Tag Archives: risk management

How Machine Learning and AI Reduce Risk

Risk management is integral to insurance, but it’s traditionally been an inexact science. Thanks to recent technological advances, however, risk management is about to get a long overdue upgrade.

If an eyebrow is raised, it is likely because the insurance industry has been slow to adopt technology, but artificial intelligence (AI) and machine learning are making headway. The appeal in using data to predict outcomes, drive efficiency and reduce costs has sparked intrigue and curiosity. Tack on the ability to make jobs easier and facilitate claims faster, and even the biggest skeptics, those most resistant to change, are curious about how AI can be applied.

Despite the aversion to tech or potentially costly, time-consuming operational overhauls, AI systems already have been put to work in some of the world’s largest insurance organizations, where they are used to address highly specific issues that have plagued different sectors for years. Now, the time has come to consider how AI can help with risk management.

New Data, New Insights

Much of the information that risk managers value in making assessments is not readily accessible to them today. Data in claim notes, documents, images, even injured worker sentiment requires someone manually poring through files because this type of information can’t be entered or sorted in conventional systems easily. But new, AI-based systems can incorporate and analyze these forms of unstructured data. They make it much simpler for employees — even the least tech-savvy employees — to find and interpret the elements that will be the most crucial to their decisions.

See also: How Machine Learning Transforms Insurance  

Additionally, the more that AI-based systems “read,” the faster and better they learn and understand. Models that leverage unstructured data yield more accurate and detailed analysis, and, by enabling adjusters to make more informed decisions based on data, organizations can reduce the severity and frequency of claims. This makes everyone happy. The industry can move light years forward by delivering this kind of data and analysis to risk managers’ fingertips whenever they need it.

Group Analysis

Another way in which new AI-based systems can help risk managers is by analyzing data across groups. It’s far more efficient to grasp what is happening across a portfolio or set of claims when a machine generates a report vs. reading file after file to formulate an opinion. With new tools, risk managers easily can look across very large datasets to see what’s happening collectively. They can determine the macro impact instead of relying on an isolated view of a single claim. In addition to the time and resource advantages, AI-based software spots trends and outliers that cost money unnecessarily.

Collective View Vs. Limited Project Basis

AI models also are able to draw on a wealth of historical information — information that is constantly updated. This stands in contrast to the way the world of risk works today, where most analysis is conducted on a project basis. The project ends; so does data collection. Important information is often lost in the lapse between projects. Modern AI systems solve the issue by persistently refreshing to ensure updated reports can be ready on demand. The result is a much richer and more realistic picture of what is happening in an organization’s claims.

Power of Prediction

The gold for risk management, however, lies in AI-based solutions’ ability to predict outcomes. AI applies science to risk management based on an incredible number of data points that should be considered in helping teams prepare for the future. Modern systems show risk managers the behaviors that need to change, assumptions that are incorrect and what things will look like if they continue to follow the present course. This information is so important because every customer or risk manager has observed different behaviors, which shape their views and how they conduct their jobs. AI systems parse all of this behavior to give a far more comprehensive view. Systems then can alert users to adverse trends that are developing so that teams can adjust accordingly. This not only decreases the lifespan of claims but potentially can save millions of dollars.

To gain the best predictions, however, it is necessary to use a platform solution that lets users easily gather insights and create models that learn from the entire industry, not just their own data. They then apply that information to a specific customer’s data. The more data a system can analyze, the more patterns come up, yielding more precise and valuable predictions.

See also: Key Challenges on AI, Machine Learning  

Armed with an abundance of data that is simple to access and interpret, claims managers can do their jobs faster and more easily than ever. This can make a potentially huge positive impact, not only on their own organization but also on the larger sector. As machine learning and AI-based technologies mature and are more widely adopted, the industry will become more exact. Costs will drop, and efficiency will improve, ultimately helping to transform the insurance industry.

As first published in WorkCompWire.

A Renewed Focus on EERM Practices

With third-party risks on the rise, there is renewed focus on maturing extended enterprise risk management (EERM) practices within most organizations. This focus appears to be driven by a recognition of underinvestment in EERM, coupled with mistrust of the wider uncertain economic environment.

To understand the broader risk environment and provide organizations with the insights needed to effectively assess their risk and adapt processes accordingly, Deloitte recently conducted the EERM Risk Management Survey 2019, obtaining perspectives from more than 1,000 respondents across 19 countries covering all the major industry segments. Results shed light on crucial considerations surrounding economic and operating environments; investment; leadership; operating models; technology; and affiliate and subcontractor risk. More specifically:

Economic and operating environment: Economic uncertainty continues to drive a focus on cost reduction and talent investment in EERM. The main drivers for investing in third-party risk management are: cost reduction, at 62%, reduction of third-party-related incidents, at 50%, regulatory scrutiny, at 49%, and internal compliance, at 45%. Organizations urgently want to be more coordinated and consistent in extended enterprise risk management across their organization, as well to improve their processes, technologies and real-time management information across all significant risks.

