CECL Subscriptions

New CECL Subscriptions
Product Code: CECL_Sub_01
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Are you a financial organization that makes loans?

Are you ready for CECL?

For more information on the new standard, check here!

Are you ready for 12/15/2018?

A new accounting standard for the determination of the current expected credit loss (CECL) has been created for financial organizations who extend loans. To estimate expected credit losses under CECL, a broader range of data than under existing U.S. generally accepted accounting principles (GAAP) is needed. The data must include information about past events, current conditions, and reasonable and supportable forecasts, which are then used to validate the allowance for credit losses.

A key feature of the updated mandate states that all of the data must be collected and stored in a single source. This means that organizations must maintain or have access to systems that gather and hold an extensive amount of data in a single source. They must also hire or have access to expertise in predictive performance modeling. This requirement, in itself, poses challenges to many smaller financial institutions.

An additional aspect of the new mandate is the requirement for CECL calculation of all extant loans currently held by an organization. Under the guidelines of the mandate, these loan calculations must be performed with reference to conditions that existed at the time that the loan was created.

SIL is unique in its retention of decades of historical environmental data, allowing even long-term mortgages and other loan projected losses to be calculated in a CECL- compliant manner.

SIL also provides some supplemental information that allows an organization to calibrate itself against other organizations in the industry. The breadth of SIL’s data allows calibrated comparisons to the done, as part of a financial organization's ongoing effort to improve its profitability and service to its customers.

SIL has been delivering predictive performance modeling since 1978. By leveraging a significant investment in chaos and catastrophe mathematics, AI development, and will extensive data storage, the repeatability and accuracy of our modeling output are acknowledged worldwide. This capability is uniquely positioned to provide financial organizations of all sizes the needed data retention, consolidation, and processing to meet CECL requirements in a timely and cost-effective manner.