Chris DeBrusk

A key challenge for every company is to drive increased effectiveness and efficiency in its technology function — or what we refer to as the organization’s “Technology Dexterity.” The combination of complex legacy technology issues, a move to modern, agile, cloud-enabled software development approaches and, in many industries, regulatory pressure concerning technology risk and resilience has made this challenge even more critical to solve.

In our fast-paced technological world, innovation is the lifeblood of corporations striving to stay competitive and relevant. However, a hidden menace to innovation often lurks within corporate IT infrastructures: end-of-life technology. The term "end-of-life" (or “EOL”) refers to the phase when a technology, app, or product is no longer supported by its manufacturer or vendor and cannot be easily upgraded. That makes it increasingly susceptible to security vulnerabilities over time and a key… Show more

In our fast-paced technological world, innovation is the lifeblood of corporations striving to stay competitive and relevant. However, a hidden menace to innovation often lurks within corporate IT infrastructures: end-of-life technology. The term "end-of-life" (or “EOL”) refers to the phase when a technology, app, or product is no longer supported by its manufacturer or vendor and cannot be easily upgraded. That makes it increasingly susceptible to security vulnerabilities over time and a key source of operational inefficiencies and overhead costs. Show less

It has been a week since the 2023 AWS Re:invent conference as always it was a great experience. The keynotes were extremely interesting and there were more sessions on how to leverage the public cloud effectively than you could attend in a lifetime. I’m already looking forward to next year.

At the end of the second day of Amazon’s AWS re:invent, I was struck by how public cloud has matured over the years that I have been attending the conference and working with the major hyper-scalers.

At the first day of this year’s Amazon AWS re:Invent conference in Las Vegas, many of the sessions highlighted the key challenges that companies are facing in effective adoption of public cloud infrastructure. Specifically, the topic of talent comes up constantly in discussions as a barrier that many companies are struggling to overcome as they proceed on their technology transformation programs.

Gen Zers typically practice cybersecurity measures, and yet they share data openly on social media platforms for more personalized experiences.Instead of sitting in the shadows of consumer blind spots in data privacy, corporations should consider the reputational and brand value that could be created if they step forth and clearly communicate to their customers on how they think about protecting and using their data. This includes setting clear internal policies on data privacy. A proactive… Show more

Gen Zers typically practice cybersecurity measures, and yet they share data openly on social media platforms for more personalized experiences.Instead of sitting in the shadows of consumer blind spots in data privacy, corporations should consider the reputational and brand value that could be created if they step forth and clearly communicate to their customers on how they think about protecting and using their data. This includes setting clear internal policies on data privacy. A proactive approach would not only ensure clearance from violations of government laws and regulations and protect against any reputational risks, but also instill consumer trust in the company. Show less

Actively identifying workforce requirements based on new tools and techniques and defining the skills and capabilities required to deliver is the foundation through which organizations effectively align organizational talent to strategic goals, thereby using people as the driver to transformation. And while many companies deploy performance assessment programs, few regularly look forward to identifying gaps in their workforce that prevent them from achieving strategic goals.

Since the role of the Chief Data Officer (CDO) was created in many companies a decade or more ago, its primary responsibilities have expanded beyond defining standards and supporting data governance. Yet despite this evolution, many organizations have not achieved significant business value from their data investments. There have been two major generations of the CDO function, and it is time for a third if the goal of material business impact is to be achieved.

In today’s war for talent, it is common for the focus to be on attracting talent in order to offset any attrition an organization may have experienced. While this strategy is essential, leaders must also diagnose the root of the problem and think critically about why their top talent is leaving in the first place. As tech roles touch almost every part of a business today, having the right retention strategies to combat rates of turnover is crucial. How can you ensure that your workplace is not… Show more

In today’s war for talent, it is common for the focus to be on attracting talent in order to offset any attrition an organization may have experienced. While this strategy is essential, leaders must also diagnose the root of the problem and think critically about why their top talent is leaving in the first place. As tech roles touch almost every part of a business today, having the right retention strategies to combat rates of turnover is crucial. How can you ensure that your workplace is not a constant revolving door for tech talent, and you have both an environment where technologists want to join as well as an environment where they want to stay? Based on many years of building and managing high-performing technology teams, we’ve identified four retention strategies to mitigate the risk of attrition. Show less