Investment: Piecemeal investment has impaired EERM maturity, left certain risks neglected and hurt core basic tasks. Only 1% of organizations say they address all important EERM issues, and only a further 20% say they address most EERM issues. One of the main reasons for this maturity stall is that organizations are taking a piecemeal approach to investment – they are mostly making tactical improvements rather than investing in strategic, long-term solutions. This piecemeal approach has led to certain areas – such as exit planning and geopolitical and concentration risk – being neglected, and some organizations not doing core basic tasks well, such as understanding the nature of third-party relationships and related contractual terms.

See also: The Globalization of Risk Management  

Leadership: Boards and senior executives are championing an inside-out approach to EERM, which includes better engagement and coordination and smarter use of data. The survey reveals that boards and executive leadership continue to retain ultimate responsibility for EERM in the majority of organizations. Better engagement and coordination across internal EERM stakeholders is a top priority for boards and senior leaders. Boards are moving away from using periodically generated data to more succinct and real-time, actionable intelligence, generated online. But who has ultimate responsibility for third-party risk management? According to the survey results, 24% indicated the chief risk officer, 19% indicated other board members and 17% indicated the CEO.

Operating models: Federated structures are the most dominant operating model for EERM, underpinned by centers of excellence and shared services. More than two-thirds, 69%, of respondent organizations say they adopt a federated model, and only 11% of organizations are now highly centralized, which is down from 17% last year. Investments in shared assessments and utilities, and managed services models, are also increasing. Furthermore, co-ownership of EERM budgets is also emerging as a trend. Robust central oversight, policies, standards, services and technologies, combined with accountability by business unit and geographical leaders, is a pragmatic way to proceed.

Technology: Organizations are streamlining and standardizing EERM technology across diverse operating units. The survey confirms Deloitte’s prediction last year that a three-tiered approach for third-party risk management will continue. Smartly coordinated investments in third-party risk management technology across three tiers can drive efficiency, reduce costs, improve service levels, increase return on equity and create a more sustainable operating model. More specifically, 59% of the respondents adopted tier one, 75% adopted tier two and tier three continues to grow.

Affiliate and subcontractor risk: Organizations have poor oversight of the risks posed by their third parties’ subcontractors and affiliates. The lack of appropriate oversight of subcontractors is making it difficult for organizations to determine their strategy and approach to the management of subcontractor risk. Only 2% of survey respondents identify and monitor all subcontractors engaged by their third parties. And a further 8% only do so for their most critical relationships. Leading organizations are starting to address these blind spots through “illumination” initiatives to discover and understand these “networks within networks.” Less than 32% of organizations evaluate and monitor affiliate risks with the same rigor as they do other third parties. As affiliates are typically part of the same group, organizations are likely to have a higher level of risk intelligence on them than other third parties.

See also: Is There No Such Thing as a Bad Risk?  

For more information on Deloitte’s “2019 Extended Enterprise Risk Management Survey,” or to download a copy, please visit their website here. You can find the full report here.

TokenEx’s Alex Pezold

Alex Pezold, CEO and Co-Founder of TokenEx, talks with ITL Editor in Chief Paul Carroll about how the 10-year old company, which has been active in providing a cyber solution to the banking and payments industries, is now exploring ways to bring its data protection solution to the insurance industry. TokenEx assigns a token for sensitive data, such as a customer’s personally identifiable information, so that a company is not storing actual consumer information that is at risk in a data breach. Learn more about TokenEx.

View more Innovation Executive videos

Learn more about Innovator’s Edge

Art Fraud and Risk Management

We are all aware of numerous, infamous attempts to defraud galleries with forged paintings. We attend conferences and pay attention to this sort of a story because it is remarkable to think that anyone could trust, and breach trust, to that magnitude. Sadly, it happens every day.

Every day, there is a crate of an artwork that is sold and not reviewed for condition first. Every day, there is reliance on condition of an artwork by review of the crate alone. Every day, there is a consignment that takes place without written confirmation and transparency. This is the nature of the beast.

See also: The Globalization of Risk Management  

If you have provided insurance services to the art community for a long enough time, you will receive what is loosely referred to as a “Friday phone call.” These are the time-pressured, high-valued, too-good-to-be-true risks that absolutely, positively have to be placed by the end of the week. This is a more practical example of something that an insurance broker should be aware of as something that can affect their day-to-day life. For example, who could forget the Caravaggio in the crate that could not move until it was insured? Or the ever popular Michelangelo that came with tons of gold star stickers on the non-USPAP-compliant appraisal.

With every incoming risk, regardless of demanding time constraints, there is the need to review provided information and follow a process. It is important for brokers to take their time to examine the integrity of the information to uncover anything suspect in the submission. Some guidelines to consider when it comes to risk and art fraud related to fine art insurance submissions, include:

  • Respond logically and practically in an unemotional manner to “pressure placements”
  • Require proof that the artwork exists
  • Require proof that the artwork is authentic
  • Require proof of the value of the artwork from a credible source
  • Follow required compliance rules related to disclosure of the named insured
  • Review the credentials of the experts involved in the process as well as the credibility of the parties insured

See also: Natural Disasters and Risk Management  

Do not be dazzled or blinded by the majesty of the incoming opportunity. Our role as professionals is to pre-qualify risks for the underwriting insurance company partners with which we work. Our role as brokers is to represent the interests of an insured, and the careful selection of those parties is integral to the success of your firm.

