Credit Risk Architect

We are a global recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.

Role Title: Credit Risk Architect
Location: Knutsford (only candidates no more than one hour away from the area or willing to relocate)
Duration: 31/12/2025
Days on site: 2-3 days onsite (non-consecutive)
Pay Rate: £492 per day inside IR35

Role Description
Looking for aCredit Risk Decisioning and Affordability the architect designs and develops 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 responsibilities
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 (eg, 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 life cycle, 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 (eg, 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 modelling: Expertise in statistical modelling, machine learning, and stress-testing methodologies.
Financial acumen: Deep understanding of financial products, the credit life cycle, and the risks associated with lending.
Credit policy knowledge: Strong grasp of credit underwriting principles, affordability metrics, and regulatory compliance standards.

If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often Shortlisted within 48 hours.