Credit Risk Architect

Role Title: Credit Risk Architect

Location: Knutsford - 2 days a week in office

Duration: 2-3 months

Rate: £500 p/d Inside IR35

Role Description

We are seeking 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 shaping the overall architecture for the lending process-combining data, advanced analytics, and regulatory knowledge to deliver automated, efficient, and compliant decision-making platforms.

Key Responsibilities

• Architect decision platforms: Design, build, and implement technical architecture for end-to-end credit risk decisioning and affordability solutions. This includes integrating internal and external data sources, analytical models, and rule-based engines.
• Develop credit strategy: Translate business objectives and credit policy into technical requirements and system rules, defining risk appetite, decision flows, and application approval criteria.
• Oversee model integration: Work with data scientists and model developers to embed statistical and machine learning models (credit scoring, loss forecasting, affordability assessments) into decisioning systems.
• Ensure regulatory compliance: Incorporate responsible lending obligations and other relevant regulations into the framework, ensuring systems provide a robust audit trail for all lending decisions.
• Monitor performance: Create monitoring and reporting frameworks to track system and model performance, covering metrics such as approval rates, default rates, and predictive accuracy.
• Drive automation: Identify opportunities to increase automation across the credit life cycle, from application processing to portfolio management, reducing manual intervention and improving efficiency.
• Engage stakeholders: Act as a subject matter expert, advising senior management, risk teams, and business units, while clearly communicating technical concepts and strategy to both technical and non-technical audiences.

Required Skills & Qualifications

Technical Skills

• Extensive experience with decision engine platforms (eg, FICO Blaze Advisor, Pega, or other predictive/rule-based tools).
• Expert knowledge of data analysis tools and programming languages (Python, R, SAS), plus proficiency with databases and data warehousing.
• Strong background in enterprise-level system architecture, including integration of decisioning engines with customer applications, credit bureaus, and internal data sources.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their use in scaling decisioning systems.
• Expertise in statistical modelling, machine learning, and stress-testing methodologies.

Domain Knowledge

• Deep understanding of financial products and the credit life cycle.
• Strong grasp of credit underwriting, affordability metrics, and regulatory compliance requirements.