Salary: £45,000 - £60,000

Credit Risk Analyst

About us

JN Bank UK Ltd is a newly launched UK bank, delivering savings and loans solutions to customers through online channels and our branch. The bank builds on the heritage of the Jamaica National Group of almost 150 years and more than three decades of service to members in the UK though other operations. In 2019, we became the first Caribbean bank to be granted a UK banking license, building a resourceful and tight-knit team of dedicated professionals.  We are now looking to add to our team to help deliver our ambitious growth plans.

With a commitment to trust, inclusivity and facilitating the goals and dreams of customers in a meaningful way, the bank’s employee value proposition maintains focus on respect, innovation, service and maintaining a positive work environment.


Place of work

London/remote working

We operate a hybrid model of working both in the office and remotely, with a requirement to attend the London office (SE1) at least twice a week.


Role overview

This new role, integral to the Data Science Team, is responsible for producing analytics to develop and deliver credit risk reporting and modelling.

You will be part of the team that helps with our next phase of business growth by mapping out the credit risk requirements, providing expertise and creating and developing essential reports to inform strategic decisions.  You will contribute to reporting, monitoring and providing insight on the portfolio in order to improve acquisition and portfolio management, to optimise risk reward and drive profitability, whilst ensuring customers are treated fairly, offered competitive price and given an excellent experience.  


Duties and responsibilities

  • Input into the development and maintenance of loan acquisition strategy to ensure that acceptance criteria perform within risk appetite
  • Take ownership of and produce regular Credit Risk MI in order to review and monitor application quality, and effectiveness of loan acceptance criteria (Bad Rate analysis, Dynamic Delinquency and Static Pool/Vintage analysis)
  • Use analytical and statistical techniques to identify emerging trends, and forecasts to provide insight of rule and profile performance. In order to assist the Credit Risk manager with proposal and development of ruleset updates
  • Thorough testing (UAT) of the application process to ensure risk strategy is implemented correctly in the decision engine
  • Monitor and provide analysis of the credit risk models used in loan acquisition criteria (application scorecard, pricing model)
  • Building upon the existing risk data structure used for modelling, validation and reporting


Skills, experience and qualifications

  • Strong academic background in a highly numerate, scientific or computer science discipline
  • At least two years’ experience of credit risk analytics preferably in secured lending
  • A strong working knowledge of impairments / provisions within secured and unsecured lending. Experience of developing, validating, or monitoring Credit Models
  • Experience of building and managing scorecard and familiarity with Risk Based Pricing Methodologies
  • Experience of monitoring Decision Systems and/or implementing rule set logic into decision engines (e.g., Provenir, GDS Modellica, Strategy Manager, etc)
  • Proficiency in data extraction and manipulation using SQL or R or Python to perform statistical analysis – this is hands on role
  • Analytical Mindset with a problem-solving initiative
  • Change experience (system/strategy testing or creating new reports, models and code base from scratch)
  • Excellent communication and presentations skills with the ability to express technical ideas to a non-technical audience
  • Information sponge – ability to remember fine detail and high desire to learn
  • Effective management of own time/stakeholders


To apply:

We are committed to creating a diverse and inclusive workforce. We believe it makes our company stronger. We celebrate the differences that all our colleagues bring to our business.

Please let us know if you require any adjustments to be made to the recruitment or interview process.

We regret that owing to the volume of applicants, we will not reply to you individually if you are not shortlisted for this vacancy. We thank you, in advance, for your application.

Please apply by submitting your CV and covering letter (if you wish) to

Interested in this vacancy?

Email your latest CV and salary expectations for us to review your application for this role.