Reference number : GC-2017-Q4-01055, amendment number : , agreement type : G, recipient legal name : Li, Kin (University of Victoria), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Consumer spending has been in an upward trend worldwide. Increase in spending often results in accumulating_x000D_
debts. Most companies hand over debt collection to agencies. A number of anonymized data sets containing_x000D_
debt and repayment information used by collection agencies are available through a company that develops_x000D_
debt management and collection software. These data sets contain demographic information on individuals,_x000D_
financial and repayment history on individual debts, communication event, and other information such as_x000D_
phone number area code, address information including zip or postal codes, financial history of debits and_x000D_
credits with dates and amounts, an event history recording whether phone calls, letters, SMS or other contact_x000D_
events have occurred, and even promises to pay are recorded. There is typically a correlation between a contact_x000D_
event and subsequent payments._x000D_
The main objective of this project is to determine which contact events that trigger appropriate actions will_x000D_
lead to optimal recovery. Based on the analysis of these events and other key indicators, it is anticipated that a_x000D_
simple proof-of-concept model for decision making can be developed., program purpose french : Consumer spending has been in an upward trend worldwide. Increase in spending often results in accumulating_x000D_
debts. Most companies hand over debt collection to agencies. A number of anonymized data sets containing_x000D_
debt and repayment information used by collection agencies are available through a company that develops_x000D_
debt management and collection software. These data sets contain demographic information on individuals,_x000D_
financial and repayment history on individual debts, communication event, and other information such as_x000D_
phone number area code, address information including zip or postal codes, financial history of debits and_x000D_
credits with dates and amounts, an event history recording whether phone calls, letters, SMS or other contact_x000D_
events have occurred, and even promises to pay are recorded. There is typically a correlation between a contact_x000D_
event and subsequent payments._x000D_
The main objective of this project is to determine which contact events that trigger appropriate actions will_x000D_
lead to optimal recovery. Based on the analysis of these events and other key indicators, it is anticipated that a_x000D_
simple proof-of-concept model for decision making can be developed., agreement title english : Collection software artificial intelligence: analysis, determination of scope and initial implementation, agreement title french : Collection software artificial intelligence: analysis, determination of scope and initial implementation, agreement number : EGP, agreement value : 25000.0, agreement start date : 2018-03-07, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada