[INT]Capital Markets Risk and Quantitative Analytics Intern (5892)

The Asian Infrastructure Investment Bank (AIIB) is a multilateral development bank whose mission is Financing Infrastructure for Tomorrow in Asia and beyond—infrastructure with sustainability at its core. We began operations in Beijing in 2016 and have since grown to 110 approved members worldwide. We are capitalized at USD100 billion and AAA-rated by the major international credit rating agencies. Collaborating with partners, AIIB meets clients’ needs by unlocking new capital and investing in infrastructure that is green, technology-enabled and promotes regional connectivity.

This project aims to integrate advanced Large Language Models (LLMs) and related techniques—such as Retrieval-Augmented Generation (RAG), agentic AI, and multi-agent mechanism—into comprehensive risk management workflows. Modern risk management often involves sifting through large volumes of diverse, unstructured information, including internal and external reports, market data, regulatory guidelines, and policy documents. Extracting timely, actionable or even hidden insights from these sources remains a significant challenge.  

By leveraging cutting-edge NLP methods, neural networks, graph neural networks (GNNs), RAG, and other LLM-based approaches, this internship will explore innovative strategies to enhance critical risk functions. Potential areas of exploration include: more effective early-stage risk identification, uncovering hidden risks, improvement on scenario analysis, adjusting risk appetites dynamically, and providing comprehensive guidelines based on new features or emerging risks from the new products. In short, the project seeks to identify and validate scenarios where these advanced methods can strengthen the overall risk management process.  

Expected outcomes of the internship include a high-quality research paper (with potential for conference or journal publication), a functional prototype model, and a well-documented, transferable methodology guideline. 

Responsibilities:

• Conduct a literature review on LLMs, RAG, and agentic AI methods in risk management. 
• Identify and propose novel approaches to integrate LLM-based technologies into selected risk scenarios. 
• Develop and fine-tune prototype models incorporating NLP, GNNs, and RAG, etc to improve risk identification, risk monitoring, new product onboarding, and data-driven decision-making. 
• Evaluate the prototypes’ performance, explainability. 
• Produce a high-quality research paper suitable for conference or journal publication. 
• Document the entire methodology, model development process, and usage guidelines clearly and comprehensively. 
• Prepare a transferable prototype or methodology guideline for future adoption within the risk management workflow. 
• Present the completed project details in a slide deck / project document.

Requirements:

• Currently pursuing a PhD in Machine Learning, Deep Learning, Generative AI,  or a closely related field; Master’s candidates with strong research experience will be considered. 
• Demonstrated research experience with publications in reputable ML/AI venues. 
• Proficiency in training and fine-tuning advanced deep learning and Generative AI models using leading frameworks. 
• Familiarity with LLMs, RAG techniques, GNNs, and their application to real-world data-intensive problems. 
• Strong analytical and problem-solving skills, with the ability to handle complex, unstructured data sources. 
• Fluent in English, with excellent written and verbal communication skills. 
• Capable of working both independently and collaboratively, and willing to adapt to evolving project goals.

AIIB is committed to diversity, transparency and inclusion. We believe our strength comes from having a team with the right diverse skills, experiences and abilities selected through a merit-based competitive process. We actively encourage applications from people from both within and outside AIIB members, regardless of nationality, religion, gender, race, disability or sexual orientation.

Previous experience and qualifications will determine the grade and job title at which successful applicants will enter AIIB.

Join us and help create a prosperous and sustainable Asia while growing your career in a diverse and innovative environment.