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“Why Excel is just not good enough” – Part 1

blog
3 min read

Introduction

I was on a call the other week with the Enterprise Risk Manager of a relatively sizable multi-national corporation (over 20,000 employees across a few hundred locations on nearly every continent), and she said something that got me thinking.

She said, “For us, right now – Excel is good enough.” I responded by saying that “I understood,” we discussed a few other topics on the call and hung up.

It wasn’t until afterwards that I realized how much her view about Excel took me aback. As an enterprise software sales professional, I believe in companies moving to automation. But the reason the statement took me aback was because I realized that this might be a common mindset across many people and firms.  How many other people think, “Excel is good enough”?

A Senior Manager on my team, Mark Winey, was also on the call. After the meeting we spoke, and he reminded me that one of my first roles was in Operational Risk Reporting and Monitoring (R&M), so I should be able to understand their perspective. I began to reflect on this.

Earlier in my career, my team had built out the firm’s first op risk and control R&M function completely manually in excel. Part of my role was to spend the first few hours of the day updating spreadsheets with additional information for the metrics I was tasked with tracking. We had defined thresholds of red, amber, and green based on a formula we created using standard deviations, and when those thresholds were breached, we needed to escalate.

Once I was done compiling the additional information, the next few hours were spent chasing on threshold breaches and gathering commentary around root cause and resolution. When that was finally complete, I would spend the vast majority of the rest of my day consolidating the prior month’s end reporting. This then went on for about 3 weeks until the “Month End Report” was done. At this point, we would reach out to executives in order to have meetings scheduled on their calendars; this took another 3 to 4 weeks before we could meet and present the report.

This brief narrative reveals two important insights:

First, and perhaps the more obvious insight, is that by the time we finally met with executives, the data was at least 45 days stale! This was in 2009 and we all understood the importance of accurate, real-time data; however, every month, as things stood, we were always looking in the rear view, and pretty far behind, at that.

Second, and this is the implied insight, I spent the smallest portion of my time thinking critically about the data. As an analyst, by definition “a person who analyzes or who is skilled in analysis (thank you Google, analyst),” I spent very little time actually analyzing. This was counter-intuitive to me – I was getting paid to dig-in and think critically, but most of the time was spent on redundant manual efforts.

I’d like to estimate some numbers to illustrate how concerning this should be as risk practitioners. Let’s start with the assumptions that on average there are:

  • 8 working hours in a day
  • 5 days in a week
  • 4 weeks in a month

After factoring out lunch, holidays, vacations, etc., these assumptions should be fairly accurate. I didn’t document the precise time I spent on every activity, but let’s say that for the first 3 weeks of the month my day consisted of:

  • 2 hours of updating spreadsheets
  • 2 hours of reaching out on breaches
  • 2 hours of month end reporting
  • 2 hours on administrative tasks (meetings, emails, phone calls, etc.)

My day looked exactly the same for the last week of the month, except for this key difference: I now had 2 free hours a day since the “Month End Report” was complete!

In an interview a client of ours said, “We see the GRC Program really enabling the commoditization of the existing compliance activities and governance activities, so that managers have time to think about what’s the next risk, and really use intellectual capacity to manage risk going forward.” Given the manual approach described above, as an analyst I would have spent 6.25% of my time thinking about “the next risk” and “managing risk going forward.” After reading this, does 10 hours a month seem like an adequate effort for risk analysis? Do you still think Excel is good enough?

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Blogs

Growing Data Privacy Concerns, Continued Cyber-Attacks, and the Failure of Audits to Detect Frauds: Q1 of 2018 Ends on a Less-Than-Savory Note

blog
3 min read

Introduction

With a major data privacy scandal involving Facebook, a crippling ransomware attack on the City of Atlanta in the US, and a $2 billion fraud at Punjab National Bank in India, we take a look at some of the biggest news stories that have dominated the GRC space in the first few months of 2018.

The Data Privacy Conundrum: Facebook and Cambridge Analytica

Mark Zuckerberg, Facebook’s CEO, recently testified before Congress on the alleged harvesting of personal data by Cambridge Analytica – a third-party data analytics firm – to influence the 2016 US elections.

The scandal, which reports say involved the personal data of more than 70 million Americans, has led to a public outcry, prompted #deletefacebook, and shaved off over $80 billion from the company’s stock value since the incident was uncovered. The social media giant may also be at risk of hefty fines for possibly violating an FTC privacy deal.

With public trust in Facebook diminishing, the company has had to postpone the launch of its smart speaker for a “better time.”

Atlanta Cybersecurity Incident: Cyber-Attacks Continue to Grow More Potent

After WannaCry and NotPetya last year, cyber-attacks have intensified – this time, it was the City of Atlanta in the US that was the victim. The attackers, who reportedly hobbled several internal and public services, demanded a ransom payment in bitcoins in exchange for unlocking systems. The incident was serious enough for the FBI to get involved in the investigation.

According to a New York Times report, the attack has unnerved security experts. One security intelligence analyst noted that attackers are constantly learning from their mistakes, and evolving their code before launching the next assault. With growing concerns around these issues, it isn’t surprising that the US has devoted $380 million of its spending bill to election cybersecurity.

