Category Archives: Risk Management

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RIMS Risk Forum 2018 India Kicks Off In Mumbai

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MUMBAI – The inaugural RIMS Risk Forum 2018 India launched on November 13, and leading risk professionals from India and Asia-Pacific countries met for two days to address the challenges facing companies in the region. In a country of 1.3 billion people, expectations are for India’s risk management profession to grow, though some presenters acknowledged the proactive need to fill a potential talent gap.

During the opening keynote address, Dr. Viswanathan Ragunathan, CEO and general manager of the Varalakshmi Foundation said that examining the role of risk in Indians’ behavior and culture will initiate the dialogue among students and aspiring professionals.

“We are obviously a contradiction,” he said. “We are, at once, eternal optimists and fatalistic. At one level you can relate to what I’m saying in that Indians do not take too much risk in their day-to-day lives. Yet anyone who has taken the Mumbai trains knows…it’s almost as if we have a death wish.”

Ragunathan also discussed approaches he tends to use to assess risk, including viewing them in a VUCA environment (volatility, uncertainty, complexity and ambiguity), where one weighs how much of a situation is known against the results of controllable actions and their predictability.

“The management of volume,” he said, is ultimately at the heart of India’s challenges, and that issue is exacerbated by interconnected risks, such as a dense population and struggling infrastructure. He proposed transparency and broad communication within the Indian risk management community as starting points for solutions.

“The risk manager who understands the risk but does not share it widely does not help,” he said.

As the forum progressed, ISO31000 implementation, natural disasters and resilience, infrastructure, risk frameworks, data storage and diversity hiring practices were some of topics that received special focus on Tuesday.

“The State of Risk Management in India” was a Marsh-led panel on the findings from the newly-released, India-wide survey on risk management practices co-conducted by RIMS. The report found that risk managers are a crossroads in India, where they can assume greater leadership roles that transcend just compliance and insurance matters and can expand their knowledge base, hone their skillsets and gain access to best practices, tools and technology.

During “Thinking About Thinking in Risk Management,” Peter Young, PhD of the University of St. Thomas’ Opus, discussed the major questions facing risk managers today. He discussed how, according to his findings, experience rises dealing with uncertainty – as opposed to risk – as one looks further up on the corporate ladder.

“Risk is uncertainty when you have the capacity to measure it, and when you get to the executive suite you hardly ever deal with risk at all because you’re responsible for the strategy,” he said. “I would submit that’s broadly true among organizations at all levels. We are little ships bobbing in a big sea of uncertainty.

“[Executives] can bring a level of comfort operating in an environment of uncertainty. That turned out to be only partly true, but we think it’s an abiding truth that is slowly revealing itself.”

“Diversity in Corporate India” inspired some spirited discussions about how women’s voices and the concept of assumption are emerging as integral parts of hiring practices throughout organizations in India. Panelists were Ragunthian, Praveen Gupta, CEO of Raheja QBE General Insurance Co., and Carissa Hickling, Talent Acquisition Strategy and Technology Global Consultant for Siemens Technology India.

They spoke of how efforts to better represent women have progressed. Additionally, gay and lesbian communities are experiencing a new level of acceptance now since September, when the Supreme Court of India ruled parts of Section 377 – which was introduced in 1864 – was unconstitutional for criminalizing homosexuality. The panel agreed that while talent itself should win above all else, they acknowledged that it was a sign of progress for the nation and should be thought of as such by its corporate sectors. Hickling explained how Indian companies can now use be more open-minded in their hiring and promotion practices.

“When we look at onboarding plans and organizations, these are the moments of truth,” she said. “We can have conversations about making a small change to our HR system because this is an opportunity to change the first impression of our organization.”

She added that Siemens leadership is taking the initiative to recognize same-sex partners when discussing health benefits and taking the progress a step further extending the welcoming to transgender workers. “This is all happening very fast,” she said, “but it is a time when an organization can demonstrate that this is a time when this does matter.”

For more coverage of the forum, visit Risk Management Monitor’s Q&A with Shankar Garigiparthy.

Live RIMScast coverage of the forum is also available. Download Speaking with Leaders in Risk Management Part I and Part II.

And exclusively for RIMS members, download Peter Young’s audio live from Mumbai: Thinking about Thinking in Risk Management: New Skills for the Future.

Updates to PIPEDA, Canada’s Own GDPR

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The Office of the Privacy Commissioner of Canada released new breach reporting requirements for businesses last week.

