Credit Risk Architect CGEMJP

Role Title: Credit Risk Architect

Duration: contract to run until 31/12/2025

Location: Knutsford (only candidates no more than one hour away from the area or willing to relocate). 2-3 days onsite (non-consecutive)

Rate: up to £506 p/d Umbrella inside IR35

Role purpose / summary

Our client is looking for a Credit Risk Decisioning and Affordability Architect to design and develop the technology strategy and systems used to assess the creditworthiness and financial capacity of loan applicants. This role focuses on building the overall architecture for the lending process, combining data, advanced analytics, and regulatory knowledge to create automated, efficient, and compliant decision-making platforms.

Key Skills/ requirements

A Credit Risk Decisioning and Affordability Architect has a wide range of responsibilities, including:

• Architecting decision platforms: Design, build, and implement the technical architecture for end-to-end credit risk decisioning and affordability solutions. This includes integrating various data sources (internal and external), analytical models, and rule-based engines.
• Developing credit strategy: Translate business objectives and credit policy into technical requirements and system rules. This includes defining risk appetite, decision flows, and the criteria for approving, denying, or referring credit applications.
• Overseeing model development: Work closely with data scientists and credit risk model developers to integrate statistical and machine learning models into the decisioning architecture. This includes models for credit scoring, loss forecasting, and affordability assessments.
• Ensuring regulatory compliance: Incorporate all relevant regulatory requirements (e.g., responsible lending obligations) into the decisioning framework. The architect must ensure the system provides a robust audit trail for all lending decisions.
• Monitoring system performance: Establish monitoring and reporting frameworks to track the performance of the decisioning system and underlying models. This includes tracking key metrics like credit approval rates, default rates, and model accuracy.
• Driving automation and efficiency: Identify opportunities to increase automation within the credit lifecycle, from application processing to portfolio management. This involves leveraging technologies to reduce manual intervention and streamline operations.
• Managing stakeholder engagement: Serve as a technical subject matter expert for senior management, risk teams, and business units. The architect must communicate technical concepts and strategic direction clearly to both technical and non-technical audiences.
• Required skills and qualifications
• The ideal candidate for this role possesses a deep blend of technical, analytical, and financial knowledge.

Technical skills:

• Decision engine platforms: Extensive experience with industry-standard decisioning software like FICO Blaze Advisor, Pega, or other rule-based and predictive analytics tools.
• Data and analytics: Expert knowledge of data analysis tools and programming languages (e.g., Python, R, SAS) and proficiency in database and data warehousing technologies.
• System integration: Experience with enterprise-level system architecture, including integrating decisioning engines with customer-facing applications, credit bureaus, and internal data warehouses.
• Cloud platforms: Familiarity with cloud services (AWS, Azure, GCP) and how they can be leveraged to scale decisioning platforms.
• Advanced modeling: Expertise in statistical modeling, machine learning, and stress-testing methodologies.
• Financial acumen: Deep understanding of financial products, the credit lifecycle, and the risks associated with lending.
• Credit policy knowledge: Strong grasp of credit underwriting principles, affordability metrics, and regulatory compliance standards.

All profiles will be reviewed against the required skills and experience. Due to the high number of applications we will only be able to respond to successful applicants in the first instance. We thank you for your interest and the time taken to apply!