Counterparty risk as a conversation
Your XVA engine is sophisticated. So why can’t your traders ask it a simple question?
Most institutions run powerful counterparty risk models, yet traders, portfolio managers and senior risk officers still rely on stale dashboards or wait for an overstretched quant.
In this paper, LSEG’s Scott Sobolewski argues that the real weakness is the last mile, and shows how artificial intelligence can close that gap between models and decision-makers without compromising model governance.
What you’ll learn:
- Why the interface, not the calculation, is now the weak link
- How AI can call on trusted, open-source risk models instead of guessing the numbers itself
- Practical first use cases, from pre-trade incremental credit valuation adjustment (CVA) to potential future exposure analysis
The paper is instructive for XVA and CVA desk heads, counterparty risk managers, model risk teams and front-office traders.
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