Junior bankers, rejoice: FactSet is working on a way to automate one of the most time-consuming parts of the job

• Data provider FactSet is helping investment banks automate their pitching process.
• The firm has recently rolled out APIs focused on helping bankers manage increased deal flow.
• Newly appointed Chief Product Officer Kristina Karnovsky told Insider about the company’s plans.

Data provider FactSet is looking to bring more automation to investment banking as robust M&A activity puts pressure on bankers.

What started out as an idea at an internal hackathon last year has sparked a wider push by FactSet to develop more application programming interfaces (APIs) to connect various tools used by investment bankers, streamline pitchbook creation, and, eventually, automate the entire pitch cycle.

“There’s just so much activity, and I’ve honestly had conversations with some banking clients where they tell me they just simply can’t hire enough bankers to keep up with the volume, with the workload,” Kristina Karnovsky, FactSet’s newly appointed chief product officer as of July, told Insider.

Dealmaking has soared in 2021, with $2.3 trillion worth of M&A deals announced globally during the first six months of the year, according to FactSet data. Meanwhile, bankers are struggling to keep pace and pressure is mounting for executives to rethink juniors’ workloads or partially swap out humans for machines.

APIs are pieces of software that allow applications to talk to each other. They’ve become key to streamlining workflows, especially those that use different tools and features. And in the past year, FactSet has doubled down on the tech, literally.

There are nearly 200 APIs in the company’s catalogue — roughly 100 of which were developed last quarter — spanning analytics, content and research, pricing, and document processing, to name a few. Of the total collection, roughly about 35 apply to investment bankers’ work, according to a FactSet spokesperson.

The APIs have been key to building up FactSet’s investment-banker client base. FactSet’s sell-side business, made up of mostly investment bankers, grew 8% last quarter, the spokesperson said.

Rather than “hire a hundred more bankers,” banks should “think about how to lift that junior banker up out of certain parts of the workflow that now can be automated because of what technology we have,” said Karnovsky, a 20-year veteran at FactSet.

FactSet is building more APIs for increased automation

Entity Recognition API, launched in February, can identify upcoming business meetings in a banker’s calendar. It can be used with another API that converts the company name into a ticker symbol, and then fetches the ticker data to pre-populate a saved pitch-book template (Bookbuilder API), which was launched in 2020.

The idea to stack APIs for investment banker automation was born out of an internal hackathon in April 2020, when an engineer developed a solution that allowed users to link the Bookbuilder API with their calendars to generate pitchbooks for upcoming meetings. Her idea was “a spark” that led to the broader investment-banking automation initiative, according to the spokesperson.

Now, FactSet is working to integrate these internal APIs with other companies’ functionalities, like customer relationship management applications. It’s also aiming to automate workflows through chatbots and Microsoft Teams, Karnovsky said.

FactSet has also developed so-called signals that are used to help drum up new business for banking clients. The data-science and machine-learning team has built different content sets to come up with predictive indicators that investment bankers use to spark conversations with clients and high-net-worth individuals.

FactSet has 45 signals currently, with “another handful in development and testing,” Karnovsky said.

To be sure, FactSet is not the only company on Wall Street looking to automation to support junior bankers.

Goldman Sachs has also invested in new technology to lift workflows and eliminate manual, but simple, tasks. It has deployed sophisticated algorithms to identify deal opportunities for clients and automated data scrubbing for comparison tables of similar companies.