Risk Analytics Degree Apprenticeship Programme

What is Decision Science?

Decision Science is a central team that partners with every area of the bank—particularly functions that use models. We build and maintain the statistical models that determine who we lend to, how we manage customers throughout their product lifecycle, and how we assess risk. We work directly with product teams to quantify risk and deliver clear, actionable insights that shape decisions and help the bank respond to change. We also own all impairment financial reporting and support key regulatory publications shared outside the bank. It’s a fast-paced, wide-ranging team that uses analysis, presentations, and documentations to create clear outcomes from raw data.

What does a typical day look like for you?

My team covers Model Development, Governance, Validation and Implementation, so my week cycles through each of them. I start every week with a full team catch up, to highlight key focus areas and deadlines for the week, followed by colleagues collaborating on task updates, feedback and support, and priorities. I then split my time between current projects and collating and summarizing that work into clear updates, to the executive team. I review our plans to ensure we’re hitting key milestones, as well as engaging with suppliers, stakeholders, and auditors to drive new projects and manage our existing relationships. I like to get into the detail of any problems that arise, and help support the analysts through coaching and mentoring, to help them grow in their roles.

What is Risk Analytics?

The Risk Analytics team plays a pivotal role in supporting Shawbrook Bank’s risk management strategy by transforming data into actionable insights. Like Decision Science we work collaboratively with various risk teams across the bank and partner with the Data Engineering function, to embed data-driven decision-making throughout the organisation. Our focus is on enhancing the bank’s insight capabilities through advanced BI tools such as Power BI, creating intuitive dashboards and automated reports, that provide stakeholders with timely, accurate, and meaningful analysis for effective risk oversight and strategic planning. We also partner with stakeholders and Data Engineering to integrate new data sources, automate manual processes and improve data quality. This streamlines workflows, reduces operational risk, and strengthens the overall risk of data infrastructure.

What does a typical day look like for you?

An average day in the Risk Analytics team blends analytical delivery, collaboration, and problem-solving. The team provides weekly and monthly reports that support risk colleagues across the bank with accurate, timely, and actionable insights. We also work closely with stakeholders to understand and prioritise requirements for new data sources or dashboards, translating these needs into clear specifications for the Data Engineering team,  to implement or enhance data pipelines. A significant part of the role involves building and maintaining Power BI dashboards, leveraging the bank’s data to provide meaningful insights and visualisations. The team also handles ad hoc analysis requests, delivering data-driven responses to one-off questions or emerging risk issues as they arise.