FIS Launches Neural Treasury AI Suite as Stock Climbs 0.04% Amid $10.3B Revenue and Top 500 Trading Volume Ranking

, , . The cloud-native platform integrates machine learning and robotics to streamline liquidity management and fraud detection, featuring Treasury GPT, a specialized large language model. The launch follows recent industry recognition, including awards at the 2025 Treasury Management International and Global Finance Treasury Awards.

Analysts highlighted mixed signals in the company’s Q2 2025 results. While full-year revenue guidance was raised, earnings and revenue fell slightly below expectations, . , maintaining “Outperform” ratings despite concerns over flat EBITDA margins and organic growth guidance.

The Neural Treasury suite aims to democratize AI tools for mid-market firms, addressing legacy system limitations in treasury functions. IDC’s called it a “notable advancement,” while FIS executives emphasized its potential to enhance cash flow forecasting and automation. The product’s market reception will likely influence investor sentiment ahead of broader AI adoption in financial services.

To run this back-test rigorously I need to nail down a few practical details: 1. Universe – “Top 500 stocks by daily trading volume” – which market/universe should we scan each day (e.g., all U.S. listed common stocks on NYSE + NASDAQ, or some predefined index such as Russell 3000)? 2. Trade price and execution timing – Should we assume we buy at that day’s close and sell at next day’s close (close-to-close return), or buy next day’s open and exit that same day’s close (open-to-close)? 3. Transaction costs / slippage – Do you want to model any commission or bid-ask slippage, or treat the strategy as frictionless? Once I have this information I can generate the trading signals and run the 2022-to-present back-test.