FS_BUSINESS CONSULTING_FSRM-QAS BANKING BOOK_STAFF
EY
Bengaluru, KA, IN
1d ago

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you.

And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Description

EY's Financial Services Office (FSO) is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with strong functional capability and product knowledge.

FSO practice provides integrated advisory services to financial institutions and other capital markets participants, including commercial banks, investment banks, broker-dealers, asset managers (traditional and alternative), insurance and energy trading companies, and the Corporate Treasury functions of leading Fortune 500 Companies.

Within EY’s FSO Advisory Practice, the Financial Services Risk Management (FSRM) group provides solutions that can help FSO clients to identify, measure, manage and monitor the market (trading book), credit (banking book), operational, and regulatory risks associated with their trading, asset-liability management, capital management and other capital markets activities.

As a credit risk analyst in the Quantitative Advisory Services under FSRM, you will be helping the client to design and implement strategic and functional changes and regulatory changes across risk management portfolio.

You will perform credit risk model development, validation and audits based on specific guidelines followed by large global financial institutions and banking organizations.

Key Responsibilities

  • Demonstrate strong knowledge and implementation capabilities on Statistics and Econometrics
  • Independently learn and work on statistical programming languages such as SAS / R / Python / MS Excel.
  • Understanding of financial products across the banking book portfolio.
  • Develop and perform validation of credit models including conceptual soundness, assessments of modelling methodology and model outcomes and evaluation of model's performance and perform benchmarking against other candidate models.
  • Create model development and validation documentation describing business purpose, model scope, model theory and logic, model performance testing, and implementation of the model developed.
  • Perform model reviews and model audits to critically comment on the model methodology and model performance trends and support in ongoing monitoring of the model.
  • Understand the market trends, demands and changing regulatory landscape faced by clients and understand their impact on the banking book models.
  • Engage with Clients and Managers on a daily basis to discuss the project needs and work with onshore and offshore teams to successfully deliver the requested tasks.
  • Actively help managing the team’s workload and ensure prioritization of activities based on stakeholders’ needs
  • Qualifications required

    Graduates :

  • Master's degree in Statistics and / or Economics, Masters / Bachelors degree in Engineering from premier institutions
  • Prior experience of working in the credit risk space model development and model validation
  • Experience of working with various regulatory models such as CCAR, CECL, IFRS9 and IRB
  • Strong background on statistical, econometric and numerical techniques and the principles of the theory of probability.
  • Specially- Logistic regression, Linear regression and knowledge of PD, LGD, EAD concepts

  • Knowledge of Machine learning techniques is desirable
  • Understanding of Model Risk Management framework comprising of development, validation and implementation for the banking book portfolio along with knowledge of Credit Risk analytics techniques is desirable
  • Ability to build strong relationships with clients and stakeholders
  • Certification in FRM, CFA is preferable
  • Strong knowledge and hands on experience on statistical programming knowledges such as SAS, R, Python
  • Data manipulation skills using SQL
  • Proficiency in MS Office Excel, Powerpoint, Word
  • Strong technical writing and verbal communication skillsA
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