Credit Model Development & Validation Role - Model Risk Team (4-12 yrs)

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/B.Tech/Bstat/BSc Eco/ A 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.