Technical credit risk manager - unsecured & secured lending - Eximius Finance

ZipRecruiter; London; On-site; GBP 100,000 - 125,000; Full time

Job summary

A leading financial institution in London seeks a Credit Risk Manager to support the development and implementation of their Credit Risk Framework. The role requires extensive experience in Risk Management, particularly in Credit Risk within Financial Services. Candidates must possess strong quantitative analytical skills, including expertise in SQL, Python, and Power BI. This is an excellent opportunity to work with senior stakeholders and utilize advanced analytical tools to drive decision-making.

Qualifications

• 5+ years in a Risk Management role with a strong quantitative focus.
• Demonstrable understanding of Credit Risk management fundamentals.
• Strong experience in developing credit risk models.

Responsibilities

• Support the Head of Credit Risk in developing the bank’s Credit Risk Framework.
• Oversee Credit Risk portfolio management and reporting activities.
• Create and maintain analytical risk tools and dashboards.

Skills

Credit Risk management

Quantitative analytics

SQL

Python

Power BI

Stakeholder management

Artificial Intelligence

Tools

MS Power Query

Credit Risk Scorecard models

Job description

Job Description

The role:

• Support the Head of Credit Risk by playing a key role in developing and embedding the bank’s Credit Risk Framework and provide ongoing support in the provision of an effective, data-enabled Credit Risk management function for the business.
• Act as a quantitative, data-driven subject matter expert in the bank’s credit risk team and, where necessary, represent the team in bank-wide projects or change initiatives.
• Take ownership of overseeing the Credit Risk portfolio management and reporting activities including, but not limited to:
  • Maintaining and developing the bank’s credit risk portfolio monitoring, assessment, and reporting activities to ensure high-quality quantitative and qualitative reporting of the bank’s credit exposures to senior management.
  • Development and maintenance of the bank’s suite of key credit risk indicators and metrics used in assessing and monitoring performance against risk appetite and key risk controls.
  • Identify trends and patterns in data to assist in credit risk insights, scenario analysis, and stress testing of the bank’s credit risk exposures in response to macroeconomic developments, internal or external initiatives, and idiosyncratic events.
  • Provide clear and concise communication of complex credit risk information to colleagues, management, and governance committees.
• Be responsible for Credit Risk modelling tools used for the measurement and monitoring of Credit Risks, including development and maintenance of the bank’s Credit Risk Scorecard model, and its performance assessment and calibration, in conjunction with risk management and data science colleagues.
• Create and maintain analytical risk tools and dashboards such as Power BI dashboards (or similar) to inform and advise on risk matters within the business.

The experience:

• 5+ years in a Risk Management role with a strong quantitative focus, predominantly in Credit Risk management within Financial Services, preferably in Private/Corporate banking.
• Demonstrable, advanced understanding of Credit Risk management fundamentals, key credit metrics, and portfolio risk management.
• Strong experience in developing and maintaining models used to measure and manage credit risk, including application of concepts such as PD, LGD, and EL.
• Expert proficiency in SQL, Python, VBA, MS Power Query, BI tools (such as Power BI), and other quantitative analytical tools or methods.
• Deep experience of leveraging advanced analytical tools to extract, analyze, and interpret data, and identify trends to inform decision-making.
• Proven experience working successfully with senior stakeholders to understand, communicate, and manage risk effectively.
• Experience and knowledge in Artificial Intelligence (AI), with practical application of AI fundamentals in financial analytics, reporting, and process optimization.