Make Risk Management Compliant, Robust, and Fail-Proof

Changes in regulations require companies to strengthen their internal policies and strategies for 100% compliance and protection against repercussions. Risk management teams that are pressed for time and resources lose comprehensive oversight and focus on only high-risk models. Evalueserve helped a US bank in ensuring compliance, continuity, and zero gaps

Supervisory guidance note SR 11-7 mandates that all US-based banks must maintain rigorous governance mechanisms for model risk management. Ongoing model monitoring is one of the most important elements. It requires quarterly reporting with a wide range of metrics, including model discriminatory power and performance, population and characteristic stability indices, backtesting, benchmarking, and override analysis. Producing these detailed reports for a large set of models is a challenging task because of the ever-evolving guidelines and the dynamic business environment.

 In response to US federal mandate SR 11-7, our client needed to streamline their model monitoring and reporting process, which covers more than 60 regulatory and other credit risk models.

 The bank’s model risk management team was only able to focus on high-risk models, not provide comprehensive oversight, because of:

• A shortage of people with experience in statistical and credit risk analytics
• Undeveloped or incomplete documentation on old models
• Changing regulatory expectations leading to changes in internal guidelines
• Changes in credit and collection policies

We set up a dedicated team with experience in credit risk model monitoring and various data analytics tools, including SAS. A senior risk specialist supported the team.

Our focus was stabilization and enhancement of the processes covering all the bank’s automobile lending models at the segment level: origination, behavioral and BASEL (PD, LGD, and EAD) models.

 By performing all of the analytics, reporting and documentation of credit risk model monitoring processes and methodologies, our team ensures comprehensive support, delivering insights into the impact of market condition changes, borrower profiles, product features and policy changes on model performances.

In addition, our team standardized the existent processes, cleansed SAS codes, created detailed SOPs, and developed model performance histories for old models in low- and medium-risk categories

Providing expertise for both the missing analytics and process improvement helped the client achieve effective compliance with several essential requirements under SR 11-7.

An important gap in the governance process was closed thanks to the implementation of model monitoring for old and low-priority models. The detailed process documentation ensures continuity and easy knowledge transfer in the event of future loss of key personnel.

Clean SAS codes, data validation routines and process automation helped to increase the overall volume of work delivered and significantly increased the accuracy. The team now monitors 61 models – over twice as many as at the start of this partnership one year ago.