Grant: CCI Applied Research and Development Grants
Lambton College of Applied Arts and Technology
$100,000.00
Development of Artificial Intelligence (AI) and Machine Learning (ML) Based Model for Data Analysis and Detection of Suspicious Transaction Activities
EF 2023-24
Résumé
Clear View Systems (CVS) has been developing software solutions for small to medium size financial businesses, including a ‘Transaction monitoring system’ that can detect and monitor transactions that follow a certain pattern and bring them to the attention of a compliance officer (human) for validation and approval. The current Transaction monitoring system has been developed as a ‘Rule-based Engine’ (RBE). The RBE is a powerful and flexible engine that can detect transactions that fall within the criteria defined by a set of rules. It can be programmed to detect specific patterns that must be reported (to the government) such as Large Cash Transactions or Electronic Fund Transfer.
Since every country has its own Anti-Money Laundering (AML) Compliance rules and regulations, each company has its own specific version of the procedures and guidelines. As a result, each company requires a customized version of the rules, and regulations change regularly. Companies have to adhere to the new laws, and the cycle creates a continuous demand for modifying the rules to match the current regulation.
The main goal of the project is to develop an AI/ML-based solution that can be used by financial entities to detect suspicious or reportable transaction patterns of their clients. The project’s focus and scope are for Canadian entities and are based on the regulatory requirements of the Financial Transactions and Reports Analysis Center of Canada (FINTRAC). The AI/ML-based solution will be developed to work in hand with the RBE and will reduce the complexity of having hundreds of rules for each client and trying to maintain the rules with ever-changing AML requirements. The AI/ML tool will not only learn from the RBE but also from the Compliance Officer(s) who manually resolve every case that is raised.
With the successful completion of this project, CVS has the advantage of being recognized in the market as one of the leaders of software and automation systems for small to midsize financial companies. This reputation can help the company market its newer enterprise-level product to its current and future customers. In addition, The Canadian market is in need of robust and trustworthy technology developed in Canada that can 100% adhere to Canadian laws and regulations. This project will lead to regulated Canadian businesses not looking for this technology outside of Canada.
Programme
CCI Applied Research and Development Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
CCARD-2022-00810
Name nom
Sheikhzadeh, Mehdi
Department département
Applied Research and Innovation - Lambton College (Lambton College of Applied Arts and Technology)
Organization id
26621
Institution établissement
Lambton College of Applied Arts and Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2022
Award amount
100000
Program id
CCARD
Program name en
CCI Applied Research and Development Grants
Program name fr
ICC Subventions de recherche et développement appliquée
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
10000
Research subject group en
The field of research available
Research subject group fr
The field of research available
Research subject en
Le domaine de recherche disponible
Research subject fr
Le domaine de recherche disponible
Field of research list codes
RDF5020405
Field of research list names en
Monetary systems and policies
Field of research list names fr
Systèmes et politiques monétaires
Application title
Development of Artificial Intelligence (AI) and Machine Learning (ML) Based Model for Data Analysis and Detection of Suspicious Transaction Activities
Keyword
Anti-Money Laundering; Artificial Intelligence; Information Technology; Rule-Based Engine; Transaction Monitoring System; Software Development; Data Driven Models; Machine Learning; Analytic System; Data Management and Analysis
Application summary
Clear View Systems (CVS) has been developing software solutions for small to medium size financial businesses, including a ‘Transaction monitoring system’ that can detect and monitor transactions that follow a certain pattern and bring them to the attention of a compliance officer (human) for validation and approval. The current Transaction monitoring system has been developed as a ‘Rule-based Engine’ (RBE). The RBE is a powerful and flexible engine that can detect transactions that fall within the criteria defined by a set of rules. It can be programmed to detect specific patterns that must be reported (to the government) such as Large Cash Transactions or Electronic Fund Transfer.
Since every country has its own Anti-Money Laundering (AML) Compliance rules and regulations, each company has its own specific version of the procedures and guidelines. As a result, each company requires a customized version of the rules, and regulations change regularly. Companies have to adhere to the new laws, and the cycle creates a continuous demand for modifying the rules to match the current regulation.
The main goal of the project is to develop an AI/ML-based solution that can be used by financial entities to detect suspicious or reportable transaction patterns of their clients. The project’s focus and scope are for Canadian entities and are based on the regulatory requirements of the Financial Transactions and Reports Analysis Center of Canada (FINTRAC). The AI/ML-based solution will be developed to work in hand with the RBE and will reduce the complexity of having hundreds of rules for each client and trying to maintain the rules with ever-changing AML requirements. The AI/ML tool will not only learn from the RBE but also from the Compliance Officer(s) who manually resolve every case that is raised.
With the successful completion of this project, CVS has the advantage of being recognized in the market as one of the leaders of software and automation systems for small to midsize financial companies. This reputation can help the company market its newer enterprise-level product to its current and future customers. In addition, The Canadian market is in need of robust and trustworthy technology developed in Canada that can 100% adhere to Canadian laws and regulations. This project will lead to regulated Canadian businesses not looking for this technology outside of Canada.