Boston, June 25, 2018 — DataRobot, the founder of automated machine learning, today announced it has appointed H.P. Bunaes as the Director of Banking. Bunaes joins DataRobot from SunTrust Banks, where he led the design and development of the risk data and analytics infrastructure used in credit decisioning, pricing, portfolio management, and reserve and capital adequacy.
At DataRobot, he will be responsible for helping banks leverage AI and machine learning to increase speed to market, improve model accuracy, and reduce the cost to develop, deploy, and maintain AI and analytics initiatives.
Bunaes has 35 years of experience in banking, with broad banking domain knowledge and deep expertise in data and analytics. Prior to joining DataRobot, he held a variety of leadership positions at SunTrust and at FleetBoston in Risk Management, Finance, and IT. Most recently, Bunaes was senior vice president and consumer bank data officer for SunTrust building the first business intelligence and data office for the national consumer lending, consumer banking, and private wealth management business lines.
“H.P. is a seasoned executive whose experience will support DataRobot’s commitment to helping banks be more AI-driven so they can grow revenue, reduce costs, and manage risk,” said Jeremy Achin, CEO of DataRobot. “H.P. is a tremendous addition to the team and he will help further establish DataRobot as the trusted advisor banks need to solve their machine learning and AI challenges.”
While at SunTrust, Bunaes also spearheaded an enterprise-wide anti money laundering initiative, including implementation of a real time risk assessment engine and due diligence framework for new client on-boarding.
“I know firsthand the challenges banks face generating insights from data—processes can be manually intensive, predictions imprecise, and managing the data and modeling infrastructure difficult and expensive. DataRobot’s machine learning platform addresses all of these and allows banks to automate modeling and quickly and efficiently extract insights and deploy capabilities that deliver bottom-line benefits,” said Bunaes. “This is why joining DataRobot was a no brainer, and I’m excited to help banks use machine learning to make their investments in data science pay off.”
The DataRobot automated machine learning platform empowers business analysts and data scientists of all skill levels to build and deploy highly accurate machine learning models in a fraction of the time of traditional modeling methods. To learn more about how banks are using DataRobot toimprove modeling, lower costs, and reduce regulatory risk, please visit https://www.datarobot.com/banking.
H.P. will present best practices for banks using AI and machine learning to mitigate risk and ensure regulatory compliance in his conference session, “Using AI and Machine Learning in AML,” at the Automation and Operational Efficiency in KYC Forum taking place June 25—26 in New York City.