Asset managers are facing a range of demands including compressed profit margins, fee pressures, the ongoing cost of regulation and changing investor preferences that are shifting to low-cost Exchange-Traded Funds and index-tracking funds. Francis Jackson, RBC Investor & Treasury Services' Head of Global Client Coverage shares his insights.
Francis Jackson
Head of Global Client Coverage
A recent paper by Oliver Wyman highlighted the scale of the challenges facing asset managers. The report acknowledged that while assets under management grew by 13 percent in 2017, profits lagged by 9 percent and absolute costs rose by 8 percent.1 This is resulting in asset managers looking to reinvent operating models while they search for a competitive edge to help them attract new investors. The role of big data will be a critical element for managers in achieving these objectives.
The adoption and intelligent application of data offers a number of benefits for asset managers. For example, harnessing and utilizing data in the investment process could help managers boost alpha generation by providing an information advantage others may not have. Smart data management, where information is stored and analyzed in a single location, will make it easier for managers to perform risk oversight, regulatory compliance and service provider monitoring. This may also allow for cost and resource efficiencies.
Key insights
- Applying big data analytics in fund distribution will be pivotal for asset managers to become more competitive
- Well-capitalized and resourced service providers with robust technology platforms are in a strong position to help managers with their distribution data analytics
- Big data can bring a commercial upside, but with consumers and regulators becoming more sensitive and stringent about how personal information is used, asset managers need to tread carefully
Leveraging data and winning mandates
Introduced in January 2018, the European Union's Markets in Financial Instruments Directive (MiFID II) has imposed product governance requirements on asset managers to prevent them from mis-selling higher-risk funds to retail consumers. As a consequence, asset managers must obtain information from distributors about their target market and attest that products are being sold to the correct investor demographic. If client requirements are not appropriately identified, asset managers could be selling or distributing products that are misaligned with their customer’s risk and return profiles, and expectations.
In light of this, big data can play a significant role in fundraising and product distribution. Barring a handful of USD 1 trillion plus asset managers, there are a limited number of mid-sized firms (i.e., those with assets under management of less than USD 500 billion) that have used data analytics to acquire insights into the behaviour or needs of their clients.
The requirement for a more granular view of clients’ buying preferences represents a potential commercial opportunity where holders of client data can aggregate that information, add relevant insights, and provide to asset managers to support their strategic business objectives. For example, the data that RBC Investor & Treasury Services maintains has the potential to highlight diverse distribution metrics; sharing that tangible and real-time information with managers would be useful intelligence for them to have during the fundraising process. It also serves to identify buying patterns of multiple or individual investors, allowing manufacturers to create products that are far more tailored or nuanced to that client base.
Harnessing and utilizing data in the investment process could help managers boost alpha generation by providing an information advantage
Further drill-down analysis of distribution data at the market level, could also help asset managers benchmark how product sales compare to a broadly similar competitor or strategy set. If there appears to be a divergence between the two, the asset manager can take further action and adjust their distribution strategy accordingly.
Moving to the next stage
Technological innovation continues to drive efficiencies. By flowing data in centralized data lakes or warehouses, then applying artificial intelligence and robotic process automation tools, companies can organize and surface previously unstructured data into useable forms that can be analyzed to detect trends, irregularities and errors. Once information is properly structured and formatted, it can be more readily shared with clients.
The requirement for a more granular view of clients’ buying preferences represents a potential commercial opportunity
While large asset managers are willing and able to invest in the resources to perform such data analytics in-house, mid-sized firms are looking for more economical solutions. Amid the pressures facing the financial services industry today, these asset managers may not need to invest heavily in technology platforms when external providers have the resources and infrastructure already available. Furthermore, for fund houses wanting to derive insights from big data, acquiring and retaining the necessary qualified resources is difficult, given that they are competing for talent with virtually all other industries including companies with significant brand loyalty.
Safe data
With asset servicers looking after more client data, controls and protections around that information need to be increased. Across the industry, data security is a key risk issue with clients increasingly requiring assertions that cybersecurity and data protection are of the highest standard. European Union legislators, through the General Data Protection Regulation, have now codified the basic data management criteria that firms must adhere to, along with the penalties should they fall short. While big data opens the door to a number of commercial opportunities, its users must act responsibly and safely.