AI Analysts for Financial Services: Accurate, Auditable, and Built on Shared Context
Date: Wednesday, July 22 at 11am PT / 2pm ET
Across financial services, the same gap keeps showing up in audits and consent orders: your analysts know what changed in the data, but they cannot find out why fast enough. Fraud alerts pile up in queues while investigators pull data source by source. Regulatory submissions get validated with Excel pivots and manual escalation chains. Generic AI tools promise to help, then fail where it matters most: accuracy, auditability, and consistency.
In this session, Sandip Devarkonda, Director on PromptQL's AI Catalyst Team, shows how leading financial institutions are deploying multiplayer AI that the whole team can teach and trust. You will see AI-assisted fraud investigation and regulatory variance analysis in action, and learn how a shared context layer, a Wikipedia-style operational wiki that builds itself as your team works, delivers deterministic, fully traceable answers while your data never leaves your environment.
Attendees will learn:
- Why 95% of enterprise AI initiatives fail, and what the 5% do differently
- How AI can auto-answer the fraud investigative checklist across all sources in seconds
- How plain-English variance analysis eliminates Excel pivots and escalation chains in regulatory reporting
- How shared context compounds: teach it once, and everyone on the team gets the skill
Register now!
About the presenter:
Sandip Devarkonda, Director, AI Catalyst Team, PromptQL (by Hasura)
Sandip Devarkonda is a Director on the AI Catalyst Team at PromptQL (by Hasura), where he leads forward-deployed engineering for the company's largest financial services and enterprise customers, including one of the biggest banks in the US. He works hands-on with fraud, risk, and finance data teams to take AI from pilot to production in highly regulated environments.