Explainer

The OWASP list for LLM applications, read from a finance desk: prompt injection, training-data leakage, and a supply chain of someone else's code.

A language model puts a probability on every possible next word, picks one, and runs the calculation again. Everything else follows from that loop.

Banks were scoring credit risk with models in the 1980s. A history of machine learning in finance, and why explainability came first.

Google researchers asked 53 practitioners about their data. Ninety-two percent had watched a data problem surface much later in a live system.

Credit scoring is named as high-risk in the AI Act itself. What the law demands of a lender, and which rulebooks apply at the same time.

Self-attention weighs every token at once, a convolution slides across pixels. Why one system writes a summary and another spots a tumor.