This article is provided for general informational purposes only and is not intended to provide individualized business, risk management or legal advice

Women’s World Cup: Tips for Managing Risk

The world’s largest sporting event of the summer kicked off (pun intended) in France this month and continues through July 7. According to Reuters, more than 1.5 million supporters are expected to attend the 2019 Women’s World Cup matches in the nine cities hosting the tournament. With record-breaking attendance, the rising popularity of women’s soccer also means an increase in crowd-related risks and the need for a comprehensive risk management plan.

To ensure a safe and positive experience for all, host cities and venues must consider risks from all angles and think about how to prevent and respond to potential incidents. The responsibility for crowd safety goes beyond city and stadium officials, first responders and security staff. Members of the public – the crowd itself – also can and should take an active role in ensuring everyone enjoys the event without incident.

Risk analysis

First and foremost, city and venue officials need to identify and assess risks and have a plan ready to address them. This analysis requires total situational awareness and a thorough assessment of potential vulnerabilities, including everything from how many exits are available at the venue, to what can happen between the stadium and the parking lot, to understanding how crowds typically interact and move throughout the event.

This kind of assessment requires thinking about the event in a broader context, beyond the stadium gates and the confines of the match itself. Risks are not limited to the main location or time of an event. Attendees should remain alert before, during and after an event, as well as inside and outside the venue.

See also: The Globalization of Risk Management  

Total situational awareness encompasses:

  • Infrastructure
  • Environment
  • Crowd/human behavior
  • Emerging technologies


Host cities and stadium officials need to consider what infrastructure exists to support the event. Is there a comprehensive map of the venue that includes all the entrances and exits? Are they secured? Is there an emergency plan in place for various crisis scenarios? If so, when was the last time it was tested it?

Prior to a major event, every venue should do a practice run-through to make sure the plan is up to date. By going through the various crisis scenarios, you can identify gaps in the plan and figure out how to fill them, before an actual crisis occurs.


While security personnel are typically sufficient for the entrance into a big event, hostile attacks are increasingly occurring outside the main venue. For example, in naturally open spaces such as parking lots, perpetrators have easy access to large groups outside of the stadium’s protection. Also, think about the venue itself. Is the place/location of special significance to any group or cause? Does the timing coincide with a particular holiday or anniversary? When considering a potential attack, officials should also monitor social media, before and during an event, for clues and possible tips that an incident may occur.

Crowd/human behavior

Finding the right balance between creating a fun, entertaining atmosphere and a safe place for large crowds to gather can be tricky. On one hand, you want an open, inviting space; on the other hand, you must maintain order and some kind of control. With people from all over the world coming together, safety instructions and protocol must be visual and easy to understand. For example, emergency exits should be clearly marked and accessible. Security and other staff, such as concession workers and maintenance crews, should be trained to watch for body language, verbal cues and unusual behavior that might indicate potential threats. A “see something, say something” policy, where people are encouraged to report suspicious behavior, is helpful to enlist community vigilance to prevent incidents.

Emerging technologies

From passive surveillance to handheld apps and artificial intelligence, advances in technology are enabling a better understanding of risks. Closed-caption television (CCTV) cameras that allow a central command center to monitor crowds are widely used in venues today. Advances in facial recognition algorithms and AI enable computers to analyze faces and raise red flags when someone elicits extra scrutiny. With machine learning, computers are getting better at detecting bodies and objects in crowds. Whether it’s distinguishing between a flashlight and a firearm, crowds pushing each other and a fight, or a joke and negative intent, artificial intelligence is analyzing real-time video feeds to better identify threats.

Proactive policing and passive surveillance, such as millimeter wave technology, can identify weapons (explosives, guns or knives) with nearly 100% accuracy. Mobile apps can turn any phone into a body cam, so that all staff (from concession workers to maintenance crews) can feed images to security. Stadiums can even set up “no drone zones” with equipment that can intercept drones within a periphery and turn them around.

See also: Why Risk Management Is a Leadership Issue  

For crowd safety, some stadiums offer apps that can guide event attendees through the venue or allow them to send alerts if a family member or friend is lost. These apps can also “crowd-source” security, allowing fans to provide real-time information on potential threats to the on-site command center. Using sensors placed strategically in and around the venue, exact locations can be determined and security personnel dispatched quickly and efficiently.

Be part of the solution

Public safety is everyone’s responsibility. It takes community involvement, and being aware of and caring about the person next to you, to make a positive impact. Everyone – players, fans, stadium employees and even the public at large – plays a role in keeping the peace. Whether you’re heading to France this summer or attending some other crowded event, my advice to you is simple: Pay attention, be smart and, most importantly, have fun!