Can technology create value in asset management?

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Asset managers are struggling to deliver sustained, profitable growth. In the markets, investment returns are being disrupted by macro-economic and geopolitical volatility. Competitive dynamics are accelerating, and investors are pushing for lower fees – while also stepping up their service expectations.

Furthermore, the need to offer new asset classes to a wider range of global investors is pushing up complexity and adding to compliance costs. In response, firms are accelerating their shift towards technology enabled, data-driven business models. The ability to adopt and integrate these models is fast becoming a key factor in determining long-term success.

Smart use of technology and data is critical to reducing cost and risk, and to meeting growing demands for personalisation and access to digital and private assets. It’s also a vital enabler of firms’ ability to integrate ESG into portfolios, operations and governance – not to mention ensuring consumer protection and complying with evolving regulations like the EU’s Digital Operational Resilience Act.¹

Unlocking that potential is hard though. Asset managers struggle to integrate new technology with legacy systems, develop the agile infrastructure they want, and maximise the value of internal and external data. And as they extend their reach into new markets, the regulatory and operational landscape gets even more complex. 

This means that the goal of building a flexible, scalable platform often remains tantalisingly out of reach. This picture is corroborated by KPMG’s 2023 global tech report, which shows that 67 percent of technology leaders felt under pressure to do more with less in 2023 compared to 2022.²

As Agnel Kagoo, Consulting Industry Leader for Capital Markets, KPMG in the US puts it: “Challenges are magnified by asset managers having to become technology companies and drive more value from data, with all the investment that entails. At the same time, there’s a downward trend in the fees they can charge.”

These points resonate with our 2023 survey Capturing the data opportunity: Institutional investors in the age of AI, which examined data-related themes among 520 institutional investors.One major finding was the moving target for data management being created by emerging asset classes such as private assets, and by evolving regulations like ESG reporting.³ Stacy Belf, Global Head of Consultant Relations at State Street adds, “Generating value from data is a moving target given the abundance of data to be analysed, normalised and standardised to extract insights. But this work is an essential foundation for gaining a competitive edge and driving growth.”

The State Street survey also revealed a worrying absence of holistic data strategies. Two-thirds of institutional investors lack an overarching data strategy, and this is especially true for mid-sized firms with assets under management of US$100 billion-500 billion. Just 40 percent of these firms are halfway through their data transformation journey. The average institution needs to upgrade almost half of its existing technology to meet its data goals – with all the time, cost and effort that entails.⁴

The challenges facing asset managers are thorny and well known — but not insurmountable. Technology can play a crucial role in unlocking profitability amid volatile markets, shifting demand, and increasing regulatory burdens. When it comes to existing technology though, data architecture is often a fragmented affair – a patchwork of best-of-breed service providers. Multiple system providers can create restrictive data silos, making it hard for information to flow seamlessly. As a result, sharing data across systems for analytics involves cumbersome and error prone processes. As Nathan Attrell, Head of Industry, Financial Services, EMEA, Snowflake explains, “There’s a push-pull challenge for asset managers – building capacity and scaling while managing new volumes, velocities and varieties of data.”

Too many firms struggling to manage this complexity, becoming truly data-driven at a time when investors’ demands are becoming ever more sophisticated can appear to be an insuperable challenge.

A robust data strategy is the best starting point. Recognising the critical role of data in driving long-term value, market reach, scaling operations and personalising products is key. Asset managers are looking for solutions that will help to deliver these data strategies. As Dean Brown, Head of Asset Management Consulting, KPMG in the UK, says, “They need providers and advisors who connect front-to back- office across asset classes and geographies. They want data flowing through investment processes and surfacing the right information at the right time.”

In terms of technology, both the use of ‘low-code’ and process automation can differentiate successful asset managers through their ability to enhance efficiency, scalability and agility — allowing them to provide clients with the information and services they need, and in turn hopefully exceed client expectations.

