About Eagle

A Close-up on Canada: Data, Investment Performance, Technology and Operational Strategy in Focus

Manuel Tereso, CFA, Consulting Lead, & Mark Goodey, Dip IoD, Director


The investment management landscape in Canada continues to change rapidly. Mounting regulation, technological advancement, changing client demands, business transformation initiatives, and consolidation are presenting asset managers with both new opportunities and new risks. This prevailing shift in the industry was felt at two recent events in the region – TSAM Toronto and a client event that Eagle hosted jointly with CIBC Mellon. The events shared common, prominent themes in the industry that arose amongst the operations teams of Canadian asset managers and asset owners.

Mastering Strategic Data Quality
Firms are focusing on creating robust governance frameworks and enhancing the strategic management of their data, evidenced by the growth of the Chief Data Officer role. At TSAM Toronto, a show of hands was asked for those who did not have a data office within their organisation, highlighting that a tipping point has clearly been reached. Previously, the assumption of embarking on a new technology project was that data issues would resolve themselves or would be someone else’s problem to address further down the line. Yet today, many enterprise level projects and initiatives now start with better alignment to data as a primary governing thought. Firms are investing significant amounts of time, money, and energy in ensuring the quality of their data. Judging from the topics and interest from the TSAM Toronto delegates, it is evident data management will continue to be a growing priority.

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Replacing LIBOR: Transitioning to Risk-Free Rates

Brexit has effectively sealed the fate of LIBOR. The transition to global risk-free rates promises to be more taxing than most organizations are anticipating

Brian Dunton, Head of Instrument Engineering, Eagle Investment Systems


LIBOR, the most referenced interest rate benchmark in the world, is due to be phased out starting in 2021. The 2012 LIBOR scandal – in which benchmark rates were manipulated by rogue bankers to benefit their derivatives-trading operations – has resulted in a move toward risk-free rates (RFR). The momentum behind this has only become more acute as financial institutions get their arms around the impact of Brexit.

LIBOR, for the uninitiated, refers to the London inter-bank offered rate and is calculated using appraisals from leading financial institutions in which the banks estimate how much they would be charged to borrow from peer institutions. Risk-free rates, alternatively, are generally calculated as the weighted average rate from actual overnight lending between banks. Given the potential for manipulation, inter-bank offered rates are expected to gradually be replaced by global RFRs. For historical context, the LIBOR benchmark has long been used to calculate financing on swaps, bonds, mortgage-backed securities, bank loans and a host of other financial instruments. The expectation is that deals will start to gravitate toward published risk-free rates. While it sounds seamless, replacing the benchmark with a different index to calculate financing accruals is far more complex than it may appear at first blush.

Consider, for instance, that a vanilla interest rate swap would historically represent a fixed rate versus a floating interest rate hedge based upon the current LIBOR rate. Other economic indicators, such as the yield curve, are also generally factored in at the time that the deal was struck. While one leg would remain fixed throughout the life of the deal, the other would reset at each payment period. Different tenors of LIBOR were published and used to calculate swap financing fees for each period.
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Embracing Analytics: What Asset Management Firms Can Learn from Major League Baseball

Baseball has demonstrated the profound impact of analytics. Although it is a major sport in the United States, the lessons learned from its data transformation have global application. As asset managers are similarly navigating data transformation in their own industry, they are looking to close the data and technological gap – and discovering Managed Services as a solution that can help them rapidly and effectively make the shift.

Liz Blake, Global Head of Eagle Managed ServicesSM


When Michael Lewis first published Moneyball, he documented how one baseball team embraced data. Fifteen years later, this data-first mindset has spread across the league, impacting how teams invest in free agents, how the game is managed, and even how they sell tickets.

For asset managers, this is more than a curiosity. Baseball’s data transformation foreshadows the change currently reshaping the investment business. Just as advanced analytics challenged long-held assumptions and, ultimately, rewrote convention in baseball, asset management now is undergoing a similar transformation.

