Sageworks, a financial information company that offers lending, credit risk and portfolio risk solutions to banks and credit unions, today announced that it will produce and distribute research and analysis using Sageworks’ proprietary data set of loan, lease and core deposit data to assist the financial services industry in a variety of activities, including the transition to the FASB’s current expected credit loss (CECL) model specified in ASU 2016-13, Topic 326 (Credit Losses).
Initial publications of Sageworks’ research and intelligence will be available in the fourth quarter of 2018, with subsequent updates published annually or quarterly as appropriate. Users of Sageworks ALLL as well as the MST Loan Loss Analyzer software will be able to incorporate this market intelligence provided by Sageworks into their modeling and documentation efforts.
In June of 2016, when the FASB adopted the CECL ASU, Sageworks released CECL measurement functionality to users of Sageworks ALLL, with no additional fee. In a continued spirit of service to its customer base, versions of benchmark research results – at the input and output level – will be available to Sageworks customers within the Sageworks ALLL and other applications without additional license fees. Sageworks has also announced that versions of its research and inputs will be made available publicly, regardless of engagement with Sageworks or MST. Financial institutions, as well as their auditors and regulators, will have access to research reports describing critical inputs for loss and other institutional modeling as well as benchmark outputs.
“In our field work with clients implementing the standard, we have found the transition to be a statistical problem as much as a technical or project management problem,” explains Garver Moore, managing director of the Sageworks Advisory Services group. “For many institutions, especially regulated commercial banks, there simply aren’t enough first-party observations to produce a stable, meaningful projection of loss rates, defaults or other inputs. Nearly every institution we work with needs to look outside first-party experience to support certain inputs for at least one material portfolio segment -- otherwise, the institution is right back where it started, relying on massive qualitative allocation to cover for the lack of observable losses. Thankfully, the standard clearly and explicitly allows for the consideration of information from outside the institution when projecting credit losses under the CECL standard.”