BANKS in the Asia-Pacific (APAC) region are struggling to maximize the benefits of artificial intelligence (AI) technologies amid rapid digitalization and the lack of expertise and appropriate infrastructure, Accenture said.
Majority of global banking executives feel they are not prepared to keep up with technological developments, Accenture APAC Financial Services Senior Managing Director and Lead Masashi Nakano said in a webinar on Tuesday.
“According to our latest CXO (chief experience officer) survey, over 90% of global banking executives feel that the pace of change has accelerated over the past six months, and they expect it to accelerate even further in the next six months. However, only 40% feel prepared for this change,” he said.
Accenture Managing Director and APAC Banking and Capital Markets Lead Nicole Bodack said only 10% of surveyed companies have identified specific use cases for AI technologies.
“The 10% leading in AI adoption have validated specific AI use cases. And most importantly, they have scaled their strategic bets that are most relevant to the industry,” she said.
Accenture APAC Data and AI Senior Managing Director and Lead Vivek Luthra added that 70% of the global banks they surveyed believe that AI is “moving faster than their ability to prepare the workforce.”
This means banks should work on accelerating building AI expertise in the workforce and also redesigning future jobs as AI adoption grows, he said.
Accenture APAC Banking Managing Director Navin Suri said banks also need to rebuild their core infrastructure as legacy systems will not be able to handle emerging AI use cases.
“This old infrastructure is really struggling to keep pace with the demands of modern banking, especially things like artificial intelligence. Hence, the number one requirement for banks today, AI in fact, is to look at modernizing their legacy core systems.”
Banks can either completely rebuild their infrastructure or create subsidiaries where they can build new core systems, he said, but added these efforts could be costly and take a long time to implement.
“It can take anywhere between five to eight years to migrate out of your 20- to 40-year-old system to a new-age system. It can cost hundreds of millions of dollars and it will still be quite risky.”
Mr. Suri said he is seeing rising industry interest in “incremental migration,” which refers to a slower, more phased approach in building new systems.
“This allows you to operate the old and new alongside each other, making it much simpler for you to offer these new services.”
Nevertheless, banks are “more people-centric and have implemented change management and learning and development at all levels of the organization,” Ms. Bodack said.
“They’ve moved beyond demonstrating intent to truly operationalizing responsible AI practices,” she added. “The banking industry has always been at the forefront of technology adoption, and… banks are considering their AI investment seriously and see it as a key value driver.”
Mr. Nakano said banks are currently using AI to address customer needs, compete against new business models and rapid innovations, and for risk and compliance.
Mr. Luthra added that banks looking to expand their AI use cases should look at “leading with value” or focusing on how they can leverage AI technologies to drive growth in both clients and talent.
“We see banks being able to drive about 30% efficiency based on the research which we conducted. [This is] close to about 600 basis points increase in revenue,” he said.
Lenders can also use AI in risk and fraud management, as well as investment management and advisory through AI agents, he added.
“We see 57% of the banks globally are piloting or actively deploying AI agents across their functions.” — Aaron Michael C. Sy