Model for Asset Management Firms
Incorporating a true evidenced-based, data-centric mindset into baseball’s scouting and player selection required new thinking or risking being left behind. Today, investment managers are confronting similar challenges. They’re not only rethinking what they analyze and how they generate alpha; they’re reimagining their entire operating model to treat data as a true asset. This enables them to redeploy resources – both people and capital – in new and more effective ways.

Historically, baseball managers were relegated to manual tabulations of individual data points, stored on paper and in their memories to drive decision-making. For example, great managers may know that a batter was a good hitter and was likely to get on base.  However, in order to win more baseball games, teams needed analytics to know how he got on base (he hit a curveball to shallow right field). Using this information in context, managers were able to hone game strategies, like the “shift,” in order to get the batter out, and put their team in a better position to win games. Ineffective use of resources – such as bringing in a curveball pitcher to throw to a batter who loves hitting curveballs or leaving the third baseman and shortstop in their traditional positions waiting for a ball that is rarely going to come – are not winning strategies.

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Performance Measurement: Controls, Workflows, and Technology

Mark Goodey, Director, Senior Principal of Investment Analytics, Eagle Investment Systems


Recently, I was fortunate enough to observe a number of thought-provoking presentations and panel discussions as chair of the FTF Performance Measurement Americas Forum in New York. In reflection of the event, I’ve highlighted some of the key themes I found most impactful.

Improved Controls
Performance teams are under increasing pressure from internal audit teams—and, more importantly, external regulatory bodies—to ensure their data is passed through comprehensive control processing. Once validated, the data is deemed reasonably bulletproof in the eyes of consumers. There’s an acceptance that the performance function acts as a safety net for clients and, therefore, needs to act as a data quality feedback loop to other teams across the business. There is a firm ‘quality control’ component to the performance measurement function, requiring significant oversight of data and robust workflows.

Much of the conversation I witnessed centred on the data management challenges for performance teams, as well as the role of manual ‘eyes-on’ processes versus automation. Based on the increase in the volume of data, the sources of data, and the frequency of reporting, it’s apparent that processes and workflows need to be streamlined and the ‘maker-checker-supervisor’ process must be systematised. Ultimately, this comes down to a combination of human and technology processes. It’s essential that exception-based reporting, like that provided by Eagle, replaces manual reconciliation. This solution increases the human operator’s responsibility to supervise and oversee the data by using tools and dashboards to ensure data accuracy and resolve issues as they occur. At Eagle, one of our key considerations, as part of our continual product enhancement, is to enable any number of “checkers” and “supervisors” in the process at any time in order to satisfy regulatory demands. Eagle’s next Performance software release will introduce the ability to have any number of ‘flags’ to evidence a sign off by a stakeholder as part of an approval workflow, this will be audit ready.

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ESG Data: The Case for Transparency

Joao Sousa Dias, Sales Director, Eagle Investment Systems


It seems there is nothing hotter in investing today than ESG. While long considered a “tick box” activity, environmental, social, and governance factors have taken centre stage in recent years amid pressure to address issues such as climate change and diversity, as well as societal changes spurred by generational transition. Among investors, though, the catalyst with the biggest impact is the mounting evidence that accounting for ESG factors can improve returns.

“Incorporating ESG analysis into the investment process can add between 50 and 100 basis points per annum to returns,”Arabesque’s Andreas Feiner quantified in an interview with Eagle, adding that it: “imparts a slight reduction in the overall risk”. The numbers support the narrative that impact investors have been making for years. Companies with high ESG standards are likely to be better run, more resilient to changes in regulation, and less susceptible to being fined or suffering reputational issues over the long-term.

That’s the good news for investors. And it helps explain gravitation to socially-responsible investment strategies, as some €19.2 trillion is committed to sustainable strategies worldwide, according to the Global Sustainable Investment Alliance. Europe leads the way in this, accounting for well over half (57%) of professionally invested funds employing sustainable strategies globally. The bad news, however, is that ESG can be a labour-intensive pursuit for firms that don’t have their “data house” in order.

