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: Optimising cloud, marketplaces & managed data services

Date: 30 June 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Financial institutions are under mounting pressure to rethink how they source, manage and distribute market data. Rising data volumes, multi-cloud adoption and the operational demands of regulations such as DORA are exposing the limits of legacy infrastructure, and driving...

BLOG

New Issue IQ and Boltzbit Partner to Slash Bond Issuance Data Processing Time by 74%

New Issue IQ, the solutions vendor dedicated to modernising primary bond markets, has announced a strategic partnership with deeptech AI company Boltzbit, to optimise the processing of new bond deal information. The collaboration reportedly delivers a processing-time improvement of approximately 74% by automating workflows that have traditionally been manual and fragmented. Through this integration, New...

EVENT

AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...