything that might represent a financial legal, or reputational risk. As a result, they are not only tasked with, but also relied upon, to give executives the analytics and guidance they need to make better business decisions. It means also that they are a crucial player in understanding and revealing legal and regulatory exposure, while providing stakeholders with useful intelligence for achieving broader strategic goals.

The fact is, access to more and better information changes how we think about and act upon that reconnaissance. While a procurement team’s performance, alongside their suppliers, can have a major impact on the revenue and profitability of any business, effective procurement and with it, better risk management, requires the right technology.

The enterprise can positively change how it manages exposure throughout the procurement lifecycle based on contract analysis, and by managing and optimizing the supply base through the aggregation of suppliers and their contracts into a single system, a 360-degree view into supplier information, capabilities, risk and performance can be created.

Contract analysis as opportunity
Generally, when we think about risk management in the enterprise, the accepted school of thought would be how to control it. But what if we instead looked to properly identify risk as a tactic for finding more revenue? The most powerful thing is to see how risk translates into lost revenue, or perhaps more importantly, new-found revenue opportunities.

There is a lot of talk about the seismic changes that AI will bring, and the prospects for self-driving cars, home robots, and all manner of time and labor-saving applications are truly staggering. However, it is the more prosaic application of AI through text analytics (enabled by the marriage of machine learning and natural language processing) that is driving the most successful applications of AI in business right now.

Contract management and analysis has emerged as, perhaps, the most important shift in the work undertaken by commercial and procurement teams in a modern business. Historically, manual contract review took months or even years to complete, if it was done at all. The new demands placed on procurement and supply management teams requires that they look to technology to automate the process.

Contract analytics, which is most effectively being driven by the application of machine learning-based decision-science and AI, has become central to efficient contract servicing and risk management. In short, data sophistication is now essential to competitive excellence, but more importantly should be central to how risk is identified as a strategy towards profitability.

A better view of the heat map
Imagine a heat map of your organization that points out where different liabilities exist and indicates the risk level of each of these liabilities. This is analogous to the application of advanced analytics to contracts within the enterprise, where the identification of non-standard language or clauses, and how far they deviate from the standard, are a primary objective. This requires far more than a static database with reporting capabilities–it demands accurate, dynamic, real-time intelligence that can only be derived from AI-driven methodologies.

A clear view of your contracts will not only provide you with the analytics and guidance needed to make better business decisions, but also better manage management.  Contract analytics and discovery systems can uncover hidden opportunities to rationalize suppliers, negotiate better deals, and take advantage of incentives.

Every organization has its own appetite for risk. Assessing a company’s risk profile is the first step toward applying right-fit contract analytics that give a view of contracts at scale and provide a heat map of potential risk exposure. Without this assessment, it is hard to take a holistic view of the entire contract corpus, and with it a comprehensive understanding of, for example, service-level agreements and uptimes, non-standard conditions and terms, and whether or not liabilities are covered by insurance.

Considering that figures from the International Association for Contract and Commercial Management (IACCM) indicate that businesses typically waste between 4% and 9% of total spend, the result of applying contract analysis to the procurement and supply management process is sobering. Based on the lower end of IACCM’s estimates, a company with an annual spend of $1 billion is losing $40 million. Should the procurement team successfully identify half of that loss, and just 50% of that figure is actually recoverable, it translates into a potential savings of $10 million.

In particular, contract analysis has been used by the enterprise in a powerful way for non-standard clause detection. Non-standard contracts constrain organizations under the best of circumstances. Vague or complex contract language, on which an organization can base many key business decisions, is a central factor in choosing between alternative courses of action. This “what if” evaluation of risk is always viewed by supply and procurement professionals as an aspect of business operations that must be properly managed within a tolerable range. This contribution to the resilience of the overall procurement process also ensures smooth and more predictable financial performance.

On the M&A side, for instance, the challenges and opportunities can be enormous. When an enterprise subsumes a smaller player, it may sample and review a set of contracts during the due diligence phase to assess obligations and risk exposure. Manual reviews or analysis using insufficient technologies, such as archaic contract lifecycle management systems that were never meant for this task, typically sample just a fraction of the overall contract portfolio–and thereby just a fraction of the overall risk–the organization could inherit through the deal.

Monitoring and managing risk is costly
Real and powerful insight can only be extrapolated from data at scale. But still, the point is not simply to mechanically extract as much data as possible from the contract corpus, but to apply it in the context of the business so that heat maps of risk are tailored to the risk assessment itself.

Better risk management of buy-side and sell-side contracts, and other legal agreements such as non-disclosure agreements and leases, requires that the analysis tools are able to learn an organization’s specific languages and clauses, and can be trained to search for specific elements, regulatory issues, and, yes, even non-standard clauses. This can only be achieved through machine learning techniques in AI.

When that risk consumes mission-critical resources, the cost is even higher, yet too many organizations remain unaware of the value that contract analysis can bring to the procurement process. That is why risk management must be well-understood by procurement teams, in particular, including a clear view of the technologies that can be implemented with minimum cost and high impact. With the application of AI to contract analysis, exposure to risk can be minimized and the impact of a potentially catastrophic event can often be avoided altogether.