Lastly, artificial intelligence (AI) tools are increasingly used for driving productivity, performance and personalisation. “AI’s impact on the industry is potentially profound in accelerating the delivery of tailored products to market – at speed, scale and with much less manual effort” adds Dean Brown. State Street: Firms are seeking to upgrade their existing technology, with AI emerging as the leading future investment priority. In the next 2 to 5 years AI’s most valuable applications will be enhanced cybersecurity, automated investment analysis, advanced customer experiences, risk analytics, and personalised investment advice. But it’s important for firms to think about how AI fits with other emerging technologies and incorporate AI within a holistic data strategy. “In our survey, firms that reported having a holistic data strategy were already seeing significant economic benefits.

Those with a holistic strategy reported on average a 19 percent increase in revenue growth, a 24 percent increase in customer satisfaction, a 21 percent increase in customer retention, and a 19 percent increase in new client acquisition⁵," explains State Street’s Global Head of Thought Leadership, Anna Bernasek, who led the research.

The power of cloud computing is improving productivity and efficiency. At the same time, AI’s ability to extract insights from new and unstructured data sets is helping to uncover investment opportunities. AI applications in asset management can be grouped into six broad categories: Chatbots, data governance, parsing documents, image analysis, visualisation and software development – where AI can generate code, freeing developers to focus on algorithm development.

“At State Street, we’re applying AI and ML across a number of use cases, from building smarter portfolios to improving data quality and optimising manual, error-prone middle-office workflows," explains Aman Thind, Chief Technology Officer of State Street Alpha®.

Many asset managers made initial steps into the cloud five or more years ago, often driven by a desire to reduce total costs, to exit on-site environments, or by license renewals. However, many firms that made the leap didn’t realise the full benefits of cloud – such service providers often failed to grasp the challenges of a fragmented financial services ecosystem or to solve for the data management problem. Today, newer technologies are enabling the industry to overcome legacy technology challenges with innovative cloud-native data platforms.

Snowflake provides limitless scaling, multi-cloud operations and advanced data-sharing all within a secure, governed data perimeter. Data sharing enables instant access to external data and leading industry applications, without the need for data movement. “This approach simplifies data management, resulting in faster access and analytics, allowing firms to gain insights more rapidly across diverse asset classes,” explains Nathan Attrell.

By removing silos and bottlenecks, data collaboration can transform internal access and self-service experiences – revolutionising client interactions. It’s not one-size-fits-all either. Data experiences vary with client sophistication, ranging from detailed quantitative analysis to bespoke visualisations, all securely shared. This is a potential gamechanger for firms seeking to provide tailored client experiences in a rapidly shifting investment landscape.

The KPMG global tech report shows that digital transformations are delivering, despite economic headwinds and budget constraints. To fully realise the potential of transformation and improve their competitive edge, asset managers will need to combine robust technology infrastructures with highly skilled talent and effective cross functional collaboration.

Looking ahead, the agility to integrate new technologies into the ecosystem will become critical to transforming asset managers’ operations and offerings. AI already has a huge breadth of use cases, and what could be next is quantum computing. Together with AI, that would further revolutionise the industry’s use of data. In truth, there will always be new technologies, so focusing investment on the right business outcomes will remain key to successful innovation.

Generative AI is top of mind for business leaders today, with the biggest impacts expected to be felt in customer operations, marketing, software engineering and research. We see generative AI as not just a tool for efficiency and productivity but as a significant driver of innovation across the board in asset management.

We’re likely to see more cloud migration, breaking down data silos for greater efficiency and joining up disparate operations. This will improve client experiences, enable quicker responses and enhance data accessibility. That’s good news for investors, and it will free up relationship managers to focus on higher-value tasks.

Meanwhile AI will continue to be deployed, with asset managers rolling out large language models to clients. As it evolves, AI will be at peoples’ side, empowering them and providing instant insights. To realise its full potential, firms will need to be laser focused on governance, training and risk management.

KPMG can assist asset management companies transform their businesses through the better use of technology and data within their business. Our services range from strategic and digital foundation design, target operating model development, and platform assessments, through to post-merger integration and divestiture support.

Working alongside firms such as State Street and Snowflake has allowed KPMG professionals to help asset managers embed market leading tech solutions into their operating models and leverage the power of these solutions to drive efficiency, scalability, and growth on both a local and global scale.

Learn about the opportunities of using AI and tech-enabled change within financial services, and explore the positive and negative impact of technology innovation in Frontiers in Finance.

KPMG's asset management specialists can help you to understand the impact of generative AI for asset management. Contact us today.