Break Your Dependency on a Fickle and Expensive Talent Pipeline
May 15, 2024
Read Time: 7 minutes
Data Management
If you’re among the financial services firms that have grown, or maybe even doubled or tripled assets under management these past few years, congratulations! Perhaps you’ve expanded into new investment strategies or asset classes, made an acquisition, expanded markets or adopted digital technologies that have accelerated your growth. But growth is never straightforward. It presents operational challenges that must be navigated—particularly on the data management end of your business, as higher transaction volumes put pressure on your middle and back office.
If you’ve ever received a call from investors after they read a Wall Street Journal piece about a regulatory fine your fund received for a technical oversight, you know first-hand the consequences of a thinly-stretched back office. If you’ve had to refund a client after your operations team made a data reconciliation error, you’re similarly familiar. Or, worse still, if you’ve experienced a system outage during trading and lived to tell about it? You’ll probably never run a lean tech team again!
Scaling both tech and middle- & back-office operations is only going to become more critical in the years to come. It’s not just the dollar value of growth that is significant, with financial services globally poised to reach $37.5 trillion by 2027, at a CAGR of 7.5%. It’s the growth of data as well. By next year, the global datasphere is expected to hit 163 zettabytes or 163 trillion gigabytes. For perspective, that’s a full ten times more data than in 2016. Like virtually every industry, financial services are contending with the explosion of data. Increasingly complex products, evolving data governance requirements, more sophisticated risk management demands, and enhanced client personalization are just some of the factors driving the proliferation of data in financial services.
So, is the answer to staff up as quickly as possible? Perhaps. But adding headcount may be easier said than done in today’s employment market.
As financial services organizations grow AUM and develop increasingly sophisticated approaches to data and analysis, the scale and scope of their hiring needs are changing.
For private markets, for instance, the financial crisis of 2008 marked the beginning of a new era. The Dodd-Frank Act of 2010 then spurred capital flight from banks to private markets, driving growth for many funds.
Many of today’s major private markets firms launched flagship funds in the period following the 2008 financial crisis–a year of institutional reorganization. Blackstone Group launched the Blackstone Real Estate Partners VII fund in 2012, raising $13.3 billion. A decade and a half later, those funds matured and are now raising their third, fourth, fifth and sixth funds. Thoma Bravo, founded in 2008, raised a $34.2 billion fund in 2022 allocated to tech. Outside of private markets, financial services at large are gaining sophistication as well.
Digitalization across the industry is driving a shift in hiring needs. From large-scale adoption of cloud computing, to automated operations solutions, to AI-powered data analytics, to blockchain technology underlying financial security solutions, supporting core functionality at a large and growing number of firms requires greater digital dexterity. Deloitte predicts digital financial architecture will become the norm by 2025 to support real-time decision-making, enable automation, and provide a foundation for emerging technologies; and 90% of respondents said digital technologies have already significantly impacted financial services. To stay competitive, firms must adapt to the increasing efficiency with which their peer companies execute transactions.
RELATED READING: Measuring the Significance of Data
As the industry evolves and legacy processes become digitized, financial institutions need not just progressively more staff – but a more technical caliber of staff. Increasingly, funds demand large numbers of software engineers, developers and data scientists. These teams craft intricate system architectures, automate processes and data normalization, and construct robust data warehouses for efficient information analysis.
Middle and back offices also require technical operators. They need the skill to execute complex reconciliations and expertly wield SQL to navigate databases. Operators’ responsibilities span managing extensive trading operations while ensuring swift time-to-market for new products. They must execute tasks with precision, avoiding errors in trade capture, security setup, data validation, reporting, and other critical functions.
As a scaling financial service firm, you’re not just competing with BlackRock, Millennium, JP Morgan and Goldman Sachs for ops and tech talent anymore. Your competition now also includes fintech, like BlackRock Aladdin and IHS Markit, as well as Big Tech players like Google, Apple, and Meta. Let’s consider the unique challenges of competing for talent under these conditions.
Recruiting Big Tech talent is expensive– especially considering that senior software development engineers at Big Tech firms typically earn around $300K while their counterparts in financial services earn between $150K-$300K for similar jobs. To attract and retain this talent, financial services must compete outside their typical pay range. Moreover, developers are known to be drawn to work on cutting-edge, modern technology–an area Big Tech excels in thanks to substantial innovation budgets. Meta, for instance, plans to allocate over $40 billion this year solely to artificial intelligence development.
Beyond monetary incentives, top-tier tech talent is fueled by a sense of purpose. For aspiring engineers and developers, the allure of contributing to groundbreaking projects at tech giants like Microsoft is undeniable. Financial services firms must acknowledge this reality as they seek to attract talent.
Moreover, the demand for operations expertise is on the rise. A growing number of companies are actively courting talent in existing pipelines, each offering increasingly enticing opportunities. Meanwhile, industry leaders like BlackRock and S&P are also securing talent through direct acquisitions, integrating seasoned and established tech teams into their operations.
RELATED READING: Why Your Front Office Needs a Data-Driven Culture
When vying for top talent against Big Tech and established Fintech, you might find yourself making offers far above “market.” And if that talent is already working at their dream job, even a premium compensation package might be insufficient. Short of dramatically inflating your recruitment budget, here are some alternative solutions to consider.
Instead of the conventional route of recruiting ops talent primarily from accounting backgrounds, diversify your talent pool by seeking individuals with skills in math and engineering. By broadening their recruitment efforts, they can tap into a more diverse range of technical expertise, attracting candidates who possess the necessary technical dexterity for modern tech operations.
Sometimes, the best people for the role aren’t classically trained in the field. Did you know Renaissance Technologies, which manages what is considered one of the most successful hedge funds in history, doesn’t even hire talent with financial or business backgrounds?! Not only could this approach bring fresh perspectives, but it could also foster a more dynamic and innovative workforce.
Many financial services companies are running outdated recruiting scripts and job descriptions that don’t resonate with people passionate about technical problem-solving. By modernizing and refreshing job descriptions, companies can appeal to the new generation of tech-savvy candidates who are excited about using the latest tools to solve complex challenges. Highlighting opportunities for innovation and growth within the organization can attract talent seeking stimulating and forward-thinking environments. You should even consider establishing a hackathon.
By investing in advanced technology infrastructure, financial services companies can streamline operations and reduce reliance on expensive, highly technical staff. Implementing a comprehensive data platform that is self-serviceable and purpose-built for the organization’s data management needs can empower employees across various departments to access and utilize data effectively. This not only enhances operational efficiency but also reduces the requirement for specialized technical skills, making the work accessible to a broader range of talent.
For example, a robust data platform can automate processes, allowing operators to pull reports and perform tasks through intuitive user interfaces rather than relying on complex coding or database queries. This shift towards self-serviceability not only minimizes the need for extensive technical proficiency but also opens up opportunities for employees to focus on higher-value tasks, driving productivity and innovation within the organization.
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