(Denver, CO—June 6, 2016)— A new loss database by PayNet, the leaders providing risk management solutions and market insight to the commercial credit industry, shows the types of equipment defaults that result in a loss. PayNet studied the economic cycle, with loss outcomes on almost half a million defaulted transactions totaling over $17 billion.
“Default and loss are closely related, but very different,” says Thomas Ware, Senior Vice President, Analytics & Product Development, PayNet. PayNet developed very specialized, and predictive, loss models from the largest proprietary database of $1.4 trillion commercial loan/lease loss models in the U.S. “While defaults are important as they are a precursor to loss, at the end of the day it is truly loss that lenders really care about.”
Highlights of New Loss Database Shows:
Half of all defaults are “Nuisance” defaults, conceivably 150 days past due or more, so these defaults have a 0% loss experience. , These are most common in a few major borrower types: Hospitals, Government, Universities/Schools, and Utilities.
Financial institutions with specific expertise in an asset class have 25% lower losses because of their asset expertise.
Equipment type, transaction size and how soon after origination a transaction defaults determine the likelihood and magnitude of a loss. The stage of the economic cycle is a big driver as losses in a recession can run 100 – 200% higher than during expansions.
The new loss database will help equipment finance lenders manage credit provisions through the economic cycle. It is also expected to assist in complying with the new Current Expected Credit Loss (CECL) requirements from FASB as well as regulations such as stress testing.
PayNet is unveiling this new loss database at the Equipment Leasing Finance Association (ELFA) Credit & Collections Conference in Denver June 5-7, 2016. Thomas Ware, PayNet’s Senior Vice President, Analytics & Product Development will be presenting this information to industry executives Monday June 6 at 3:00pm Using Analytics to Boost Your Bottom Line.
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