New โคAI Architecture Aims โto Revolutionize Financial Modeling
NEW YORK – November 18, 2025 – A novel approach to artificial intelligenceโ in finance,โฃ dubbed a “finance-native” neural network architecture, is challenging conventional wisdom about applying AI to dynamic markets. Developed by researcher Iabichino,โฃ the system prioritizesโ incorporating established โคfinancial principles directly into the AI’s structure, rather than attempting to force financial models to conform to the logic โof existing AI frameworks. This โcould โlead to moreโฃ accurate pricing, improved risk management, and enhanced trading strategies for banks and investment firms.
The core innovation lies in a neural network designโ that connects neurons directly, rather than relyingโ on traditional layer-by-layerโ connections, thereby constraining potential outputs to align with financial constraints. Iabichino argues that current AI applications in finance,such as โdeep hedging and โคmodels like Volga,are fundamentally flawed because they attempt โฃtoโ adapt AI designed for static problems – like image โor text recognition – to the inherently dynamic nature of financial markets. “They try to bend finance to obey the logic of AI,” he stated.
Thisโ newโ architecture offers potential applications acrossโ various financial functions, including โquantitative Investment Strategies (QIS), derivatives valuation adjustments (XVAs),โ and investment โportfolio management. In โthe buy-side context, the system can incorporate investor views as constraints, comparing them โฃwith market-impliedโ prices to generate trading signals, even where the no-arbitrage condition doesn’t โapply.
The podcast details how the network’s interpretability is aโ key feature, allowing for a better understandingโ of โthe reasoning โขbehind its โคoutputs. Iabichino’s research also extends toโข XVA modeling, aiming to improve the accuracy and efficiency of these crucial โคcalculations. Theโ idea originated โขfrom a desire โคto build โฃan AI โthat inherently understands and respects the underlying principles of finance.
Podcast Index:
* 00:00 introduction: what’s a finance-native AIโฃ architecture?
* 02:58 How to incorporate financial constraints into a โฃneuralโฃ network
* 08:22 Differences with other AI-based approaches
* 13:36 โคInterpretability
* 14:53 Uses for QIS,pricing and investment purposes
* 23:48 Theโค genesis of the idea
* 24:55 Iabichino’s research on XVA
Listeners can access the fullโ interview onโข Risk.net, Soundcloudโ (https://soundcloud.com/user-393208363/tracks), Spotify (https://open.spotify.com/show/2fKrhTrkJP0tdiT7RWkK8o),Amazon Music (https://music.amazon.com/podcasts/19067a46-6bb5-41bf-b7c8-9cd11d996af3/quantcast-%E2%80%93-a-risk-net-cutting-edge-podcast), or iTunes (https://podcasts.apple.com/gb/podcast/quantcast-a-risk-net-cutting-edge-podcast/id1340909285).Future podcasts in the Quantcast series will be uploaded โขto Risk.net.
