Machine Learning Assisted Risk Management And Responsible Conduct Of Gambling

Abstract

Managing risk in a proactive manner is the most important factor that contributes to the longterm success of a bookmaker as well as their patrons (punter). Traditionally, risk management is done by skilled traders. But the amount of data and information that traders can access at any given time is limited. Machine learning assisted risk management (MLARM) module that has been developed in this research can classify and identifying gambling patters of different punters with an accuracy over 92%. It makes use of two artificial neural networks that are developed specifically to handle two types of data. One being betting data and the other being notes and comment from traders. MLARM will be a helping hand for traders in risk management while supporting punters combat gambling addiction.