Projects

NSERC/Intact Financial Industrial Research Chair in Machine Learning for Insurance


Intact AssurancesNSERC-CRSNGToday, data analysis is at the heart of several new technologies. Just think of the Google's driverless car, SpaceX's autonomous rocket, intelligent personal assistants like Siri or Alexa, or even Microsoft's HoloLens. These Artificial Intelligence (AI) technologies have one thing in common: they rely on learning algorithms machine. For many applications, the end result is paramount, but some others also require that a human beings can understand how the AI algorithm makes its decisions. In these cases, the information regarding decision-end mechanisms is aimed at build confidence in the syste...

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Big Data Analytics in Insurance


Intact AssurancesNSERC-CRSNGThe big data revolution has begun. A new kind of entrepreneurship is emerging, and businesses are moving away from solely relying on hard-won human experience to rather favor innovative data-driven approaches, which are more accurate, cost effective and robust. Their main motivation is to take advantage of the volume and great variety of newly available data (e.g., social media interactions, web traffic logs, text records, image databases, etc.). Intact Insurance, the industrial partner, is no stranger to the recent advancements in data analytics and foresees the tremendous potential that the ...

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E-Community Health and Toxicity


Two HatMITACSOnline communities abound today, arising on social networking sites, on the websites of real-world communities like schools or clubs, on web discussion forums, on the discussion boards of videogames, and even on the comment pages of news sites and blogs. Some of these communities are “healthy” and foster polite discussion between respectful members, but others are “toxic” and devolve into virulent fights, trolling, cyber-bullying, fraud, or worse even, incitation to suicide, radicalization, or the sexual predation and grooming of minors. Detecting toxic messages and toxic users is a major chal...

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Insurance data mining: algorithms, ethics, and security


La CapitaleNSERC-CRSNGThe Canadian insurance company La Capitale Assurance et Services Financiers has accumulated over time several massive databases of information about their customers in their various insurance programs. They are now looking for a way to exploit this data to gain a better understanding of their customers, in order to customize their insurance coverage to each individual customer's needs. This must be done in the respect of strict ethical norms and within the constraints that the users themselves may impose on how the company can use their data. And, considering the sensitive and personal nature ...

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Machine learning for the insurance industry: predictive models, fraud detection and fairness


SSQNSERC-CRSNGAt the heart of their mission, the insurance industry strive to satisfy their customers and offer them the insurance products that most adequately match their needs. Thanks to a vast amount of corporate data accumulated through the years, to the availability of impressive computational resources, and to the current state of knowledge of machine learning research, insurance companies can now attemps to build effective predictive models about some aspects of client behaviour and their needs. However, insurance companies are also accountable to our society and, in particular, this implies that th...

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NSERC CREATE in Responsible Health and Healthcare Data Science


NSERC-CRSNGThe medical sector generates large amounts of structured and unstructured data on a dailybasis, including 1) health-related data such as medical images, laboratoryresults, questionnaire scores, treatment details and 2) healthcare-related data such as hospital admissions/transfers/discharges, demographics, disease registries, billing accounts, appointments, and schedules. Clinical environments are arguablyamong the sectors producingthe largest quantityof data yet one where their potential remains relativelyuntamed from a Big Data and artificial intelligence perspective. There are several reason...

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