About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

DataRobot on FactSet Adds Machine Learning into Investment Workflow

Subscribe to our newsletter

In early August, FactSet and DataRobot introduced an artificial intelligence (AI) investment workflow, DataRobot on FactSet, an automated machine learning (ML) tool that helps financial services firms – particularly those lacking significant data science teams – incorporate AI into their investment workflows.

At the moment there is a shortage of data scientists within the investment management industry – in particular, those who know how to code in Python –at a time when demand for this skill set is continuing to grow. For. example, for certain portfolio modelling or risk analysis approaches, investment management teams need to have in place automated data collection that will update their algorithms.

According to FactSet, the DataRobot on FactSet solution integrates machine learning technology from DataRobot into the FactSet platform, enabling clients to build, deploy, monitor, and manage sophisticated machine learning models quickly and easily. Investment managers without specific data science knowledge can use the tool to create AI applications for areas such as equity volatility, bond performance, and macroeconomic event predictions.

FactSet says the tool provides the guardrails required for investment managers without data science expertise to build and deploy advanced machine learning. For firms that already have existing data science teams, DataRobot on FactSet can increasing the speed and scale of their financial models, the company says.

“Clients are looking for more effective data and AI tools that will help them surface new investment insights faster and with greater efficiency,” said Rob Robie, executive vice president, analytics, at FactSet. “We are excited to be working with DataRobot to provide an elegant and intuitive solution that allows users to develop and execute successful machine learning strategies.” FactSet had already been using DataRobot tools internally for its own needs for several years.

“There is an unprecedented opportunity for investment professionals to capitalise on their data, and now is the time to adopt robust AI and machine learning capabilities,” said Rob Hegarty, general manager of financial markets and fintech, DataRobot. “We’re excited to work with FactSet on this dynamic integration which will help more organisations make data-driven decisions and realise the true value of AI.”

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Data platform modernisation: Best practice approaches for unifying data, real time data and automated processing

Date: 17 March 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Financial institutions are evolving their data platform modernisation programmes, moving beyond data-for-cloud capabilities and increasingly towards artificial intelligence-readiness. This has shifted the data management focus in the direction of data unification, real-time delivery and automated governance. The drivers of...

BLOG

AI Personalization in Trading: Where We Are and Where We’re Heading

Ivan Kunyankin, Data Science Team Lead at Devexperts. AI may have started out its brokerage career in back-office, enhancing operational efficiency by providing human teams with actionable client insights, but it’s now being promoted to more sensitive client-facing roles. As AI tools continue to evolve and become normalized in more areas of daily life, financial...

EVENT

AI in Capital Markets Summit London

Now in its 3rd year, the AI in Capital Markets Summit returns with a focus on the practicalities of onboarding AI enterprise wide for business value creation. Whilst AI offers huge potential to revolutionise capital markets operations many are struggling to move beyond pilot phase to generate substantial value from AI.

GUIDE

ESG Data Handbook 2022

The ESG landscape is changing faster than anyone could have imagined even five years ago. With tens of trillions of dollars expected to have been committed to sustainable assets by the end of the decade, it’s never been more important for financial institutions of all sizes to stay abreast of changes in the ESG data...