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Updates to the Personal Information Protection and Electronic Documents Act (PIPEDA), which became law in 2000, will impact private-sector organizations that operate or do business with Canadian customers. The federal privacy law establishes ground rules for how businesses must handle personal information in the course of commercial activity, mandating that organizations must obtain an individual’s consent when they collect, use or disclose the individual’s personal information.

PIPEDA is similar to the European Union’s General Data Protection Regulation (GDPR) since it requires Canadian companies to alert customers any time their personal information may have been compromised.

“The number and frequency of significant data breaches over the past few years have proven there’s a clear need for mandatory reporting,” Commissioner Daniel Therrien said. “Mandatory breach reporting and notification will create an incentive for organizations to take security more seriously and bring enhanced transparency and accountability to how organizations manage personal information.”

A statement from the commissioner’s page lists, in brief, the new regulations for organizations subject to PIPEDA:

  • Report to the Privacy Commissioner’s office any breach of security safeguards where it creates a “real risk of significant harm;”
  • Notify individuals affected by a breach of security safeguards where there is a real risk of significant harm;
  • Keep records of all breaches of security safeguards that affect the personal information under their control; and
  • Keep those records for two years.

Commissioner Therrien called the regulations “imperfect but a step in the right direction.”

He also raised concerns that the reporting requirements fall short in that, for example, they don’t ensure the breach reports to his office provide the information necessary to assess the quality of organizations’ safeguards. As well, the Canadian government has not provided the Privacy Commissioner’s office with resources to analyze breach reports, provide advice and verify compliance. The Canadian government has established that the confidentiality of information was not respected regarding those customers who take the viagra medicine. As a result, the office’s work will be somewhat superficial and the regime will be less effective in protecting privacy.

According to the PIPEDA information page:

The individual has a right to access personal information held by an organization and to challenge its accuracy, if need be. Personal information can only be used for the purposes for which it was collected.

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If an organization is going to use it for another purpose, consent must be obtained again.

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Individuals should also be assured that their information will be protected by appropriate safeguards.

Additionally, a privacy toolkit is available here for organizations to use and assess if it adheres to PIPEDA responsibilities.

How to Use ODG Data to Improve Workers Comp Case Management

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Regardless of whether or not their organizations operate in states where the use of Official Disability Guidelines (ODG) has been adopted/mandated, risk managers can often leverage ODG data and the claim data from their risk management information systems (RMIS) to benchmark the medical and lost-time components of their workers compensation costs against national averages.

With its origins dating to 1995, ODG (www.mcg.com/odg) provides “unbiased, evidence-based guidelines” and analytical tools designed to “improve and benchmark return-to-work performance, facilitate quality care while limiting inappropriate utilization, assess claim risk for interventional triage, and set reserves based on industry data.”

The following are some ways risk managers can use ODG data in conjunction with their existing risk information tools to drive improvements in their workers compensation case management and achieve greater precision in loss reserve practices.

  1. Examine the data. ODG has a wealth of data that can be used to benchmark estimated incurred financials and return to work (RTW) best practices by job class, state, injury diagnoses, and numerous other confounding factors (e.g., obesity, diabetes, etc.). You can benchmark guidelines against both current and historical workers compensation claims to identify potential issues and opportunities for individual case management or program improvement. To evaluate trends, you need to capture and analyze detailed data on historical losses (a core capability of RMIS technology). Meanwhile, improving decision-making on open cases calls for the ability to track individual financial and treatment developments on a real-time basis. That is where your RMIS or claims administration platform combined with data streaming from your TPA or carrier can be keys to success.
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  2. Be specific. When looking at historical loss trends and comparing them broadly to ODG loss and recovery data, the sharper your focus, the faster you will be able uncover issues and make needed adjustments to improve individual outcomes or overall practices. Scrutinize data by individual location, job function, injury and even body part involved to get meaningful insights that yield specific action steps and measurable improvements.
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  3. Track open claims. Leverage the analytics from ODG to compare progress of specific cases against the statistical ODG guidelines. This will enable you to spot variances in recovery timelines and make reasonable adjustments to individual return-to-work plans.
  4. Set goals. You may want to start the benchmarking process with job functions or locations that have historically been the biggest drivers on total cost of risk. Conduct an analysis of historical claims against aggregated ODG data, identify significant variances in your practices versus ODG results, and target specific improvements in open cases. Monitor overall results on a quarterly basis to assess your progress and make any midstream adjustments to align your practices more closely to the ODG findings.
  5. Get help. ODG offers participants training through frequent webinars and other educational events. At the same time, RMIS providers can offer prescriptive guidance in automation that help clients optimize their workers compensation claims operations and return-to-work programs, including the adoption of the analytics available from ODG.

