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Boston, January 29, 2013 – A new report from Aite Group outlines the benefits of using predictive analytics to improve loan portfolio management. Based on a mid-2012 Aite Group survey of 24 commercial loan underwriting professionals at North American banks, the report identifies the degree to which banks have embraced the application of predictive analytics and details barriers to the adoption of this technology.
Risk managers who are responsible for the performance of commercial loan portfolios have it rough these days. Corporations are reducing borrowing in order to deleverage balance sheets, and outstanding commercial loan balances have become riskier as a result of the anemic economy that has battered borrowers' cash flow. Add to this risk officers' need to tightly manage risk-weighted assets in order to comply with new Federal Reserve guidance on stress testing, and it is clear that risk officers are challenged with conflicting portfolio management mandates: maximize returns on loan balances, minimize risk-weighted assets, and prevent losses. While predictive analytics could be an ideal solution, it remains underutilized by banks.
“Commercial banks have the initiative, funding, and data required to use predictive analytics to improve loan portfolio management, yet adoption rates for this technology are relatively low,” says David O’Connell, senior analyst with Aite Group and author of this report. “Savvy vendors can expand offerings to serve and educate banks on the value that predictive analytics can provide in reducing loan losses.”
This 24-page Impact Report contains 12 figures and four tables. Clients of Aite Group’s Wholesale Banking service can download the report by clicking on the icon to the right. 
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To purchase this report or
for additional information,
please contact:
Aite Group Sales
Tel: +1.617.338.6050
sales@aitegroup.com
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