As banking becomes more increasingly online, and with the data touchpoints on the rise, AI and ML have become an integral part of a bank’s DNA. It is a natural outcome that the more the data touchpoints, and the wider the data exposure, the greater the chances of things going wrong. Understanding this vulnerability, banks and financial institutions are keen on deploying AI/ML to keep a check on fraud incidents.
To get a better insight into how banks are adopting and adapting new technology and what is the future looking like for them, OpenGov Asia had a conversation with Dr David Hardoon, Senior Advisor for Data and Artificial Intelligence, Union Bank of Philippines.
David acknowledged that the rise in digital data points, as a result of increased online banking, has necessitated leveraging technologies like AI and ML to derive actionable insights. Additionally, more financial institutions see the benefits of adopting technology to keep fraud in check. The headway in security has encouraged them to scale it to other core functions like floor management, compliance, and regulation.
This is an almost-radical departure as historically there has been a reluctance in adopting technology among financial institutions due to unfamiliarity and the stern regulations around it. The pandemic has driven this paradigm shift, forcing organizations to think beyond their existing boundaries and comfort zones.
David noted that even the support office is catching up with the front office in terms of robustness, scalability, and capability to know when something is wrong. This is driven by the need to ensure a smooth and secure online experience for the customer.
On being asked about the notion that online malls and shopping sites are leading the way in customer experience and engagement over online banks and financial institutions, David agreed the banking industry is lagging but highlighted an important issue. The pandemic has driven people online but there is a fundamental lack of trust among customers engaging with such e-commerce sites.
“Trust is an equity financial institutions have, he opined. But it needs to be leveraged appropriately to build customer engagement online.”
Speaking about fraud and risk management in financial institutions in the post-COVID-19 era David shared that there has been a tremendous increase in the adoption of technology among banks. The strategy has been to use existing systems and adopt/adapt more sophisticated data techniques to achieve operational efficiency.
Banks are also focusing on taking the marketing mantra of hyper-personalization to compliance. David shared that data is the tool that equips banks with the ability and capacity of seeing and engaging individuals as individuals. Adding to this, he believes that such technologies can only be deployed in an institution when the top management believes in its power.
Elaborating on the future of AI/ML in fraud, David believes that the conversation is going to shift from digitizing the front office to bringing in the latest technology in the middle and back office in financial institutions. Apart from focusing on driving top-line growth, companies will need to get a better handle to know if anything wrong or irregular is happening.
David is confident that discussions around using AI/ML to manage fraud and risk will convert into action. The implementation might not be uniform across all institutions, but will it will move forward. Bigger institutions who have focused teams and resources will look to develop in-house fraud and risk management systems initially. A major reason behind it is the need to understand the complexities and difficulties associated with this process. Once they have familiarized themselves with it, they might partner with experts who champion the field.
All in all, David is an optimist who believes in the power of AI/ML, in risk and fraud management, and believes that conversations around it will get more operational.