According to the consulting firm Opimas,total spending on ESG data will increase by around 48% in the next two years. Asset managers and asset owners alike are looking to incorporate ESG data to drive both investment decision-making and investment analysis. Furthermore, while ESG factors have traditionally been the preserve of equities, increasingly ESG-based fixed-income indices are emerging. As a result, the demand for ESG data has never been higher and will only continue to grow.

Meeting this demand is easier said than done, however. The availability of data is scarce with vendors playing catch-up as ESG strategies multiply. To fill this void, a range of heterogeneous ESG data services have been introduced, yet standardisation—and, more importantly, standards—have yet to materialise.

This is no great surprise, since the regulatory environment is still developing and ESG measurement is still in its infancy. As Andreas Feiner points out, in the last two years regulators have introduced nearly 300 different rules focused on sustainability and corporate governance. While this is likely to improve ESG reporting—and provide greater opportunity for investment decision makers to identify metrics that deliver outperformance in the longer-term—in the short-term, it holds back standardisation.

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Becoming a Data-Driven Organisation

As investment firms turn to data to help inform and improve investment and operational decision-making, they need to take a logistical, rather than tactical, approach to data management.

Marc Rubenfeld, Head of Sales EMEA, Eagle Investment Systems


Evidence-based management has become the new normal across businesses as organisations in every sector are looking to improve decision-making and, ultimately, the client experience. This isn’t necessarily new, but what has changed is that today they’re leveraging facts and data instead of relying purely on the gut instincts of their workforce. This has been made possible because technology has evolved to a point where the client experience can be substantially improved by utilising and combining data in new and unique ways. For example, Uber has combined lots of different types of data together to create an entirely new client experience and business model.

At a high-level, this has created a new breed of organisation: the data-driven organisation. A data-driven organisation fundamentally relies on data to conduct business and optimise the client experience. They typically display several characteristics, including a relentless focus on measuring results and continuous improvement, coupled with frictionless self-service capabilities available to clients. To achieve these characteristics, the value of data must be baked into the organisation’s DNA.

Organisations will need to become data-driven if they want to remain competitive. Like countless technological advances in the past, if your organisation does not embrace the potential of data, it will begin a painful journey to irrelevance. Imagine a business that did not embrace electricity or the telephone; this is the same prospect facing businesses that fail to embrace data today.

The investment industry is no different; firms are more focused on data than ever before as a means to rethink both the client experience and how to perform day-to-day business functions. Specifically, investment managers are undertaking transformation programmes to put data at the heart of their organisation in order to realise the benefits of being data-driven.

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Meet…Jayaram Iyer

Eagle’s newest data management engineering leader brings over two decades of experience from Amazon, Microsoft, and other leading technology companies. Jay Iyer shares what drew him to Eagle, as well as his views on opportunities for financial services companies to best leverage the cloud and the vast amounts of data available at their fingertips.


You’re joining Eagle after having worked at some of the most well known technology companies in the world. Reflecting on your background, could you discuss how your background will influence your work here at Eagle?

Most recently, I served as the Engineering Leader of Amazon’s Alexa Communications platform. I also spent time as Head of Engineering for AWS DynamoDB Storage services, and before that, led Amazon’s Listings and Catalog team. I also spent a considerable part of my career at Microsoft and served as Director of the company’s Caradigm healthcare-informatics joint venture. All of this, in different ways, will influence my work at Eagle.

My work at AWS DynamoDB, for instance, entailed helping stand up and manage a petabyte-scale, low latency, multi-tenant no-sql database in the cloud. It can handle literally millions of transactions per second, so when we talk about scalability, this is what we have in mind. But this experience with distributed systems and high-volume data processing is critical to what we’re doing at Eagle.

I think my experience around data management and data lakes will also prove valuable. At Microsoft, to name another example, we developed and brought to market the Caradigm Data Lake and Analytics platform. This is a highly scalable, fault-tolerant, big data aggregation and analytics engine. It’s integrated with the Hadoop open-source ecosystem; incorporates advanced security features such as encryption; and leverages a full-stack, read-write, apps-development platform with open REST-based APIs. So this experience is very relevant to what I’ll be working on at Eagle.And finally, the Machine Learning experience from my work on the Alexa Comms platform, most recently, and on Amazon’s Marketplace Listings Platform before that, will be critical.

