Current Expected Credit Loss (CECL) Overview


The strengths of AxiomSL’s ControllerView as a technological platform make it an ideal solution for hosting the entire Current Expected Credit Loss (“CECL”) process. ControllerView can aggregate multiple data sources from different systems, bringing together data from risk, finance, ALM and market data. The data can be seamlessly aggregated without duplicating it, thus avoiding database management and data governance issues.

Once the relevant bank’s data has been aggregated, it is pushed through the business rules that determine assets classification and measurement, impairment and disclosures.

For modeling, clients have multiple options. They can plug their own or third party models onto AxiomSL’s platform that will feed and run them and extract the results. Alternatively, they can write their models in R code within AxiomSL’s platform. Finally, clients can use one or several of the models already built out in ControllerView.

The entire process is transparent and auditable, along with the option to drill down to source data and track data lineage throughout. The outputs of the models, along with the other relevant data are brought together within the CECL Integration Engine.

CECL Solution & Integration Engine



Current Expected Credit Loss (CECL) Features



Current Expected Credit Loss (CECL) Background


Current Expected Credit Loss (CECL) is an accounting rule modification, introduced by the US Financial Accounting Standards Board (FASB), which will require banks to put additional reserves aside for expected—rather than incurred—loan and other credit losses in the case of impairment. CECL is calculated using quantitative methods, and will have a material effect on firms’ broader capital adequacy posture and CCAR reporting. Specifically, the new formula asks firms to account for the life of a loan from its origination via quantitative projections, rather than its status at a current point in time. For most accounting teams, this will be a relatively minor change in terms of methodology, and one which can still be broadly designed according to the contour of the institution’s loans business.

What this does mean, however, is that a far larger swath of data will be involved in completing the CECL calculation than in the past, and managing that data will become more crucial than ever given its potential impact on capital adequacy. Implementation isn’t expected until 2018, but firms will want to keep this aspect in mind as they plan for the broader CCAR process, and indeed make CECL-related data as accessible as possible.

End-to-End CECL Solution


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