Reconfiguring the buy side for the digital world

Digital continues to disrupt the landscape of the financial markets

Read this article and learn about:

  • Dealing with the tremendous pressure to reduce the cost structure within buy side firms
  • The importance of system rationalization and getting rid of legacy systems
  • Why you should put the power of analytics and predictive intelligence in the hands of business users
  • The seven key questions buy side firms must grapple with as they make sense of different trends
 brad bailey 
Brad Bailey, Research Director, Securities & Investments, Celent

Regulatory and market structure changes in the post-crisis world have put pressure on the traditional operating models of those responsible for managing the world’s assets. At the same time, the retrenchment in traditional dealer balance sheets, tied with widespread cost-cutting programs, is creating a favorable environment for new players to come in and work towards solving some of the industry’s most difficult problems.

Buy side firms are operating in an increasingly challenging business environment: regulation, competition from lower-cost models, restructuring of their counterparties, and a shifting demographic of investors. This in turn has reduced the ability of firms to generate revenue in the same fashion as before the crisis.

Hence, there is tremendous pressure to reduce the cost structure within buy side firms. This requires critical choices on where to compete, which clients to serve, what business lines to grow, and which business lines to divest from. It has also brought into view the high levels of complexity that are resident in technology architectures and business lines.

Figure 1

Figure 1: Industry Forces (Source: Celent)

The buy side has reacted in a variety of ways to the challenges presented by the capital market business environment, including new business models to allow them to compete as effectively as possible, and simplifying all aspects of their internal and external touch points. Firms are striving to minimize complexity by moving from analogue to digital models, particularly with regard to data, analytics and market interaction. Many of the changes taking place are around the three themes of; digital transformation, legacy transformation, and emerging technologies.

By and large these areas are striving to remap complex front office processes in investment, trading, liquidity management, as well as driving efficiencies middle and back office, in the light of increased demands for reporting, and workflow capture driven by MiFID II/MiFIR. These three themes impact firms regardless of their size, the assets they manage, or their structures.

Figure 2

Figure 2: The Three Themes (Source: Celent)

Digital transformation

Digital transformation is about applying customer and data-driven insights to radically transform the business. The digital firm is built on the premise of leveraging resident data for insight, and prediction across business lines and user types. The data set has morphed to include not only traditional data, but also semistructured and unstructured data. The increase in data presents challenges and rewards. The multifaceted dimensions of data that can be leveraged present a unique opportunity to unleash a digital architecture that puts analytics and predictive intelligence in the hands of not just data scientists but business users as well. This is a cultural shift that allows global solutions across a wide array of businesses and users. Collaborative intelligence will allow rapid transformation into automated solutions.

Legacy transformation

Buy side firms are innovating for simplicity, and optimizing processes across the value chain of businesses is a path to maximum effectiveness. System rationalization is a major theme here — bringing down the number of myriad legacy systems across asset classes to unify the front, middle and back offices.

Firms that are burdened by manual processes, or that lack the means to automate existing and new processes, are finding themselves at a disadvantage. The speed of change is amplified in a world where information and capital travel fast. IT, operations and frontline business leaders require market intelligence and information tools to be able to predict the trajectory of their business. Buy side firms are automating the heavily redundant processes that still exist within compliance, regulatory and operations into single workflows across their institutions. They are leveraging the wave of machine learning, cognitive computing, and AI to continuously free staff to focus on value-adding tasks. They are continuing to remap their trading to optimize product, venue and counterparty selection to minimize collateral, execution and operational costs.

Innovation and emerging technologies

Digital models, whether in adapting business models, remapping legacy infrastructure, or creating better access to data structures, are striving to address three broad areas.

FinTech firms increasingly have the flexibility, customer proximity, and technological understanding necessary to address business challenges across the entire value chain of capital markets. Solutions that address critical points around market infrastructure (including associated software and cloud deployment solutions), post-trade processes, and access to capital are the key areas.

Most of these changes are sitting on the back of major shifts in the creation of data, the types of data that is available, and the structure of that data. Properly ingesting, processing, normalizing, and storing with the ability to analyze are at the center of many emerging technologies and innovative fintech firms.

Firms are reinventing themselves through innovative business models and partnerships in order to operate nimbly in an increasingly automated and digital business. A focus on data processes allows these firms to extract value from their data via cognitive AI tools. They are creating data-driven, replicable processes that are optimized on global scales across their entire infrastructure. These firms are innovating for simplicity through a collaborative approach to their global IT challenges.

Asset managers and their clients want real intelligence and insight around their investment and the sources of its performance. Many analytical tools that retail investors take for granted are often not available to institutional investors. Whether it is quantitative investment decision tools or passive investment products that mirror active management approaches, a next wave of innovation is seeking to change the traditional asset and wealth management businesses. Active managers are trying to expand into new asset classes, while incorporating more and better data for better market insight.

They are also looking to better manage the research process in searching for alpha, portfolio structuring, client analytics, new products, and the means of actual research distribution, which is becoming more important given research unbundling under MiFID II. Platforms that simplify the investment process and knowledge about portfolios are in great demand.

Resource focus

Firms have to look at the changing world around them and consider their focus. Most firms are struggling with managing their current business, implementing regulatory mandates, and seeking opportunities while keeping an eye on the rapid changes surrounding them. Major firms are struggling with the opportunity and risk associated with the migration to digital models.

In order to get some perspective on the changes around them, there are key questions buy side firms must grapple with as they make sense of different trends.

  • What are the balances of risks that exist as my firm becomes more digital?
  • What are the risk implications from a market, regulatory, operational, tracking, and cyber perspective in considering and adopting new models?
  • Are the investments I am making today in sync with changes that are occurring in the market?
  • How do we plan for the next five years in technology, given the speed of change?
  • How do I separate the hype from the reality in an emerging technology or business model?
  • What is the speed at which distributed ledger technology or blockchain infrastructure will impact my firm?
  • Where can I leverage automation in my workflows most effectively?

These questions, often difficult to answer, are the starting point for understanding a rapidly changing, ambiguous business environment at a time when cycles move faster and faster.

Looking ahead

There is a lot of change now which yields both risk and opportunity. Most of the changes we are seeing in the capital markets, whether in technology or business models, center around the explosion of data that exists in the market — getting a handle on this will be key for buy side firms. 


Brad Bailey is a research director with Celent's Securities and Investments practice, and is based in the firm's New York office. He is an expert in electronic trading and market structure across asset classes.  His research focus is on emerging front office technology and FinTech. He also is extensively involved with firm’s digital capital market and blockchain strategy.

Brad has more than 20 years of Wall Street industry experience in trading, technology, sales, strategy, analysis, and consulting. A noted thought leader, he is quoted in the industry and general press, including: WSJ, Financial Times, American Banker, & Forbes, as well as radio and Bloomberg TV.

Prior to Celent, he spent nearly seven years at KCG Holdings (formerly Knight Capital) as the Director of Strategy. There he identified opportunities to expand across asset classes, to grow business lines via tactical acquisition, strategic investment, partnerships, market structure evolution and organic business development. He also served on the boards of several of the firm’s affiliate companies.

Prior to Knight, Brad was the senior analyst for Aite Group, LLC, a financial technology research and analysis firm, where he produced research and consulted on electronic trading. Brad has an undergraduate degree in Mechanical Engineering from Rutgers University and a MS from University of Colorado, Boulder.