Crown Agents Bank is a vastly growing and regulated UK bank that connects emerging and frontier markets to the rest of the world, using FX and payments technology. We are transforming the way payments and FX move through emerging markets, reducing friction so that more money gets to those who need it. Emerging markets payments are usually challenging, expensive, unreliable and opaque. Our solutions help fix these pain points. Ultimately, we connect traditionally hard-to-reach regions to global financial infrastructure, giving access to the best prices and the fastest, most reliable settlement.
FX and cross-border payments are often complex and expensive, especially when operating in emerging markets. Crown Agents Bank (CAB) wraps its deep and trusted relationships and strength of network around innovative digital capabilities, and cross-border transaction banking solutions to enable fintech, corporates, governments, development organisations and banks to move money to, from, and across often hard-to-reach markets.
Role Purpose
The AI Analyst is an early-career role for a high-potential graduate with a strong interest in AI and a desire to apply it to real business problems from day one.
The role sits within CAB’s AI Centre of Excellence (CoE) and will rotate across the breadth of CoE activity, including business analysis, AI adoption, prompt engineering, Power Platform automation, Copilot Studio agents, and data analysis.
Working under the guidance of the AI Implementation Lead and wider CoE team, the AI Analyst will contribute directly to the Bank’s AI delivery goals by helping progress the AI use case pipeline, supporting proof-of-concept and early delivery activities, and producing clear artefacts and updates that translate AI capability into practical business outcomes. The role is designed to build broad capability quickly while delivering tangible productivity, efficiency and insight benefits across the bank.
Role Responsibilities
Strategic & Commercial Alignment
Contribute ideas to improve the value case and practical viability of proposed AI use cases (benefits, feasibility, scalability, adoption considerations).
Help gather stakeholder feedback and shape POC scope to ensure use cases demonstrate measurable value and are deliverable within constraints.
Stay informed on relevant AI and industry trends and share insights to help position CoE approaches and tooling choices appropriately.
Hands-On Delivery
Build and deliver low-complexity automations and AI agents from the AI use case pipeline—starting with closely supervised work and progressing to increased independence as capability grows.
Support solution delivery activities such as:
data preparation, basic analysis and quality checks
prompt iteration and testing
user testing, defect triage and iterative improvement
Contribute to the shared accelerator/library by documenting components, prompts, reusable flows, patterns and “how-to” notes to enable reuse and handover.
Assist with creation and maintenance of core CoE artefacts (e.g., use case library, playbooks, guidance and reporting content) to support scale and consistency.
Stakeholder Engagement & Communication
Attend discovery sessions with business teams: capture requirements, confirm next steps, and follow up actions professionally.
Act as a reliable point of contact for internal teams, maintaining clear and responsive communication.
Prepare non-technical written updates and materials (briefings, slides, status reporting, short “what’s changed / what’s next” summaries).
Support demos and workshops; over time, present prototypes and delivered solutions to end users and stakeholders to build confidence and adoption.
Risk, Quality & Compliance
Follow the CoE’s quality approach (peer review, testing and any gating/approval steps) on all work products.
Apply CAB standards under supervision, including AI Policy, GDPR, data classification and information security requirements.
Conduct quality checks on POC and delivery artefacts to ensure accuracy, completeness and alignment to agreed requirements.
Identify delivery risks (e.g., data issues, limitations, control gaps) and escalate early; maintain clear records for transparency and traceability.
Collaboration & Team Culture
Work closely with the CoE team (automation analysts, engineers, adoption/literacy colleagues) through pairing/buddying, learning by observation and hands-on contribution.
Contribute positively to team morale and ways of working; participate actively in meetings, brainstorming sessions, Lunch & Learns and knowledge sharing.
Build relationships across the bank through CoE engagement activities (e.g., roadshows, champions network, showcases).
Learning & Development
Complete a structured onboarding pathway across Power Platform, Copilot Studio, prompt engineering, data analysis, and CAB AI tooling and policy.
Achieve foundational certifications within the first 6–9 months (e.g., Microsoft PL‑900, AI‑900 and relevant follow-ons).
Seek feedback regularly and act on it to develop technical capability, delivery discipline and stakeholder skills.
Over 12–18 months, identify a potential specialism (automation, engineering, adoption, data) to support longer-term progression within the CoE.
Recent Bachelor’s degree (2:1 preferred) or Master’s degree in any discipline. All backgrounds welcome, what matters most is curiosity about AI and learning agility.
Experience
No prior professional experience required. Evidence of applied interest in AI, technology or problem-solving is strongly welcomed (e.g., projects, internships, hackathons, side work, automations or analysis).
Skills
Genuine enthusiasm for AI and a demonstrable curiosity about how it can be applied to real business problems.
Strong analytical and problem-solving mindset; able to break problems down and think logically about possible solutions.
Demonstrates a “test and learn” mindset, comfortable experimenting, iterating and improving solutions quickly
Excellent written and verbal communication; able to explain ideas clearly and adapt to different audiences.
Comfortable with Microsoft 365 (Word, Excel, PowerPoint, Teams, SharePoint) and confident in picking up new tools quickly.
Familiarity with at least one AI tool at an end-user level (e.g. Microsoft Copilot, ChatGPT, Claude, Gemini) and the ability to describe what it does well and where it struggles.
Well-organised, reliable and able to manage multiple small tasks in parallel.
Openness to feedback, willingness to ask for help and a constructive attitude when things do not work first time.
Hybrid working
Contributory personal pension plan: - Minimum: Employee 2% and Employer 7%. Employer matches contributions in 1% increments to a maximum of: Employee 5% and Employer 10%
Life Assurance – 4 times annual salary
Group Income Protection
Private Medical Insurance – this may include cover for partner and or children at company cost. Cover includes Optical, Dental and Audiology
Discretionary Bonus
Competitive Annual Leave
2 Volunteering Days
Benefit Hub