Editing Ai Finance (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Algorithmic trading''' — Using computer programs to execute trades based on predefined strategies, often faster than human reaction time.
* '''High-frequency trading (HFT)''' — Algorithmic trading at microsecond timescales, exploiting tiny price discrepancies across markets.
* '''Credit scoring''' — Assessing the creditworthiness of individuals or businesses; historically using FICO scores, now increasingly ML-based.
* '''Fraud detection''' — Identifying fraudulent transactions or activities in real time, typically as a binary classification problem.
* '''Alternative data''' — Non-traditional data sources used in financial AI: satellite imagery, credit card transactions, social media sentiment, web traffic.
* '''Sentiment analysis''' — Analyzing news, social media, and earnings call transcripts for market-relevant sentiment signals.
* '''Portfolio optimization''' — Selecting asset weights to maximize expected return for a given level of risk.
* '''Factor model''' — A model explaining asset returns as a function of systematic factors (market, size, value, momentum).
* '''Risk management''' — Using AI to identify, measure, and mitigate financial risks (market, credit, liquidity, operational).
* '''Robo-advisor''' — An automated financial advisory service using algorithms to manage investment portfolios.
* '''Regulatory technology (RegTech)''' — AI applied to compliance, reporting, and regulatory monitoring.
* '''KYC (Know Your Customer)''' — Regulatory process for verifying customer identity; AI automates document verification.
* '''Anti-Money Laundering (AML)''' — Detecting suspicious transaction patterns indicative of money laundering.
* '''Explainability requirement''' — Financial regulations (ECOA, GDPR) often require that adverse credit decisions be explainable to applicants.
* '''Alpha''' — Return in excess of a benchmark; AI seeks to generate alpha by identifying non-obvious predictive signals.
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