Citigroup has named Muir Paterson to lead a newly formed strategic advisory group as part of a data science push for its banking, capital markets, and advisory teams.
Strategic Advisory Solutions will bring together the bank’s financial strategy, shareholder advisory, and data science groups, Paterson said in a phone interview. He joined Citi from Goldman Sachs Group in 2017 to lead the strategic shareholder advisory practice within its mergers and acquisitions unit.
Under the reorganization, Paterson says the data science effort he helped build around his role advising companies on how to defend themselves against activist hedge funds will become a more integral part of Citi’s other businesses. He is working with Ajay Khorana, the head of the bank’s financial strategy group, to make data science a stronger part of its corporate finance advice.
“Insight into what’s going on with your investor base is becoming increasingly important,” said Paterson. “We’re not trying to create the magic 8 ball,” he said, rather empower Citi’s bankers to use their judgement with the help of data analytics.
The tools Paterson has developed can help bankers understand shareholder preferences and motivations, providing them with instant information on how a company fits within an institutional investor’s’ portfolio. They might learn what types of securities a hedge fund likes to hold in certain environments, as well as how they accumulate and trade those positions, he explained.
Citi’s data analytics tools may also be used by bankers to predict possible market reactions to transactions being considered by chief financial officers, such as paying a bigger dividend or buying back more shares, according to Paterson.
Khorana said by phone that his team has been getting a lot of requests from corporate clients in the Covid-19 crisis on how to cope with the significant divergence between the views of equity markets and macro economists. The rise in stocks doesn’t match the predictions economist are making for a much larger decline in gross domestic product, he said, making it challenging for companies to manage their capital over the next couple of years.
“We have done a lot of work looking at various pandemic scenarios,” Khorana said, using the bank’s data science tools to analyze how things like GDP and unemployment feed into a company’s earnings and leverage. “When we talk with clients, the clients think the reality is more in line with what the macro economists are telling us — not what the equity markets are telling us.”