It is estimated that at the end of 2021, the world had nearly 27 million skilled software developers, a figure that is expected to grow to 45 million by 2030. While that might seem like an impressive number, given global demand it is almost certain to be insufficient. Nearly every analyst report published on the state of the global technology labor market indicates that there is a shortage of technologists to hire against ever increasing demand. Compounding this challenge, many companies’… Show more

It is estimated that at the end of 2021, the world had nearly 27 million skilled software developers, a figure that is expected to grow to 45 million by 2030. While that might seem like an impressive number, given global demand it is almost certain to be insufficient. Nearly every analyst report published on the state of the global technology labor market indicates that there is a shortage of technologists to hire against ever increasing demand. Compounding this challenge, many companies’ efforts around purposeful workforce planning and investment in reskilling, such as proactively identifying gaps or redeploying from within, have been limited. Show less

If you examine the application and data landscape in large companies today, you will usually find a web of interconnected platforms, databases, and applications that is extremely difficult to understand and even more difficult to safely change. For example, it is not unrealistic for a large global bank to run five thousand individual applications. Manual processes supported by end user computing tools such as Excel and Access also often number in the thousands or tens of thousands. Large… Show more

If you examine the application and data landscape in large companies today, you will usually find a web of interconnected platforms, databases, and applications that is extremely difficult to understand and even more difficult to safely change. For example, it is not unrealistic for a large global bank to run five thousand individual applications. Manual processes supported by end user computing tools such as Excel and Access also often number in the thousands or tens of thousands. Large numbers of databases and reports, often duplicates of each other, are also common. A viable estimate is that there is quarter of a trillion lines of COBOL – a coding language from 1969 – currently running in production.

The impact of all this complexity manifests in several ways, the most important of which is that it makes it extremely difficult for the organization to change, improve, and innovate. Show less

Strategic, customer-focused innovation is not possible without investing in a flexible and resilient technology environment. Yet the legacy technology in many companies limits their ability to move quickly and effectively take advantage of market opportunities. The reality is that when innovating, it can be a significant advantage to start fresh, unburdened by legacy platforms with their inherent organizational and technological inertia.

Based on client work and research, Oliver Wyman… Show more

Strategic, customer-focused innovation is not possible without investing in a flexible and resilient technology environment. Yet the legacy technology in many companies limits their ability to move quickly and effectively take advantage of market opportunities. The reality is that when innovating, it can be a significant advantage to start fresh, unburdened by legacy platforms with their inherent organizational and technological inertia.

Based on client work and research, Oliver Wyman has identified six key components that enable companies to create industry leading, innovative technical capabilities. Our Technology Dexterity framework outlines how an organization can meet aggressive goals in innovation by enabling cultural alignment across business and technology to effectively drive change. Show less

Financial-services firms, perhaps more so than most large enterprise organizations, are still encumbered by complex legacy platforms, which can impact agility and slow down time to market for new products and services. In addition, the volume of work related to regulatory changes and day-to-day processing needs is expensive and can hinder new-product innovation and improving customer service. But no-code application platforms may provide a pathway to speed digital transformation and broaden… Show more

Financial-services firms, perhaps more so than most large enterprise organizations, are still encumbered by complex legacy platforms, which can impact agility and slow down time to market for new products and services. In addition, the volume of work related to regulatory changes and day-to-day processing needs is expensive and can hinder new-product innovation and improving customer service. But no-code application platforms may provide a pathway to speed digital transformation and broaden product development. Show less

As 2021 picks up steam and we all look forward to the possibility of more normality in the second half of the year, the advancement of technology within mid and large corporations not only doesn’t show any signs of slowing down, but it is likely to continue to accelerate in a number of areas. We consider fifteen of the key technology trends and what we are likely to see during the rest of 2021 and into 2022 and make some predictions as to where they are headed.

Companies supporting their business teams by deploying so-called no-code software development platforms have been installing simpler apps faster, enabling them to keep up with changes occurring at a previously unthinkable pace. Such tools give nontechnical users the ability to build applications without writing a single line of code.

Since the birth of agile in 2001, there have been predictions about the demise of the project manager role. Arguments tend to revolve around the concept that smaller, more focused teams executing lighter-weight software development processes would be able to self-organize around a defined set of goals and would no longer need someone dedicated to a process management role.

Does that mean we can eliminate the project manager role when planning a transformation? Probably not, although the… Show more

Since the birth of agile in 2001, there have been predictions about the demise of the project manager role. Arguments tend to revolve around the concept that smaller, more focused teams executing lighter-weight software development processes would be able to self-organize around a defined set of goals and would no longer need someone dedicated to a process management role.

