Dr David R.Hardoon, Senior Advisor for Data and Artificial Intelligence from Unionbank Philippines, Eric Wan, Financial Crime Compliance from Moxbank, Patricia Sanz, Head of Financial Crime Investigation from HSBC Singapore, and Dev Dhiman, Managing Director APAC from GBG discuss and unbox the decision behind financial institutions harnessing AI and advanced data intelligence today.
The types of financial crime impacting financial institutions (FIs) have changed with the pandemic. Social- and cyber- engineered first party fraud are on the rise and FIs see that money muling is the top four fastest growing fraud typology in APAC 2020/21.
Two key challenges in combatting hybrid first party fraud effectively:
The ability to automate proactive learning and adaptation in fraud detection in order to discover new behavioral patterns and missed fraud.
Drill down, validate and identify anomalies on submitted identity information, by accessing data intelligence such as endpoint security, identity association, device fingerprinting, email validation, geolocation, alternative credit scoring, and phone assessment.
The recent GBG and Risk.net survey finds that 36% of FIs in APAC are exploring to invest in machine learning to enrich their fraud prevention solution, in order to help their organization stay at the forefront of technology.
What types of data intelligence are prioritised by FIs today
How data is applied to create actionable insights and intelligence for fraud prevention
How adaptive and explainable machine learning model have helped FIs adopt AI