Most AI initiatives in capital markets fail because they bolt intelligence onto broken processes and disconnected data.
The Alphient approach is different. With Prime (pro-code) and Prime (low-code), we start with three pillars:
Structured Knowledge
- Client activity and revenue attribution across the desk
- Trade pattern recognition across all asset classes
- Market context assembled automatically per decision
Automated Process Packs
- Execution quality linked to client retention over time
- Lifecycle orchestration with parallel processing
Intelligent AI Agents
- Routine matching and breaks resolved automatically
- Market scanning and pattern detection running continuously
- Product setup adapting to new instruments instantly
The business questions this unlocks:
- Revenue Streams
- Cost Per Trade
- Revenue Per Desk
- T+1 & Speed
- AI Across the Desk
AI agents for revenue streams, cost per trade, desk productivity, and trade surveillance.
Knowledge. Process. Agents. That is the transformation formula.