Risk: Risk Analytics Team INTERNAL USAGE: No. of Vacancies: Reports to: Is a Team leader?Y/NTeam Size: Grade:M - SM Business:Corporate CenterDepartment:�RiskSub-Department:- Location: CO About Risk The Risk department ensures that the Bank�s risk is managed through a risk management architecture as well as through policies and processes approved by the Board of Directors encompassing independent identification, measurement and management of risks across the various businesses of the Bank. The Risk department of the Bank strives to proactively anticipate vulnerabilities at the transaction as well as at the portfolio level, through quantitative or qualitative examination of the embedded risks About the Role The Risk Analytics team is responsible for the estimation of risk parameters (PD, LGD & CCF) for internal & regulatory purpose, Ind AS ECL implementation and execution. They are also responsible for identifying and tracking key risk indicators and early warning signals and conducting regular stress testing, economic capital and ICAAP, tracking model performance, suggesting improvements and implementing approved changes Key Responsibilities � Responsible for tracking portfolio trends and hot spots � Responsible for tracking early warning signals, root-cause analysis, covering Business Segments, Sector and Groups � Provide timely and actionable insights to the top management and business heads � Provide key risk inputs to the capital computation process � Track RAROC for customer, product, portfolio (segment, industry) � Estimation and validation of IRB (Capital Computation Approach) � Manage IRB Capital run and reporting process. � Responsible for the development of Credit Risk models and revamp of new models�������������������������� Qualifications Optimal qualification for success on the job is: � Post graduate with specialization in Quant and statistics viz. Masters in statistics, MBA, M Tech with relevant risk analytical exposure (Risk, Collections and Fraud) � Hands on experience in Advanced & Predictive analytics, Decision Tree, Segmentation analysis and Cluster analysis using analytical and statistical procedures Role Proficiencies: � Should have strong analytical & problem solving skill � Should have strong working knowledge of SAS, R, Python and data mining tools � Be able to influence stakeholders on data driven strategies � Should have good communication, presentation and inter-personal skills � Should have high level of motivation and be a fast learner