$2 Billion Punjab National Bank Fraud in India

The news of how one of India’s richest men, who until recently was on Forbes’ billionaire list, defrauded the country’s second largest state-run bank of over $2 billion, sent shockwaves across the Indian banking sector. Nirav Modi, a diamond jeweler, and his uncle, Mehul Choksi, reportedly colluded with Punjab National Bank (PNB) officials to get credit through fraudulently issued papers. But how did one of the largest frauds in recent banking history in India go undetected for over 6 years?

As the story unfolded, reports emerged of how auditors failed to detect the scam for a long time with multiple audits failing to raise an alarm. The fall-out of the scam has led to the creation of the National Financial Reporting Authority (NFRA), a new watchdog for the auditing profession with sweeping powers to act against erring auditors or auditing firms.

What Do They Mean for GRC?

A massive breach of trust at one of the biggest names in Silicon Valley, also a reputed social media giant, has led to public outrage, and highlighted yet again the importance of better controls for data privacy and data protection. As concerns grow over the use of personal data by companies, there are calls for more extensive data privacy laws. Europe appears to be leading the way with the General Data Protection Regulation (GDPR), but it remains to be seen if the US will follow suit.

With cyber-attacks continuing to exploit system vulnerabilities, holding governments ransom, and threatening to override democracy, there will be a renewed focus on cybersecurity and the protection of critical systems.

Meanwhile, in emerging Asian markets such as India, recently plagued by scandals and scams, we are likely to see the beginning a new era of not just regulations, but also of increased scrutiny and enforcement.

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Governance, Risk, Compliance and the Big Data Advantage

Governance
3 min read

Introduction

According to a leading IT firm research nearly 90 percent of the data in the world has been produced in just the last two years. Though a bit of a buzz phrase these days, big data is as important as the internet itself to many businesses today, for a number of reasons. The simplest explanation of how big data benefits businesses is this: It provides the insights needed to make more confident decisions, take faster actions, improve operational efficiencies, minimize risks, and reduce spending.

The sudden emergence of the whole phenomenon around the data explosion has been the result of the pervasive use of mobile devices and the large volumes of data generated from web based purchases, mobile activities, and social media interactions. As the massive volume of data and computing platforms continues to proliferate, the absence of thorough reassessments and thinking around information processing paradigms of the past will leave today’s enterprises ill-prepared to deal with this new (IT) normal.

Enterprises have to realize the obvious fact that big data is an immensely powerful concept, and information is a strong business asset. Managing large volumes of homogenous data is something that organizations of all kinds can benefit from; spanning retail, social networking, science and research, clinical trials, CRM, operational activities, transactions and more. The real challenge for organizations today is to move beyond the data volumes and data storage obstacles to assess the true value of available data to reduce overall internal audit or compliance field work costs. The vast majority of enterprise businesses are faced with the challenge of decoding large volumes of homogenous, inconsistent, or inaccurate data — often referred to as “bad data.”

Industry analyst Doug Laney encapsulated the characteristics of big data using the three Vs — volume (the quantity of data), velocity (the rate at which data is generated and changed) and variety (the number of different data sources and types). Many are also adding characteristics such as “complexity,” “veracity” and “variability” to their understanding of the concept.

An accurate analysis of big data helps enterprises with better insights into their customers, market opportunities, growth prospects, and corporate performance. This strategic analysis of large volumes of data enables organizations to achieve higher-quality results in their own internal audit and compliance processes, thus enabling them to establish more effective governance, controls, and monitoring mechanisms.

With the skyrocketing number of transactions and evolving compliance requirements and regulations, big data analysis offers endless opportunities for enterprises to mitigate key governance, risk, and compliance issues. Just as big data analytics can lead to more targeted marketing initiatives by analyzing marketing program responses, supplier activities, customer demographics, and sales patterns, effective analysis of massive volumes of structured and unstructured data can also enable organizations in the Governance, Risk and Compliance (GRC) space to:

  • Develop strong risk intelligence to strengthen risk management and streamline regulatory compliance
  • Identify high-risk vendors/persons with multiple fraud risk indicators in accounts payable
  • Display travel and entertainment expenses of local office employees
  • Identify the best practices in the industry to effectively mitigate risks
  • Determine if control procedures are working effectively

Big data analysis should become a core component of every organization’s operations, performed on a continuous basis, spanning areas such as payment or billing transactions, payroll, social media analysis, sales, operational processes, and compliance. For many organizations, especially in highly scrutinized and regulated industries such as healthcare, finance, and insurance, big data analysis can support Enterprise Risk Management (ERM) by helping monitor risks involving loans, claims, and patient care procedures.

Simply stated, integrating big data analytics into an organization’s GRC methodology will help pave the way for a truly data-driven organization.

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Blogs

Welcome!

blog
1 min read

Introduction

Welcome to the initial entry of this blog!  In subsequent posts, I’ll discuss competitive trends I’m observing in the GRC market along with other issues that will affect GRC vendors.

Earlier in my career, I had the opportunity to work in the CRM industry and saw directly how that market grew, matured and eventually consolidated.  In many ways, today’s GRC market is similar (buyers still learning what GRC means to them, no dominant market player, little M & A activity to date) to how the CRM market appeared in the early 2000’s.

Thanks for joining and I’m looking forward to speaking with you.

Warren

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