Asset management firms are in the business of managing money on behalf of institutional clients -- typically pension funds and mutual funds. They operate as investment advisors that purchase and sell financial instruments, with a fiduciary responsibility to generate the best possible returns for their clients. To accomplish this, asset managers seek to “increase alpha”, meaning generating results that outperform market indices. In today’s highly competitive investments markets, asset managers are increasingly turning to so-called "alternative data" sources to deliver superior returns to the institutions that entrust them with their financial assets.
UBS was founded in 1862 in Switzerland. The firm has operated under the UBS brand since the 1998 consolidation of Union Bank of Switzerland and Swiss Bank Corporation. UBS, which is headquartered in Zurich and Basel, and is publicly traded on the Swiss and New York Stock Exchanges is one of the largest global asset management firms. Thomas Heinzl is Chief Operating Officer for UBS Asset Management, and Suvrat Bansal is Chief Data Officer and Head of Innovation. I spoke with Messrs. Heinzl and Bansal about how they are leveraging Big Data and Alternative Data to increase alpha for their clients.
Heinzl and Bansal are operating in a new data-rich investment world, characterized by massive availability of data in traditional and new varieties and formats. Massive availability dictates different ways and methodologies for managing and analyzing data. UBS Asset Management seeks to identify market and investment signals that are contextually relevant, and which will have a material impact on the performance of investments in a portfolio. The focus is on long-term performance, and the sustainability of these asset’s performance.
The new sources that constitute alternative data are typically non-financial data elements that can be used to gain better insights to assess the future price performance of invested assets. As an example, UBS is leveraging card payment information to monitor sales data against earnings estimates and potential share price impacts. These alternative data signals help asset managers minimize risk while ensuring the delivery of superior investment performance on behalf of their clients. For public pension funds, minimizing risk, and understanding a firm’s diversity and sustainability are central tenets of socially responsible investing.
UBS Asset Management is engaged in capturing alternative data to expand the volume and variety of net new data sources that can be fed into advanced analytics models that are leveraging machine learning capabilities. Some asset managers use geospatial information and satellite imagery; satellite imagery can be used to count the number of cars in store parking lots as a metric for retail sales activity. Geospatial analysis can be used to identify the geographical proximity of competitors, or in which neighborhood new stores have been opened. These beneficial indicators can help paint a picture of the health and prognosis for a business over time.
UBS is not alone in turning to analytics and alternative data to achieve sustainable value creation and increase alpha. A recent study was conducted by the New York headquartered data and analytics consultancy Element-22, with sponsorship from UBS Asset Management. The study featured the participation of 20 asset management firms with a combined $14 trillion in assets under management. Study results reaffirmed the perception that leading asset management firms are turning to advanced analytics and alternative data sources to fuel investment performance, grow their client base, and improve operating efficiency. Among key findings of the study:
- Alternative data usage is exploding, with sources including transaction data, satellite imagery, weather analysis, sentiment analysis, geolocation, and video capture. AlternativeData.org projects spending on Alternative Data sources to exceed $1.7 billion by 2020.
- Asset management firms are increasingly looking to advanced analytics and alternative data to gain an investment advantage. The study reported that 85% of firms were employing advanced analytics and 55% were using Alternative Data.
- Advanced analytics capabilities such as machine learning are being used to reduce costs and increase efficiency. Approximately 75% of firms reported using advanced analytics to aid in business operations.
- Comprehensive data capabilities are being used to manage new regulations such as GDPR, fueling investments in foundational data capabilities. Firms like UBS operate under strict data protection policies, which ensure that data is certified and compliant with local laws.
The investment industry is following suit. Earlier this month, The Wall Street Journal featured a story Alternative Data is Valued on Wall Street. The story references the firm Thasos, co-founded by MIT Professor and computer scientist Sandy Pentland, noting that “Thasos is at the vanguard of companies trying to help traders get ahead of stock moves using so-called alternative data”. According to the story, Thasos will set offer its data through Bloomberg terminals.
Heinzl and Bansal of UBS envision a rich new world of informed investment, fueled by data, with machine learning playing a central role. “We are starting to test, or apply machine learning to fund flows, product innovation, alpha generation, and risk and middle/back office operations”, they note. “Machine learning enables us to identify opportunities and make investment decisions faster”. Big Data and Alternative Data will be at the core of machine learning algorithms as asset managers seek to identify and manage risk. For Heinzl and Bansal, faster data access, richer data sources, and more robust data analytics are translating into the delivery of superior client performance. This is the front line of innovation in the asset management world – applying alternative data sources as the next frontier of a data-driven world.
