Witad Awards 2021: Vendor professional of the year (data and operations)—Masami Johnstone, CLS

Masami Johnstone, who wins the vendor professional of the year category (data and operations), is driven by creating and commercializing business lines in data services. 

Before joining CLS as head of information services, Johnstone was head of buy-side sales and development at Euronext, where she focused on building an alternative data business aimed at sophisticated investors, including hedge funds and systematic quant funds. She took what she learned there and applied it to her role at CLS.

One of her priorities after joining CLS in 2019 was to restructure the firm’s information services team. She has since built two new teams—the data science team and the data distribution channel team—which has revolutionized the way CLS uses and markets its data.

Johnstone formed the data science team starting with three members who were part of the firm’s broader data analytics team. She specifically recruited them to decode foreign exchange (FX) volatility. They now focus on data mining to derive insights from CLS’ datasets and identify relationships between them. The team uses various machine learning techniques, including deep learning, to find signals in the data they collect. As for the data distribution channel team, their client-facing expertise allows CLS to collaborate with suitable partners to maximize sales opportunities. 

In 2020, she led two new initiatives to provide a deeper understanding of FX market dynamics. Through collaboration with data analytics platform provider Mosaic Smart Data, CLS was able to analyze the impact of Covid-19 on FX liquidity and volatility. The solution was built within a few weeks and used CLS’ aggregated FX-executed trade data and Mosaic’s analytics software to provide market participants with greater transparency on FX market conditions. 

CLS also partnered with causaLens, a time-series software provider that uses causal machine learning techniques to examine the main factors driving market participants’ behavior in the FX market. The software combines multiple CLS datasets and sends out a signal when it discovers a strong correlation between them.