Subventions et des contributions :

Titre :
Collection software artificial intelligence: analysis, determination of scope and initial implementation
Numéro de l’entente :
EGP
Valeur d'entente :
25 000,00 $
Date d'entente :
7 mars 2018 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Colombie-Britannique, Autre, CA
Numéro de référence :
GC-2017-Q4-01055
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Nom légal du bénéficiaire :
Li, Kin (University of Victoria)
Programme :
Subventions d'engagement partenarial pour les universités
But du programme :

Consumer spending has been in an upward trend worldwide. Increase in spending often results in accumulatingx000D
debts. Most companies hand over debt collection to agencies. A number of anonymized data sets containingx000D
debt and repayment information used by collection agencies are available through a company that developsx000D
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 asx000D
phone number area code, address information including zip or postal codes, financial history of debits andx000D
credits with dates and amounts, an event history recording whether phone calls, letters, SMS or other contactx000D
events have occurred, and even promises to pay are recorded. There is typically a correlation between a contactx000D
event and subsequent payments.x000D
The main objective of this project is to determine which contact events that trigger appropriate actions willx000D
lead to optimal recovery. Based on the analysis of these events and other key indicators, it is anticipated that ax000D
simple proof-of-concept model for decision making can be developed.