Does that mean we can eliminate the project manager role when planning a transformation? Probably not, although the role does need to change to remain relevant in our new agile change world. Show less

Our clients are being forced to navigate their organizations through some fairly significant changes in their capabilities, organizations and markets. In our latest report, we discuss how firms that succeed in incorporating change risk management into processes and culture will become more agile and more resilient, while firms that lag will run the risk of being caught flat-footed when the next disruption arrives.

Financial institutions are ramping up their efforts to leverage artificial intelligence (AI) and machine learning to create competitive advantage to better serve customers and realize more efficient operations. Tailored product recommendations, seamless customer on-boarding and support, near-instant underwriting and pricing decisions, secure identity verification and real-time fraud detection are just a few of the many areas where financial institutions are experimenting with AI.

Building complex machine learning models has never been simpler. Thanks to software offered by companies like Amazon Web Services (SageMaker), Microsoft Azure (Machine Learning Studio), DataRobot and RapidMiner, users just need to point to their dataset, specify their objective, and the wizard-style software takes care of the rest. No coding required. But what does this mean from a risk perspective?

As the adoption of applications that leverage complex machine learning grows, so do concerns about our ability to understand and explain decisions made and actions taken by machines. This concern has been particularly pronounced in areas where this lack of understanding can have a tangible negative impact on customers. Prominent examples include instances of unfair treatment of loan applicants within financial services or the misdiagnosis of patients within the health care industry.

Since the invention of the computer, the banking industry has aggressively pursued technology with the goals of creating competitive advantage and reducing costs. It is no surprise that banks and asset managers are aggressively embracing public cloud technology as they continue an industry-wide modernization effort that began after the 2008 great recession. One area where we believe there are significant gains to be achieved via the leverage of public cloud capabilities is in risk management.

In early 2018, we made some predictions on how new trends in cybersecurity, the public cloud, and big data would redefine the high-tech landscape. As we finish up the year, it is time to see how we did and consider what might be in store for the coming year.

Marriott International recently announced that it was the victim of one of the largest data breaches ever reported. If you sit on the board of a company, or are part of the executive management team, this latest hack is yet another reminder that cyber risk needs to be at the top of your agenda. This data breach should lead you to ask some particularly hard questions about your company’s cyber preparedness, and cyber risk appetite.

In our eighth edition of the Oliver Wyman Risk Journal, we bring together a diverse set of perspectives on how managers should approach this year’s greatest prospects and threats. These range from advances in artificial intelligence, automation, and cyberattacks to revolutions in industries such as financial services, retail, healthcare, and energy.

I contributed an article on data bias in machine learning to the Journal.

Ten ways smaller, more agile teams can achieve greater productivity for the organization. Smaller teams move faster, iterate at a higher frequency, and innovate more for the company. There are endless examples of small teams achieving amazing things.

The risk of using models that have a bias built into them is very real, and there are numerous examples of it already happening to the detriment of the people involved.

As the adoption of applications that leverage complex machine learning grows, so do concerns around humans’ ability to sufficiently understand and explain the decisions made and actions taken by machines. This concern has been particularly pronounced in areas where the lack of understanding around modeled output can have a real, negative impact on customers such as unfair treatment of loan applicants within financial services or misdiagnosis of patients within health care.

Leading financial services institutions are already taking steps to transition their KYC capabilities from a fire drill/project mode to a sustainable/business as usual mode. In many cases, however, KYC is still being treated as a large regulatory project with a “spend whatever it takes to comply” mentality.

Organizations that continue with this mindset will not only suffer higher costs, but will also be at a considerable strategic disadvantage compared to leading institutions that offer… Show more

Leading financial services institutions are already taking steps to transition their KYC capabilities from a fire drill/project mode to a sustainable/business as usual mode. In many cases, however, KYC is still being treated as a large regulatory project with a “spend whatever it takes to comply” mentality.

Organizations that continue with this mindset will not only suffer higher costs, but will also be at a considerable strategic disadvantage compared to leading institutions that offer a better customer onboarding experience and effectively leverage KYC data and resources to identify and pursue growth opportunities.

