Peter Ku of Informatica discusses how a modern, intelligent approach to data management will enable collaborative innovation, regulatory compliance, cost savings, risk management and exceptional customer experiences.
The asset management industry is amid a major digital transformation driven by the acceleration of technologies, including cloud computing, artificial intelligence (AI) and machine learning (ML), designed to help scale and automate business processes and decisions to create a competitive advantage. To capitalise on the potential benefits of these innovations, fund and asset managers are continuing to evolve their services, dramatically improve their back-end processes, and meet the complex demands of new and existing regulations. It’s a lot to manage, all on top of the stresses and strains of the day job. The question is: how to solve these challenges efficiently?
A key part of the answer to that question lies in next-generation data management. With modern cloud-based offerings providing the ability to marshal, clean, and deploy vast amounts of data at speed, fund managers can begin to harness the data they collect to meet the current demands of the sector and future-proof their business.
Here are four ways the sector can benefit from getting control of its data and making it available for frontline business use, starting with improving customer experience, then looking at improving regulatory compliance and risk management and finally driving cost savings through greater efficiency.
Improving customer experience (and aiding business growth)
No matter your sector, customer experience is at the heart of business success. An advanced data management strategy enables fund managers to understand their customers in-depth, predict their needs before they communicate them and offer personalised solutions. With trusted, accurate data, companies can make informed portfolio decisions, provide personalised recommendations and evolve more customer-centric offerings rather than providing a one-size-fits-all approach. It’s not hard to see how this improves customer satisfaction, but it also increases customer retention and lifetime value as clients engage more intensely and for longer with the fund’s offerings. What’s more, as AI and ML become essential to the work of fund management – particularly in navigating complex markets where trading is increasingly run at machine speed rather than human speed – high-quality, automated data management provides a firm foundation of accuracy and integrity, enabling more profitable fund management, greater customer trust and satisfaction and so sustainable business growth.
Meeting regulatory requirements with confidence
The financial industry operates under a new and existing stringent set of regulations from the new Consumer Duty regulation, the incoming Sustainability Disclosure Requirements (SDR) and an increasingly in-depth ESG reporting regime. At the heart of these regulations lies accountability, which essentially requires a clear understanding of data origin, lineage and use. An AI-powered approach to data management provides the transparency and governance needed to meet these regulatory obligations. By accurately tracking, classifying and governing data, firms can respond confidently to regulators’ demands, ensuring compliance without compromising operational efficiency. With the right data management regime in place, high-quality data can become the foundation on which robust regulatory compliance strategies are built.
Strengthening risk management and decision-making
Effective risk control is fundamental to fund management – in a sense, it’s the whole job. And it’s impossible without accurate and relevant data – the foundation on which risk assessments and critical decisions are made. A cloud-based, automated data management approach can help ensure that data is clean, reliable, and valid, improving the accuracy of those assessments and decision-making processes and ensuring managers can wisely determine the risk level to which the fund is exposed. With real-time access to reliable information, they can identify and mitigate controllable exposures more effectively. This proactive approach to risk management not only protects against potential losses but also builds confidence among stakeholders, from investors to regulators – and customers.
Driving cost savings through data modernisation
Finally, the right approach to data management can have a direct impact on cost savings. Many asset managers are still running older systems (some up to 30 years vintage) that are simply not designed to handle the demands of the modern financial landscape. Deploying an intelligent data management strategy not only improves operational efficiency but also reduces the risk of errors and inaccuracies that can lead to costly consequences. By streamlining data processes, fund managers can improve resource allocation, reduce redundancies and eliminate the need for costly data rectification efforts. These cost savings translate directly into profitability, allowing organisations to allocate resources more strategically.
On top of all this, it’s clear that emerging technologies based on AI technology will offer vast opportunities to the fund management sector – as to so many other industries. But to fully make the most of this evolution, businesses must adopt a modern, intelligent data management strategy. You can’t build data models without good data. Business-ready data is becoming the lynchpin that enables collaborative innovation, regulatory compliance, cost savings, risk management and exceptional customer experiences. As we enter this new era, those equipped with the right data will be at the forefront of the industry’s future transformation.
Peter Ku is VP & chief industry strategist, banking, capital markets and financial services, Informatica
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