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François Friggit, Expert in AI and mathematical finance

 François Friggit is a distinguished expert in artificial intelligence and mathematical finance, with a career spanning over three decades. He has held top executive positions, including the Global Head of Models and Valuation Processes at Banco Santander, the largest bank in the Eurozone at that time. François has a proven track record of managing multinational teams and implementing complex mathematical models in financial markets. His expertise extends to AI, where he has developed and managed advanced models and algorithms, making significant contributions to the field.


François stands out for his ability to bridge the gap between theory and practice. He is not only skilled at understanding and creating complex mathematical models, but also excels in their practical implementation and maintenance.


His extensive experience, coupled with his innovative approach and global perspective, makes him a highly sought-after consultant in the fields of artificial intelligence and mathematical finance.

Education

 M.Sc., Mathematics

Ecole Polytechnique 

(French Ivy League)

Paris 1985

 M.Sc., Hydrology

Ecole Nationale du Génie Rural, des Eaux et des Forêts

Paris 1987

 Master's in international finance

HEC Paris

(best French business School)

Paris 1993

Conferences and presentations

Some institutions where François presented his work include

Fields of Expertise in AI

Market applications

Market data simulation, portfolio simulation, fast pricing, cross-markets influence, market regime detection

Customer and market integration

Recommendation engines, transaction analysis, voice command

Customer behavior analysis

 Sentiment analysis, topic detection, anomaly detection (supervised and unsupervised)

Segmentation and analysis

 Customer and product segmentation

Process Control

 Data quality check, data cleansing, reconciliation, software maintenance & support

Information extraction

 Extraction from legal agreements and contracts, in different languages

Advanced AI models and techniques

  •  NLP (Speech recognition, advanced OCR, sentiment analysis)
  • Knowledge graphs, Graph Neural Network
  • Clustering/classification
  • Random Forest, Gradient Boosting
  • Convolutional Neural Networks
  • Auto-Encoders, GANs
  • Active Learning, semi-supervised learning
  • Collaborative Filtering (including Deep Learning)

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