AI is transforming industries, and finance is no exception. The traditional image of finance is all about numbers and spreadsheets, but the future is being built on Data Science and Machine Learning. If you’re an aspiring ML Engineer looking to break into the booming fintech sector, you need a portfolio that speaks the language of the industry. So, in this article, I’ll take you through three AI in Fintech project ideas you should try to boost your portfolio.
AI in Fintech Project Ideas for Portfolio
For a career in AI in Fintech, instead of generic projects, you need to build applications that solve real-world financial problems. Here are some project ideas you should try.
Building an AI Agent for Trading Decisions
First, let’s talk about building an AI agent for trading. Forget the movies, this isn’t about creating an AI that will make you a millionaire overnight. The reality is far more interesting and practical.
A traditional trading model might predict a stock’s price based on historical data. That’s good, but it’s a one-way street. A trading agent is a much more sophisticated system. It’s a program that can not only analyze data but also make decisions and take actions based on that analysis. It utilises a core model (based on reinforcement learning or LLM) as its foundation, as its true power lies in the tools you provide it.
Find a solved and explained example of building an AI Agent for Trading Decisions here.
Building a Smart Loan Recovery System
Loan defaults pose a significant challenge for financial institutions. Instead of a one-size-fits-all approach to debt collection, an innovative system can personalize the process to be more effective and empathetic.
A traditional loan recovery system sends generic reminders at fixed intervals. An AI-powered system, however, utilises predictive analytics to identify borrowers at high risk of default and personalizes the recovery strategy to increase the likelihood of a successful recovery. Working on such a problem will show your ability to build a robust predictive model for a critical business function.
Find a solved and explained example of building a smart loan recovery system here.
Building a RAG Application for Financial Documents
Financial professionals spend countless hours sifting through dense legal documents like annual reports (10-K filings), earnings call transcripts, and regulatory filings. A Retrieval-Augmented Generation (RAG) application can save them a massive amount of time.
Large Language Models (LLMs) have a knowledge cutoff; they lack knowledge of recent events or specific proprietary documents. RAG addresses this by enabling the LLM to look up information from an external knowledge base before generating a response. For financial records, this means your application can answer questions about the latest company report even though the LLM itself wasn’t trained on it. This is arguably the most modern and impactful project idea.
Find a solved and explained example of building a RAG Application for external documents here.
Summary
So, here are my recommended AI in Fintech project ideas you should try to boost your portfolio:
- Building an AI Agent for Trading Decisions
- Building a Smart Loan Recovery System
- Building a RAG Application for Financial Documents
No matter which project ideas you choose for your next AI project. Ensure that you break down your process, clearly explain your decisions, and demonstrate the impact. That’s the difference between a project and a portfolio piece.
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