In this article, we discuss six areas that are the sources of inefficiency and ineffectiveness in KYC operations today and discuss the steps that can be taken in each area to transform KYC from a significant compliance cost, to a value-generating asset. Show less

There are a whole range of data, process, and tools related cyber risks, that are often overlooked when audits are performed. In this article we explore ten of the more common “hidden” cyber risks prevalent in large and mid-sized organizations, and offer some suggestions on how to begin to address them.

The world in which intelligent robots replace humans at scale is still imaginary – for now – but the line between how traditional capital markets firms operate and the techniques in common use by technology companies will only continue to blur.

As promising as machine learning technology is, it can also be susceptible to unintended biases that require careful planning to avoid. Thinking about the data that is used to train machine learning models is critical.

Banks and other consumer lenders must prepare to strengthen collections capabilities and increase capacity in advance of the inevitable recession. In the current environment of strong economic performance, rising equity markets, low unemployment, and generally positive consumer sentiment, it is easy to think that the good times will never end. But the current economic expansion will ultimately come to an end at some point, leading to higher unemployment, tightening household spending, and a… Show more

Banks and other consumer lenders must prepare to strengthen collections capabilities and increase capacity in advance of the inevitable recession. In the current environment of strong economic performance, rising equity markets, low unemployment, and generally positive consumer sentiment, it is easy to think that the good times will never end. But the current economic expansion will ultimately come to an end at some point, leading to higher unemployment, tightening household spending, and a corresponding increase in consumer credit delinquencies. Show less

In 2017, new trends in cybersecurity, the public cloud, and big data redefined the high tech landscape in ways that caught many companies off guard. As we contemplate what 2018 might bring, we thought it might be helpful to share some predictions for what might happen in the new year in these three increasingly critical areas. Below, in no particular order, is our list of nine predictions that might catch the industry by surprise if they actually manifest the way we are expecting.

A major cyber event can, if not handled correctly, result in company ending losses or the termination of one or more senior executives, including the CEO. The time to plan your response is before your Board is demanding answers on how the company is going to respond to an emerging threat.

The use of AI in the payments industry promises to reshape how customers and transactions are monitored and analyzed, especially as payments move closer to real time.

Given the accelerating frequency of data breach announcements and the fallout that occurs when discovered, the historical approach taken by many organizations to addressing known weaknesses is not working. Our premise is that many corporations need to consider fundamental changes in approach to cyber risk that goes beyond their current endeavors.

As organizations explore how software robots — or bots — can help automate administrative tasks and decisions, it pays to keep in mind some of the risks that come with the territory.

ID verification needs to start relying on information that is only known to the company and its customer. The Equifax breach brought to light how fragile current ID processes are.

Inappropriate conduct has cost the financial services industry a significant amount in direct losses, lawsuits, and fines since the last financial crisis. In response, banks have invested heavily in surveillance programs to identify employee misconduct manifesting via trading activity and electronic and voice communications. These programs are typically relatively simplistic and rules-based, and have often expanded over time to form a complex and inefficient web of firm-built and vendor… Show more

Inappropriate conduct has cost the financial services industry a significant amount in direct losses, lawsuits, and fines since the last financial crisis. In response, banks have invested heavily in surveillance programs to identify employee misconduct manifesting via trading activity and electronic and voice communications. These programs are typically relatively simplistic and rules-based, and have often expanded over time to form a complex and inefficient web of firm-built and vendor solutions. While a radical transformation of existing surveillance programs would be quite difficult in the current environment, it is essential that financial institutions seriously consider and plan for what comes next, as it is clear that the status quo will not hold. Show less

Equifax, a leading US credit bureau, has announced that it suffered a data breach resulting in the exposure of critical personal and financial data for 143 million Americans. The implications for the affected consumers are profound. While their credit cards can be re-issued with new numbers, their legal names, addresses, social security numbers and birth dates cannot.

As large companies consider how to integrate the public cloud into their technical and operational capabilities, many end up debating the same question: “Should we aim to be vendor agnostic?” In this piece, I frame a discussion on whether vendor lock is worthy of consideration as it relates to deployment of public cloud capabilities.

Large financial institutions are starting to consider new ways that the public cloud can help them drive innovation and competitive advantage.

Since business units, rather than enterprise-wide IT departments, are often responsible for writing RPA bot scripts to solve their particular problems, companies risk introducing another helter-skelter stack on top of the current legacy stack. There is a clear analog to today’s scenario—the way in which business organizations tried to patch over legacy systems in the early 2000’s.