Assistant Vice President - Credit Risk - RWA - Banking

Assistant Vice President - Credit Risk - RWA

Principal responsibilities:

- The incumbent will be required to work extensively in an integrated team environment to work on portfolio MI and reporting, exploratory data analysis, data anomaly identification and remediation.

- Support deep dive analysis on the credit and lending portfolio like identification of low return clients and analysis of concentration risks, Economic Capital, Credit Risk and RWA consumptions.

- Proficiency in working with huge volumes of data and data visualization techniques, Ability to build data visualization dashboards using Tableau or any other equivalent software.

- Develop and build an understanding of the Basel norms around the key metrics for credit such as Expected Loss, Risk Weighted Assets (RWAs), Exposure at Default, Probability of Default, Credit Risk Rating and Loss Given Default

- Analyze the credit risk composition and the drivers of credit risk & profitability metrics of the global wholesale credit & lending portfolio.

- Help associates in developing an in-depth expertise in the assigned sector, industry, region, country and client relationships within the portfolio.

- Work independently; lead execution on straightforward situations; effectively deploy internal and external resources.

- Share information, knowledge and ideas with the team, Understand and ensure compliance with all relevant internal and external rules, regulations and procedures that apply to the conduct of the business in which the jobholder is involved.

Qualifications:

- Must have 10-14 years of relevant work experience

- MBA in Finance from a reputed institute preferred

- Understanding of Basel norms/Risk Weighted Assets is highly desirable

- Good understanding of credit risk concepts and risk & return profitability measures

- Good understanding of corporate finance, banking and associated Bank book products & trading-book products

- Competency in Microsoft office applications, especially MS Excel, MS-Access and Power-point presentations

- Knowledge of working with Alteryx/SAS/ SQL/Python, R or any other programming language is desirable

- Experience working with large volumes of data and using ML techniques to drive inferences

- Knowledge of working with Tableau, QlikView or QlikSense or any other data visualization software is desirable