Credit Risk Specialist – Assessment & Validation Job Careers – DFCU Bank

Organization: DFCU
Duty Station: Kampala,
Reports to: Head
of Credit Risk Management
About US:
DFCU Bank is a fast
growing commercial bank offering a variety of innovative products and services.
DFCU Limited was started by the Commonwealth Development Corporation (CDC) of
the United Kingdom and the Government of Uganda through the Uganda Development
Corporation (UDC) under the name of Development Finance Company of Uganda
Limited. Later restructuring brought in DEG (of Germany) and International
Finance Corporation (IFC) as equal partners with CDC and UDC, each having a 25%
stake in the company. Its objective was to support long-term development
projects whose financing needs and risk did not appeal to the then existing
financial commercial lending institutions.
Job Summary:  The Credit Risk Specialist – Assessment &
Validation will drive the standardization and operationalization of the bank’s
model risk governance framework through validation of model and model-based
decisions/ guidelines, enhance the accuracy of credit analytics &
predictive models to mitigate losses arising out of errors and minimize shocks
arising from changes in the macro-economic environment and sector trends on the
bank’s performance.
Key Duties and Responsibilities: 
  • Be responsible for the collation, analysis (including trend
    analysis) and publication of the Key Credit Risk Performance Indicators.
  • Design relevant risk reporting tools & templates and prepare
    timely, comprehensive and reliable credit risk reports.
  • Proactive assessment of Industry/ Sector risks and performance to
    guide prioritization of business efforts.
  • Conduct Macro economic analysis and forecasting and advise the bank
    on possible impact to performance.
  • Participate in conducting of periodic Credit stress tests and
    scenario analysis, assessing the impact on the Bank’s credit portfolio and
    make appropriate recommendations to senior management for action.
  • Assess the quality of the overall loan portfolio through trends and
    other analytical risk indicators, to improve credit collections and
  • Benchmarking quantitative and qualitative risk appetite and
    tolerances, as well as limit structures, relative to sound industry
    standards and regulatory expectations, while considering the bank’s
    business strategies.
  • Analyze performance qualitatively and/or quantitatively, detecting
    emerging risks and/or deviations, and recommend actions to mitigate losses
    and improve performance and profitability.
  • Perform regular portfolio surveillance including earnings review and
    credit market spreads.
  • Review the Bank’s credit analytics to enhance its accuracy and
    support in the review, understanding and management of model risk to
    mitigate losses arising from errors.
  • Assessment of model development and model review activities within
    various risk management domains.
  • Operationalization of the model risk governance framework covering
    both model development and model validation by engaging all stakeholders
    to establish solid model risk management.
  • Validation of assumptions, formulae and methodologies in the
    guidelines and processes for developing models and provision of
    recommendations in the regular improvement of the models (upgrade towards
    predictive models) to avoid and mitigate losses to the Bank; Including but
    not limited to rating parameters (EL, PDs, LGDs, EAD etc.), pricing and
    capital allocation models, RAROC framework, Credit Var estimation and
    regulatory Capital estimation (Standardized approach and Internal Rating
    Based approach).
  • Validation (for improvement) of the statistics used in portfolio
    analytics such as credit limit setting, loss forecasting, allowance for
    portfolio losses, loan stress testing, capital allocation etc.
  • Validation of model governance policies, standards, processes and
  • Validation of compliance with regulatory and statutory model
  • Advise Senior management on model risk management following
    independent model validation activities.

Qualifications, Skills and Experience:
  • The applicant for the DFCU Bank Credit Risk Specialist – Assessment
    & Validation job placement must hold an undergraduate degree in
    mathematics, statistics or quantitative economics.
  • CFA qualification will be an added advantage
  • Four years of working experience in a financial institution
  • Knowledge of data analysis and validation tools
  • Knowledge of data modelling, data cleansing, and data enrichment
  • In possession of formal research training
  • Highly numerate and analytical
  • Statistical modelling, interpretation and translation
  • Risk management (Credit and Market Risk) and commercial grounding
  • Capacity to develop and document procedures and workflows
  • Knowledge on macro-economic and sector performance tools
  • Ability to carry out data quality control, validation and linkage
  • An understanding of data protection issues
  • An awareness and knowledge of industry-specific databases and data
  • Experience of statistical methodologies and data analysis techniques
  • Ability to produce clear graphical representations and data visualizations
  • Ability to pay attention to detail
  • Ability to communicate well and be highly organized
  • Ability to translate analytics and provide insight and analysis
    through clear visual, written and verbal communication.
  • Highly curious and inquisitive
How to Apply:
All candidates who
so wish to join the banking sector in the aforementioned capacity are
encouraged to send their applications with detailed CVs including present
position and copies of relevant professional/academic certificates (University
Transcript, O & A level) to:
Deadline: 22nd January 2019
NB: dfcu
Bank does not solicit/accept payment in cash/kind from prospective candidates
in exchange for shortlisting or job placement. Any candidate who engages in
this kind of transaction is aiding and abetting fraud and will be automatically
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