While there are many options available for employers to use predictive analytic benchmarks with workers compensation claims to drive improvements, ODG provides one of the most widely adopted measurements for tracking actual costs of injured employee cases and the success of return-to-work initiatives. When these resources are used in conjunction with a contemporary RMIS, risk managers can gain visibility into claims management issues, focus on improvements that accelerate recovery of injured employees, and start lowering the total cost of workers compensation risk.

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Using Adaptive Behavioral Analytics to Detect Fraud

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While fraud threats are nothing new for payments processors and financial institutions, the degree and magnitude of such incidents have escalated in recent years. A February 2018 Javelin study found that nearly 16.7 million consumers were victims of identity fraud in 2017—up 8% from the previous year.

Fraud prevention solutions must be flexible and sophisticated enough to not only counteract increasingly-savvy fraudsters, but also distinguish true fraud from false positives, which occur when genuine activity is mistakenly treated as fraud. According to CreditCards.com, four out of five blocked transactions are actually genuine, and these misunderstandings often result in customers being locked out of their accounts. In many ways, the aftermath of false positives can prove more damaging and costly than an actual instance of fraud, as institutions miss revenue generation opportunities while simultaneously hindering customer loyalty and trust.

As consumer payment technologies evolve, so too will the complexities of fraud detection and mitigation. Therefore, it is vital that risk management teams end their reliance on rigid, manually-programmed rule sets or static machine learning models and instead capitalize on the advanced capabilities offered by today’s more versatile tools. By modernizing their fraud strategies with adaptive behavioral analytics, payments processors and financial institutions can better mitigate risk and increase revenue.

How Does it Work?

Unlike the static machine learning of the past, adaptive behavioral analytics are extremely proficient at differentiating between actual fraud and activities that appear suspicious but are ultimately genuine. As a result, friction in financial services and e-commerce is significantly reduced and customers can maintain confidence in their preferred transaction method.

Adaptive behavioral analytics empowers machine learning through a set of sophisticated, automated, self-learning algorithms that review account activities and notify security teams of anomalies.

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These algorithms construct baseline behavioral profiles to reflect a customer’s activity type and frequency. In every interaction—regardless of if a payment occurs—information is gathered and evaluated on the type of device that is used, how it’s used, its location and the amount of the purchase. Combined, these behaviors create a customer portrait that becomes increasingly more accurate over time. Every subsequent interaction then can be measured against the behavioral portrait, within milliseconds, to determine if their activities are fraudulent or genuine.

For example, if a user logs into his or her account at an abnormal rate or suddenly begins adding priority shipping to high-priced orders, the system will detect the irregularity and block future activity. However, if a user simply purchases an expensive holiday gift or books travel arrangements—behaviors that coincide with seasonal activity—the system will recognize and differentiate the fraudulent from the legitimate accordingly.

Adaptive behavioral analytics also optimizes the speed and convenience of fraud detection by processing volumes of data and delivering critical intelligence accurately and immediately. Through this more comprehensive investigation, the software enhances the customer profile to better understand and recognize behavioral trends—a welcome sight for security teams that previously spent hours sifting through reports to locate red flags.

Where Can Adaptive Behavioral Analytics Help Most?

The ubiquity of mobile technology has created a consumer audience who prefers to conduct business through a smartphone, tablet or another device that eliminates a trip to a physical store or bank branch. In turn, these consumers demand leading-edge mobile technologies that are intuitive, convenient and offer a full range of services.

The combination of the U.S. adoption of the EMV standard in 2015 and the rise in e-commerce has escalated the volume and prominence of Card Not Present (CNP) fraud. Whether through online purchase portals or apps that access mobile wallets, the digital entry of account information raises the likelihood of a person’s information becoming compromised.

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With more transactions taking place, the volume of both true fraud activity and regular behaviors that appear suspicious will increase. However, adaptive behavioral analytics enables a more refined detection between the actual fraud and genuine activity.

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It is the best of both worlds: a much-needed, innovative line of defense that combats payments fraud and clears a path for more revenue-generating transactions.