Quantolio Insights: Augmenting the investment management process through AI & ML

The project consists of developing new methodologies to augment the investment management process through AI & ML. To this purpose, the project will be divided in two subprojects :
1) Optimization of error detection and error correction in the data cleansing process.
In every data science project, data scientists and analysts spend a considerable amount of their time cleaning the data they have. The objective is to automate the error detection and error correction processes, with the goal of integrating the models in a user-friendly platform. The end product, Quantolio Data Doctor, will allow users to significantly improve the quality and precision of their data, and speed up the data cleaning process by at least 50%.
2) Development of machine learning algorithms to improve different phases of the investment management process.
The objective of this part is to develop a platform called Quantolio Insights, that will allow portfolio managers to efficiently integrate AI solutions in every phase of the investment management process – allowing them to take better data-driven decisions and improve the performance of their portfolio

Faculty Supervisor:

Frédéric Godin

Student:

Partner:

Quantolio Financial Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Concordia University; HEC Montréal

Program: