Credit Risk Modeller

. Role Name- Credit Risk Modeler

Candidate Profile

Qualification MBA (Finance), preferably graduation in quantitative background Should have studied Statistics as part undergraduate /graduate level.

Skills Essential

a. Hands on Experience in building or validation of IFRS-+ or Basel-IRB models, for Wholesale / Commercial Portfolios

b. Conceptual understanding of Basel IRB/ IFRS-+/ IndAS-10+ guidelines

c. Proficiency in commonly used predictive analytics techniques such as Decision trees and Logistic Regression

d. Strong proficiency in Python / R for implementation of statistical techniques

e. Project Management / Liaison Skills / Stakeholder management

f. Effective Documentation skills

Desirable/ Good to Have

a) Underwriting/ Credit experience in Wholesale, SME

b) Professional certification such as FRM) Experience in system development life cycle, preferably in OFSAA Years of Experience 3- 5 years relevant experience in banks/ large financial institution

Job Description

a) Estimation of TTC PD, PIT PD and LGD for bank’s Wholesale portfolio in line with current methodology

b) Review of the data, process and system involved in calibration of PD estimates an ensure adherence with regulatory guidance (IRB/ Ind-AS 10+) and Industry best practices

c) Recalibrate/ Refresh the model based on latest data

d) Scope the data requirements required for new models

e) Liaise with Validation, Internal Audit and RBI on periodic basis on all matter related to PD and LGD

f) Implement and Manage Rating Models & Rating system of the bank in line with Policy

g) Act as functional Lead for automation of PD and LGD estimation tasks in OFSAA

h) Reporting & Presentation of PD & LGD estimates before executive level Committees & Board.