There is a need for experiential banking and hyper personalisation emerging as essential tools for the journey back to profitability, institutions should be better equipped to provide clients holistic engagement to tackle the new frontier of fraud with the help of machine learning. Financial criminals have become increasingly sophisticated when it comes to exploiting vulnerable consumers. A report says, there are fraudulent stimulus payments that are spurring major banks to shut down legitimate bank accounts due to suspected unemployment fraud. Furthermore, bad actors are deploying tactics such as call centre scams, account takeovers and micro deposit fraud to extract funds from both crypto and traditional currencies.



Financial service providers are responsible for protecting customers from large-scale fraud attacks. Unfortunately, not all have demonstrated the ability to operate on the same level of sophistication as the agile fraudsters, ultimately putting their brand reputation and penalties on the line. Banks are also competing with new players in financial services that are tech-forward, exhibit high growth potential and offer sophisticated, tailor-made products and services. Hence, traditional banks must keep pace, by leveraging advanced technology powered by machine learning, to accurately identify customer behavioural trends, preventing fraud or criminal activity at the outset. The advantage with Machine learning platforms is able to analyse tens of thousands of complex signals. Financial service providers can then utilise behavioural pattern recognition to effectively understand and enforce on malicious activity, rather than relying on antiquated threshold rules that bad actors eventually learn to circumvent.


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