About the Role :
Model Risk team is involved in review, validation, maintenance and monitoring of regulatory or decision-making models / rule engines / computation platforms in the areas of credit risk, operational and fraud risk and market / liquidity risk across retail and corporate businesses.
Key Responsibilities :
KRAs would include the following :
- Perform validations in one or more of the below domains :
a. Validation of new models or model upgrades coming from data sciences team (retail Application, Behavioral , Marketing scorecards / Collections models / Compliance and AML models)
b. Monitoring of all existing scorecards
c. Validation of regulatory models (PD / LGD / CCF, IFRS 9, Economic Capital and Stress testing) and pricing models such as RAROC
d. Validation / monitoring of EWS, corporate and SME models
e. Validation of operational and fraud risk management models (Fraud / DTM)
f. Validation of market risk and ALM models
g. Validation of system platforms for risk and lending models (e.g. for ALM, for Treasury and Market Risk, for Operational and Compliance Risk, for Rating and Retail Scorecards etc.
Active involvement in model governance activities such as framework updates, inventory maintenance, materiality assessmentDevelop and deliver training programs for validation staff and other stakeholders on model validation concepts and techniques.Participate in model governance committees and working groups and provide regular updates and recommendations to senior management.Preparation of reports and presentation materials for risk committees and senior managementAny adhoc analysis pertaining to models and portfolios required by the CRO and risk management departmentMonitor and evaluate emerging risks and trends in model validation and provide guidance and recommendations to senior management and other stakeholders.Contribute to regulatory submissions and IA activitiesQualifications :
Optimal qualification for success on the job is :
Masters in Statistics / Quantitative Economics / Quantitative Finance / MBA with a quantitative modeling backgroundBE / BTech / Bstat / Bsc Eco / BA Eco with suitable experience in analytical and risk management domainsRole Proficiencies :
6-12 years of experience of working in a team either as an individual contributor in one or more of the above mentioned or also managing a team of 1-2 peopleExperience in design and development of Statistical models using regression (logistic and ML / AI techniques such as GAM / Machine learning / Decision Trees), optimization, time series, survival modelling techniques will be an added advantageStrong conceptual knowledge in one or more of credit risk / market risk / ALM / AML / Fraud risk / collectionsHands on / demonstratable experience with SAS / Python / RIn-depth knowledge of regulatory requirements related to model validation.Readiness to work with data at a granular level, write codes and create programs to undertake any analysis as required (while the person may have a small reporting team, but he / she should be willing and able to extract, process data and generate metrics and insights himself / herself)Basic understanding of different business lines and products / processes in the bank (retail banking / corporate banking / treasury etc.)Readiness to learn about new types of modeling methodologies / new areas / new concepts / willingness to work out of comfort zone; be flexible rather than being a specialist in a particular domain or model typeShould have excellent communication skills and ability to manage senior stakeholders across risk, modelling, audit and business verticalsShould be a good team playerComfortable using excel, powerpoint, etc.ref : hirist.tech)
