Global Product Portfolio and AI Moonshot Operations Director - GAMMA
Asset managers today face a fundamental and indisputable fact: the world they are analyzing in order to make and execute investment decisions is increasingly complex and rich in data. For some managers, this is a tremendous opportunity: more complex strategies can be supported.
However, for most firms, the ability to keep up, from an investment and trading standpoint, will require significant investment and material changes to almost all elements of the target operating model, the blueprint that governs nearly every component of the business. The alternative to adapting that model is to risk becoming less competitive in the ability to generate alpha.
Keeping up in this context requires significant investment in developing and maintaining advanced, digital data and analytics capabilities in support of the front office. Doing so isn’t just a matter of technology. It requires a step change increase in capabilities related to process flows, work structure, roles, metrics, and talent.
Historically the realm of a small subset of esoteric strategies, investment in advanced analytics, machine learning, big data, and other capabilities is on the verge of becoming mainstream. The enablement of investment decisions with any or all of these tools cannot be confined to just a few managers, nor can it be just something that IT can figure out on the firm’s behalf.
Embracing these capabilities will be central to the way many large investors make decisions—even those that have traditionally relied on human judgment—and go to market. It is therefore critical for all asset managers to reconsider their operating model to ensure that they are set up to deliver on these capabilities in the near term.
A target operating model, in BCG’s view, is a framework with three primary components: process and technology, structure, and organization. (See the exhibit “Three Elements of a Target Operating Model Provide the Blueprint for an Asset Manager’s Future State.”) These three elements provide a blueprint for an asset manager’s future state and translate into a series of business questions and decisions for front-, middle-, and back-office operations.
In recent years, many leading asset managers have pushed to better align their target operating model with their core business strategy. They are, for example, creating centers of operational excellence, evaluating alternative sourcing models, and adapting operational and technological skill sets to the structure of their business.
Such changes have helped firms scale their businesses more effectively, accelerate new-product speed to market, trade in new asset classes and markets, and operate more efficiently.
The Boston Consulting Group's 2016 Global Asset Management Benchmarking Survey uncovered a number of significant operating model changes that originate directly in the front office and that are impelled by the analytical and data-driven challenges described above. Some forward-thinking firms are adapting their target operating model in ways we believe are relevant to all asset managers. Their efforts focus in particular on adapting technology and data infrastructure to handle these changes by building excellence in data management and honing capabilities to use a rapidly expanding set of technology tools.
An evolving data landscape is not a new phenomenon for asset managers, but the pace of change today and the breadth of opportunity it has created represents a significant step forward. The scope of change increasingly touches multiple elements of the target operating model.
We believe that of all the changes, advanced analytics, portfolio order and execution management capabilities, innovation in trading, and data in the front office have the greatest potential for profound impact.
Advanced Analytics. There is rapidly rising interest in the potential of advanced digital technologies and techniques to provide competitive advantage in investment management processes and elsewhere. Technologies that push the boundaries of traditional analytics—such as machine learning, data visualization, artificial intelligence, natural-language processing, and predictive reasoning—were once the province of a small set of alternative managers. Now they are becoming mainstream, sometimes yielding highly targeted investment insights with unprecedented speed.
Portfolio Order and Execution Management Capabilities. Managers looking to take on more-complicated investment strategies, trade at higher volumes, and execute more efficiently are adopting technology tools that can help them. The technology providers of these products are building progressively more sophisticated tools across asset classes.
The most frequently integrated new tools fall into three front-office functions:
The reevaluation of front-office tools requires significant work operationally, as well as the technology and data to handle that complexity. As tools have evolved, vendors have begun to look for opportunities to integrate them across functions and asset classes. Most managers, however, focus on developing or procuring best-of-breed solutions.
Innovation in Trading. A number of factors now disrupt the trading space: near-real-time technology, access to liquidity, strategic ability to pick a trade’s timing and exchange market, cost minimization, and ability to obfuscate trades. At high-frequency-trading firms, much in-house technology focuses on the ability to beat the market. Other pressures for change include the sometimes-disruptive financial-technology innovations of fintech firms, as well as constantly changing regulation.
Data in the Front Office. Some investment managers still view advanced analytical tools and sophisticated front-office IT as secondary to sound investment process and are, therefore, not adding resources in those areas. Still, despite a range of views, almost every investment manager we have encountered has identified improvements to the governance, quality, availability, and breadth of data as priorities for the front office and the risk management organization.
Data initiatives are being launched in three areas, each of which creates very specific business value for managers:
Every trend affecting the front office affects one or more of the target operating model’s three elements. There are implications for each element, and we see leading firms making some changes as they invest in the front office.
Process and Technology. Technology and data, in our experience, receive the most investment and will continue to attract the keenest focus of managers’ time and resources. Firms are emphasizing investments in core platforms and related workflows and building two-speed technology platforms for experimenting and learning in more agile ways:
In many cases, investments in data are made in conjunction with a broader front-office effort, such as portfolio management and order management replatforming:
Work Structure. Shared services, organization structure, and resourcing are all areas in which the evolving dynamics in the front office affect the operating model:
Organization. The ability to tackle and deal effectively with any and all of these trends can place significant stress on the organization. Processes and tools change, creating the need for significant change management. It is crucial to identify and hire new talent, and that requires competing in a variety of talent pools. Competition is steep for data scientists, architects, and governance professionals—and not just with other buy-side institutions but also with the sell side and leading technology companies. Bringing new people into the investment group and into IT requires viable career paths and career development expectations.