NEOBANKS
relevant and timely engagement via the optimal channel .
“ As well as allowing neobanks to address current customer needs , the insight gained through AI and ML will help identify emerging customer needs and enable banks to drive proactive engagement with customers .
“ For example , in the area of collections , understanding customer behaviour and changes in their circumstances can help identify those that are potentially moving towards a stressed financial situation .
“ By picking up on potential indicators , banks can engage with the customer and help before that situation becomes a collection or recovery engagement . This is better for the customer and the bank or financial organisation .
“ Whether banks can successfully use AI and ML to hit these ambitious growth targets depends on several factors beyond just investment in software – for example , correctly prioritising which areas of the business to target first , and making sure they have sufficient in-house skills to fully exploit the technology .”
Retaining pulling power Leveraging technology for use in real-time , then , is a future that neobanks should continue working towards – engaging with customers when necessary and taking preemptive action to protect both their own and their clients ’ interests .
They can go even further , too , according to Grinbaum , staying ahead of the curve by understanding the financial end goal of every customer they serve .
He says : “ Take the example of someone using a product to pay off student loans . While the transactional component of making payments and saving money is important , the way to go above and beyond is to ask the question , ‘ why does a particular person want to pay off their student loans ?’. Maybe to buy a house , start a family or open a savings account for their kids .
“ Challengers need to view their product from the user ’ s perspective : start with a financial goal and then build an exceptional product experience to support that .
68 February 2024