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Meet…Jackie Colella

With more than two decades of experience from Wall Street and consulting, Jackie Colella shares what her new role overseeing the client experience entails and her perspective around how to define success.


You initially joined Eagle last year in a project management capacity, helping clients adopt Eagle’s V17 software release. Today, your focus is overseeing the client experience—a role that is seemingly unique from positions traditionally encountered on Wall Street or within fintech. Can you discuss the encompassing responsibilities and how you’re approaching this new role?

Working directly with clients and providing support as they adopted the V17 release early on positioned me well to fully comprehend the significance of the client experience to Eagle’s success; and then, how to help facilitate alignment between all areas of Eagle’s business and the objectives of the financial institutions we serve. Accordingly, this role—which resides within Eagle’s Office of the Client—builds on the company’s value proposition to collaborate closely with clients and create business-led solutions.

In a lot of ways, my position is comparable to that of a cruise director. I’m not sure if anyone remembers the TV series The Love Boat, but the cruise director is expected to know all of the ins and outs of the ship; they are tasked with orchestrating the staff, ensuring the right people are where they need to be; and they serve as a guide to the passengers, helping to shepherd guests accordingly so they can enjoy all that the boat has to offer. Similarly, the customer experience isn’t just managing client relationships—it’s about raising awareness of what Eagle can offer through our software, strategic alliances, and other offerings, like managed services. By knowing our clients intimately, we can proactively help them identify the optimal solution.

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Riding the Transformation Wave

Mal Cullen, Eagle’s Chief Executive Officer, reflects on 2018, highlighting Eagle’s considerable progress in its deployment-model transformation


Thomas Friedman, in his book “Thank You For Being Late,” identified 2007 as the precise year that technology began to devour the rest of the economy. This was the year when consumers likely bought their first iPhone or created a Facebook account. It wasn’t obvious at the time, but a decade later, it’s plain to see that beyond a radically new user experience, these innovations created an insatiable demand for data—and consequently, a need to store, manage, analyze and protect this information.

Not coincidentally, 2007 marked the first year in which Eagle ACCESSSM, our secure private cloud, became the preferred deployment platform for clients. This shift represented a step-function change in how clients engaged with Eagle. Again, this may have seemed revolutionary at the time, but we now recognize the extent to which this move is allowing organizations to holistically re-imagine their business model.

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Meet…Barbie Connell Spencer

Eagle’s newest Insurance Accounting Lead, Barbie Connell Spencer, brings a wealth of experience navigating legacy system conversions. She also loves a challenge—a characteristic cultivated during her service in the US Navy, professional career choices and her sense of adventure in pursuing outdoor activities. 

Tell us a little about your background and your journey that lead you to Eagle?
I definitely have a unique background! After my time in the US Navy, I spent time working in IT at Intel as well as several public accounting firms. At the same time, I continued to achieve my secondary education in accounting. These experiences in the early phase of my career were critical in preparing me to consult on the installation of accounting solutions. I eventually accepted a position at MassMutual, where I would then spend the next 18 years of my career. Although I initially started out as a programmer, I gained experience learning all aspects of the insurance accounting industry, and was hooked.

Investment accounting in the insurance vertical is quite different from traditional accounting. Industry-specific rules and regulations create quite a bit of nuance, so substantial experience and a deep understanding of how business users may seek to leverage software is critical to becoming a true subject matter expert.

My ability to gain experience across a range of functions while working for my last employer, MassMutual, proved to be tremendously advantageous in building my skillset. I eventually moved away from IT and transitioned into a role overseeing investment data for the company’s investment accounting system and its corporate ledger. When MassMutual made the decision to move to Eagle, I had the opportunity to learn the Eagle system and become an expert. I served as the data-conversion lead during the implementation, so I’m well-versed in the challenges insurance companies face when transitioning from a legacy system. I also gained an appreciation for the strategy required to navigate an implementation, and have a true passion for this kind of work. After I earned my Master’s Degree, I was excited to return to my consulting roots and begin this new phase of my career at Eagle.  Read More…

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