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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:
• Validation of new models or model upgrades coming from data sciences team (retail Application, Behavioral , Marketing scorecards/ Collections models/ Compliance and AML models)
• Monitoring of all existing scorecards
• Validation of regulatory models (PD/ LGD/ CCF, IFRS 9, Economic Capital and Stress testing) and pricing models such as RAROC
• Validation/ monitoring of EWS, corporate and SME models
• Validation of operational and fraud risk management models (Fraud/ DTM)
• Validation of market risk and ALM models
• 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 assessment
• Develop 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 management
• Any adhoc analysis pertaining to models and portfolios required by the CRO and risk management department
• Monitor 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 activities

Qualifications

Optimal qualification for success on the job is:

• Masters in Statistics/ Quantitative Economics/ Quantitative Finance/ MBA with a quantitative modeling background
• BE/BTech/Bstat/Bsc Eco/ BA Eco with suitable experience in analytical and risk management domains

Role 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 people
• Experience 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 advantage
• Strong conceptual knowledge in one or more of credit risk/ market risk/ALM/ AML/ Fraud risk/ collections
• Hands on/ demonstratable experience with SAS/ Python/ R
• In-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 type
• Should have excellent communication skills and ability to manage senior stakeholders across risk, modelling, audit and business verticals
• Should be a good team player
• Comfortable using excel, powerpoint, etc.