Nowadays, more and more consumers choose to make the mobile phone their primary method of managing their banking transactions. With the onset of mobile banking, convenience and accessibility has gradually given way to fraudsters, by providing them with excellent opportunities to hijack bank accounts.
Internal fraud can take place at any level of organization. Fraud costs $3.7 trillion each year and nearly 75 % of the banking fraud is internal (ACFE, 2016). Even if a bank successfully wards of attackers, there is always the risk of insiders abusing the precious information they hold.
Machine learning and artificial intelligence (AI) create $1 trillion of change in the financial services industry. Likewise, the impact of machine learning and AI on fraud detection and prevention is tremendous.
Cyber fraud is projected to reach $6 trillion by 2021. While adoption of new technologies has created new channels to give customers a unique anytime anywhere banking convenience, the systems that banks depend on to deliver their services have multiplied and grown much more complex.
Increasing regulatory pressures regarding the efficiency of AML environment and the increasing fines present new challenges for financial institutions. Only in the beginning of 2018, banks were fined up to 70 million USD.