How to Automate Risk Decisioning: Getting Real with Artificial Intelligence

Risk decisions come in different shapes and forms: from credit decisioning utilising real-time risk assessments of loan applications, acting on early warning triggers, to effectively managing portfolios in times of uncertainty. In an era of digital technologies and open banking, organisations are relying more and more on automation, artificial intelligence and machine learning for consistent and contextual decision making in Risk Management. At the same time, with the use of artificial intelligence, machine learning and automation in risk decisions, the impacts of wrong decision making are exacerbated. Organisations are rightly concerned about the explain-ability of the decisions and the risk of amplifying bias. Join our risk modeling and decisioning experts, Dr. Terisa Roberts and Yi Jian Ching, as they lead a topical discussion on incorporating artificial intelligence and machine learning in risk decisioning, including global industry practices and real world examples. Learn how financial institutions can... - Leverage more data and the transformational power of machine learning to improve efficiency. - Cut costs and increase profitability in risk decision-making.