Quantitative analysis has long been a cornerstone of investment management as firms have sought to use data and analytical expertise to provide a competitive advantage for their clients. Quants have sometimes been referred to as financial alchemists due to their sophisticated data and analytics prowess.
Franklin Templeton [NYSE:BEN], one of the nation’s largest investment firms, was founded in New York City in 1947, and now has employees operating in over 30 countries. The California-based firm currently oversees more than $714 billion in assets under management as of February 28, 2019.
To compete at the highest levels of customer performance in a highly data-driven industry sector, Franklin Templeton is invested in the transformation of its data management infrastructure to accelerate business value. Current and point-in-time data is being parsed and analyzed to support key business initiatives. The result of this data management transformation is a modern, agile infrastructure that increases business efficiency and client returns. “The sources and volume of data for making investment decisions are steadily increasing, and this transformation of our data management platform will help us use data more efficiently,” said Chris Pham, SVP of data management and data science at Franklin Templeton.
Pham is responsible for the investment management data environment at Franklin Templeton. The firm has embarked on a transformation of its traditional data environment to a modern environment which Pham characterizes as a “completely different approach” to the process of data ingestion and data sourcing. Employing a data lake infrastructure, her team has been able to deploy the first iteration in the context what she describes as “an adaptive ecosystem” that features a hub-and-spoke model to support the firm’s equity, fixed income and other investment businesses. Franklin Templeton has achieved notable success in business process improvements such as “backtesting,” a key solution that is free from bias where an analyst can evaluate how a proposed investment strategy would perform under historical conditions. The ease and speed of working with decades of time-series data has limited this functionality in the past. The second area of success has been in incorporating alternative data sources to evaluate investable assets, which like backtesting, requires concordance and normalization of data.
Franklin Templeton is enabling these results using a Platform-as-a-Service (PaaS) developed by Boston (MA) based Elsen. Shortly after the firm launched it became part of the first class of startups accepted to the FinTech Sandbox, a cooperative initiative supported by Franklin Templeton, Fidelity Investments, Thomson Reuters, State Street Corporation, and others, which I wrote about in a 2018 Forbes article, How FinTech Initiatives Are Driving Financial Services Innovation. Elsen’s engagement with Franklin Templeton materialized, in part, due to its relationship with the FinTech Sandbox, an organization Franklin Templeton sponsors and where its SVP and Chief Technology Officer, Joe Boerio, serves as a board member. Elsen was selected as a member of the FinTech Sandbox’s inaugural class of innovative startups in 2015.
The Elsen nPlatform provides technical quants and non-technical users at Franklin Templeton with faster access to data which enables analysts to quickly develop new, data-driven investment strategies. “The sources and volume of data for making investment decisions are steadily increasing, and this transformation of our data management platform will help us use data more efficiently,” says Pham. She observes that the platform removes much of the complexity from data management. For example, the process of data normalization is simplified to make hundreds of datasets from multiple vendors readily accessible and usable. This enables Franklin Templeton to lower operating costs, rapidly generate alpha, and optimize data sources, while also supporting new initiatives in Big Data, machine learning, and AI. Franklin Templeton quants and power users can now access data directly through an application interface, and non-technical users can leverage data through intuitive, web-based applications. A proprietary engine and programming language accelerates quantitative data analysis at Franklin Templeton to a rate that is now 50 times faster than previous approaches. Leveraging the platform as a consolidated source of data that has been cleansed, normalized, and aggregated saves time and accelerates business value, while ensuring a consistent output across teams.
Unlike many of its industry counterparts, Franklin Templeton has opted not to designate a role of a Chief Data Officer, though the firm has established data council, executive data, and data governance boards. The data organization headed by Pham currently resides within the business organization, reporting to CTO Boerio, who oversees the firm’s investment management data science, Fintech, and rapid development. Elsen CEO Zac Sheffer, observes, “Franklin Templeton has proven that it can deliver excellent outcomes and help investors meet their goals through changing times.”
Investment firms have long been at the forefront of data-driven quantitative analysis. As the industry continues to invest in robust data management capabilities, Franklin Templeton is among those firms that are demonstrating a commitment to adopting modern, agile data management technology to redefine how the research and investment management business can deliver superior client and performance results.
