Blog
Explainers and worked examples on financial due diligence, audit and controls, and valuation — and how finance teams turn raw data into defensible, fully sourced work.
AI & agentsHow AI is used in banking and finance (2026)
AI in banking and finance is really two generations under one label — mature statistical and ML systems that run fraud, credit, and trading decisions, and a newer wave of generative and agentic tools for drafting and triage. A practitioner survey of where each is deployed, how mature it is, and what it still can't do.
10 min readRead more
AI & agentsAI in trading: what's real and what's hype (2026)
AI in trading means bounded, checkable jobs — executing orders, scoring signals, reading sentiment, backtesting, monitoring risk — not a system that predicts where a price is headed. What's genuinely useful, why the "best AI trading app" hype breaks down, and a four-step research workflow with copy-paste prompts.
10 min readRead more
AI & agentsMachine learning in finance: applications that actually work
Machine learning in finance is the quiet, proven half of the AI story — credit scoring, fraud detection, algorithmic trading, cash forecasting, and document NLP, all in production for years. What each application actually does, how ML differs from generative and agentic AI, and where the limits (data quality, overfitting, regime change) bite.
9 min readRead more
AI & agentsWhat is agentic AI for finance?
Autonomous agents that run whole financial workflows end to end — how agentic AI differs from RPA and chatbots, the architecture underneath (ReAct, tool use, memory, planning), what a multi-agent system is, where it's used, and what stays human.
12 min readRead more