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Grant: CCI Applied Research and Development Grants

Collège de Bois-de-Boulogne

$150,000.00

Development of a data-driven engine for the private investment sector

EF 2023-24

Résumé
The enthusiasm for entrepreneurship has significantly increased in recent years in the high technology sector. As a result, the many innovative projects that are in the early stages of their life cycle sometimes need refinement both in terms of the value proposition they suggest and the structure of the company that supports them. It is in this perspective that private investment firms and accelerators like Holt play a critical role. They support start-up companies in defining their business model, tracing the technological roadmap and designing a marketing plan. However, given the premature nature of their intervention and the high level of risk of the investment, better control over the entire investment decision process is required: from the discovery of startups with high potential to the allocation of funds to these companies. Briefly, what the project aims to achieve is the development of a solution for venture capital firms, VC as a Service (or VCaaS), that would significantly improve the investment decision process of its users through a data-driven approach. This involves, among other things, establishing a portrait of companies by identifying all the factors that could have an impact on the quality of the investment. One of the important factors in this process is the quality and objectivity with which a startup's potential is assessed within its technological and economic context. This requires specialized experience and skills in the field of expertise of the company. Indeed, this assessment is carried out by investment experts (referred to as advisors), selected from a pool of collaborators with diverse profiles. The right match between a startup and advisor is therefore crucial for the success of an investment portfolio. Optimizing this process through data science requires the use of advanced artificial intelligence techniques in the fields of information retrieval systems, recommendation systems, natural language processing, supervised learning, as well as reinforcement learning.
Programme
CCI Applied Research and Development Grants
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
CCARD-2022-00246
Application summary
The enthusiasm for entrepreneurship has significantly increased in recent years in the high technology sector. As a result, the many innovative projects that are in the early stages of their life cycle sometimes need refinement both in terms of the value proposition they suggest and the structure of the company that supports them. It is in this perspective that private investment firms and accelerators like Holt play a critical role. They support start-up companies in defining their business model, tracing the technological roadmap and designing a marketing plan. However, given the premature nature of their intervention and the high level of risk of the investment, better control over the entire investment decision process is required: from the discovery of startups with high potential to the allocation of funds to these companies. Briefly, what the project aims to achieve is the development of a solution for venture capital firms, VC as a Service (or VCaaS), that would significantly improve the investment decision process of its users through a data-driven approach. This involves, among other things, establishing a portrait of companies by identifying all the factors that could have an impact on the quality of the investment. One of the important factors in this process is the quality and objectivity with which a startup's potential is assessed within its technological and economic context. This requires specialized experience and skills in the field of expertise of the company. Indeed, this assessment is carried out by investment experts (referred to as advisors), selected from a pool of collaborators with diverse profiles. The right match between a startup and advisor is therefore crucial for the success of an investment portfolio. Optimizing this process through data science requires the use of advanced artificial intelligence techniques in the fields of information retrieval systems, recommendation systems, natural language processing, supervised learning, as well as reinforcement learning.
Application title
Development of a data-driven engine for the private investment sector
Area of application code
10000
Area of application en
The socioeconomic objective available
Area of application fr
L'objectif socioéconomique disponible
Area of application group en
The socioeconomic objective available
Area of application group fr
L'objectif socioéconomique disponible
Award amount
150000
Competition year année de concours
2022
Country en
CANADA
Country fr
CANADA
Department département
Head Office
Field of research list codes
RDF1020104
Field of research list names en
Machine learning
Field of research list names fr
Apprentissage machine
Fiscal year exercice financier
2023
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Institution établissement
Collège de Bois-de-Boulogne
Keyword
human-in-the-loop; natural language processing; recommender systems; machine learning; Representation learning
Name nom
Malette, Marie-Ève
Organization id
2437
Program id
CCARD
Program name en
CCI Applied Research and Development Grants
Program name fr
ICC Subventions de recherche et développement appliquée
Province en
Québec
Province fr
Québec
Research subject code
10000
Research subject en
Le domaine de recherche disponible
Research subject fr
Le domaine de recherche disponible
Research subject group en
The field of research available
Research subject group fr
The field of research available
Socioeconomic objective list codes
RDS11101
Socioeconomic objective list names en
Finance and economics
Socioeconomic objective list names fr
Finance et économie