Financial sector
Financial services
The financial sector is undergoing a radical transformation driven by digitalization and demand for more personalized and efficient services. QUANT AI Lab helps financial institutions innovate through: predictive analysis, process automation & customer experience.
Risk Management
Comprehensive balance sheet and liquidity risk management solution, enabling the analysis, management, monitoring and control of risk exposure.
Portfolio Optimization
Solution dedicated to portfolio optimization combining different models from financial mathematics (Black-Litterman, etc.) and AI (DL, DRL, etc.)
Fraud and compliance
Our product combinations and accelerators allow us to cover topics such as anti-money laundering, corruption, fraud prevention, KYC, and more.
Quantitative analysis
Solution specialized in advanced data analysis, using statistical and mathematical models.
View use cases
Flood Risk Assessment
Our ESG physical model for flood impact assessment determines flood-prone areas by municipality in France, classifying floods into three severity levels
ESG CSRD
Our mission involved building an ESG reputation score for their investment portfolio, based on our existing solution, integrating both media/public perception and sustainability reports.
Propensity Models and Creation of Sustainable Data Repositories
The main objective of the sustainability project is to implement an advanced data-driven analysis system that enables the banking entity to optimize energy efficiency and promote sustainable mobility within its customer base.
Futura App
Futura aims to evolve from a fundamentally transactional relationship model to a more relational model in order to improve the look and feel and, altogether, de clients’ experience while using the app.
Development and industrialization of the PyPF
The AI Products team of a leading player in the banking sector aims to strengthen its Data Science development capabilities to accelerate the production deployment of its AI products in alignment with its roadmap.
Drawdown management in portfolios
The use case focuses on managing drawdown risk in factor-based investment portfolios.
LLM Chatbot
For one of the most important clients in the Spanish banking sector, QUANT AI Lab, as part of the client’s Cognitive Architecture team, has released a Conversational Assistants service with LLMs.
RAG x Chatbot
Our client is a major player in the Savings sector in France and international. They process a lot of contracts, term sheets, and brochures for various clients.
Interdependencies & conditional probabilities
The “Causal ML” mission at a leading player in the financial sector aims to analyze the interdependencies between risks databases to establish causal chains and clusters.
Transition climate risk – Dynamic rating
The model assigns a dynamic rating to homes in France for the period 2024-2050, based on their Energy Performance Certificate (DPE) and current energy scenarios (including heating).
Unsupervised fraud detection
Financial institutions often face an overwhelming number of cases that require manual review to determine potential fraudulent activity.
Factor investing & ML
The use case focuses on managing drawdown risk in factor-based investment portfolios.
Data Office for a data-Centric transformation
As part of a major transformation program towards a « Data-Centric » model, a Data Office was developed and deployed for a leading player in the insurance sector to effectively address business challenges.
Destination recommender system
In the airline industry, personalized customer engagement is crucial for boosting bookings and enhancing satisfaction. The effectiveness of these recommendations hinges on the precision of integrating and analyzing extensive user data.
