AI in Finance
Last updated · 1 min read
Where AI meets your money
Fraud detection. Every time your card gets declined in a country you have never visited, that is a machine-learning model scoring the transaction in milliseconds. Fraud models learn your spending patterns and flag anomalies far faster than any rule list could.
Credit decisions. Lenders use models to estimate repayment risk. Regulators (in the US, the CFPB) require that adverse decisions are explained to you — explainability is a legal requirement, not a luxury, when a model affects your life.
Robo-advisors and chatbots. Automated portfolios rebalance themselves to a target risk level, and bank chatbots handle balance questions and card freezes. Both are narrow uses — LLMs are now making those bots conversational.
Trading. Algorithmic trading driven by machine learning has been common for years in institutional markets; retail investors mostly meet it as index funds and faster execution, not as a magic money machine.
The honest risks
Models can discriminate in subtle ways when trained on biased historical data, and "the model said no" is not an acceptable answer to a regulator — or to you. If an AI denies you credit, you are entitled to a real explanation.