BRD
“ AI is being introduced on a small scale , meaning we have a very consistent path ahead , which is the way to go with AI ,” explains Mikic . “ We first of all started by introducing some RPAs for tasks that were the least provoking or stimulating – basically , we eliminated the boring stuff , if you want . “ Then afterwards , we started using the data analytics that was accessible from the banking experience , and machine learning in order to eliminate potential threats and boost the good clients ahead in a seamless experience .”
Over the years and under Mikic ’ s leadership , BRD has utilised customer profiles to predict client behaviour , as well as monitor those who express dissatisfaction or desire to leave the bank , referred to in the industry as a churn model . This allows BRD to work towards fulfilling its overall vision of ‘ operating as a customer-centric , universal model ’, by offering the highest level of customer service , while simultaneously complementing the company ’ s digital banking efforts .
Safeguarding businesses in a digital world The advancement of AI has brought with it a wide array of advantages to a number of industries . Over the past decade , the significant rise in the increase of AI adoption and machine learning ( ML ), has empowered organisations to successfully leverage these technologies , integrating them into their business practices . However , as with any new technology , there are associated risks that come with the territory .
“ Entire risk management is crucial ,” Mikic explains . “ At BRD we don ’ t just do it occasionally or once a problem arises , we do it consistently . There are a lot of ill intentions in the market , a lot of trustabusing phishing attacks and there is no bulletproof system , we know that .
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