According to the latest report from the Financial Times (FT), top Swiss investment bank UBS has formally updated its hiring criteria: For graduates and interns joining its Global Banking & Markets division in 2027, an AI proficiency assessment has been added to interview sessions. Candidates must present real-world examples to demonstrate how they leverage AI tools to streamline research, analysis and deliverables, improving output quality and work efficiency.

According to the latest report from the Financial Times (FT), top Swiss investment bank UBS has formally updated its hiring criteria:

For graduates and interns joining its Global Banking & Markets division in 2027, an AI proficiency assessment has been added to interview sessions. Candidates must present real-world examples to demonstrate how they leverage AI tools to streamline research, analysis and deliverables, improving output quality and work efficiency.

UBS is among a small number of leading global large banks that explicitly include hands-on AI competency as a screening requirement for junior roles.

Notably, UBS is not using AI proficiency to replace academic qualifications, GPA, analytical skills or interpersonal communication skills. Instead, it serves as an additional evaluation criterion assessed in parallel, carrying equal weight alongside traditional academic and grade requirements.

Focus on practical use cases, not AI theory

Many candidates misunderstand this rule, assuming they must master the underlying algorithms of large language models or coding development to pass UBS’s AI-focused interviews. This is not the case.

UBS does not require proficiency in any specific AI product. Interviewers do not test how many AI concepts you can recite; they focus on your practical experience:

What tasks have you completed with AI? What flaws have you spotted in AI-generated outputs? How did you verify and revise AI content, and what final results did you achieve?

Simply put, the bank is not looking for AI research engineers. It seeks new finance professionals who can use AI well as a productivity tool.

UBS has already rolled out large-scale AI upskilling across the firm. Since 2024, more than 49,000 employees have enrolled in the bank’s internal AI training programmes, and 38,000 have finished the full learning track.

For new campus hires, the bank has built the **AI Fluency Pathway**, which trains staff to use AI responsibly and build the judgement to evaluate the credibility of AI outputs. However, this training takes place post-onboarding. At the job application stage, the firm expects candidates to already possess basic hands-on experience.

UBS stated officially:

“AI is fundamentally reshaping financial services. AI capability and practical experience have become vital to future career success and are therefore relevant hiring considerations. AI literacy complements, rather than replaces, academic, analytical and interpersonal communication skills.”

Industry trend: AI is rewriting the fundamentals of junior finance roles

UBS’s policy shift is not an isolated case. Banco Santander in Spain has also explicitly looked for “advanced AI users” in its graduate programme for corporate investment banking. The tide across the whole industry is changing.

Morgan Stanley analysts have predicted that over the next five years, more than 200,000 banking roles in Europe may be impacted by the combined effects of AI adoption and branch network downsizing.

AI is taking over much of the basic work once done by junior analysts: sorting industry information, organising preliminary financial data, drafting presentation slides and summarising public documents.

Previously, new banking recruits spent large amounts of time on repetitive, manual information compilation.

Now AI can finish such basic tasks rapidly, shifting employers’ expectations for new hires. Firms no longer simply recruit people to carry out tedious manual labour. They want talent who can command AI, validate its outputs, and focus their energy on high-value judgement and business communication.

A key point to clarify: the banking sector’s emphasis on AI skills does not mean roles will be fully replaced by AI. The industry logic is AI augmentation of humans, not full replacement.

AI-generated content commonly suffers from hallucinations, data inaccuracies and detachment from real business scenarios. Human practitioners are still required for validation, decision-making and business implementation. Companies want applicants who understand the business and know how to use these tools.

Practical takeaways for international students job hunting

Competition for overseas finance roles remains extremely fierce. Strong GPAs, elite university backgrounds and internship experience have become standard qualifications for most applicants. Hands-on AI experience is emerging as a new differentiator.

Drawing on UBS’s hiring update, here are actionable tips for international students applying for overseas finance positions:

1. Avoid vague phrasing such as “proficient in AI tools” on your resume and in interviews.

Interviewers want real STAR-method examples. Coursework, class projects, internships or club activities can all serve as material. Clearly explain what problem you solved with AI, how you refined your prompts, how you checked and fixed AI errors, and what outcomes you delivered. Generic descriptions will not pass evaluation.

2. Distinguish casual AI usage from AI application in professional scenarios.

Using AI for short videos or casual writing is not the AI competency recruiters seek.

For finance tracks, intentionally practice tasks such as quickly dissecting industry materials, summarising financial reports, conducting preliminary comparative analysis and drafting business presentation slides. Build the habit of double-checking AI outputs; data and facts in finance contexts must always be cross-referenced.

3. Do not put the cart before the horse.

AI is only a productivity tool. Professional expertise, financial analysis, logical reasoning and communication remain core foundations.

Do not pour all your energy into testing AI tools while neglecting subject knowledge. As UBS has clarified, AI literacy is supplementary and will not replace traditional core competencies.

4. This trend will spread beyond UBS to more overseas big tech firms, investment banks and consulting roles.

Even if some employers do not write this requirement explicitly in job descriptions, the likelihood of being asked about your AI usage experience in interviews will keep rising. Building practical AI project cases in advance will boost your competitiveness among candidates.

Under the AI wave, the rules of overseas job hunting are evolving.

Prestigious degrees and standout internships still act as entry tickets, but proficiency in harnessing AI tools is gradually shifting from a bonus advantage to a basic requirement.

For international students, rather than waiting passively for employers to set new requirements, actively integrate AI tools into your projects and internships to build your unique hybrid competitiveness.