Artificial intelligence, particularly generative AI, is redefining the aggressive fintech landscape. The McKinsey Global Institute recently predicted that generative AI could add an additional $200 billion to $340 billion in annual value to the banking industry, representing a potential 9 to 15 percent increase in operating profits.
As industry players up their game, Visa is betting big on AIlaunching more than 500 generative AI applications to drive innovation and increased productivity at scale.
The vision for AI integration is not just about reducing costs; it’s about redefining workflows. Visa has invested $3.3 billion in AI and data infrastructure over the past decade, and recently dedicated $100 million to generative AI startups. The company’s AI-based credit approval systems even fill service gaps for banks in the event of network disruptions.
Credit: McKinsey Global Institute
AI + humans are the future
Visa’s approach to AI is less about reducing headcount and more about improving human oversight. “My vision is for Visa to have AI-generated digital employees, supervised by human workers. Any given human employee can supervise, on average, eight to ten AI employees who are assigned various tasks. said Rajat Taneja, President of Technology at Visa.
Meanwhile, other tech leaders also appear to echo this belief. “I think there is potential to automate a high percentage of jobs, but I also think there is great potential to bring much more efficiency to jobs,” said Deb Lindway, vice-president. executive president and head of AI at PNC, in a statement. interview.
BYOT (bring your own tools)
According to McKinseyGenAI carries many risks, such as misinformation, intellectual property issues, transparency gaps, bias, and security concerns. Sustainable value requires going beyond initial trials and addressing these challenges. This is why AI in most fintech companies is still largely in-house and not consumer-facing.
“We don’t have customer-facing use cases. At the moment, all of these cases are internal and there is a natural sequence. There have been interesting stories of companies putting generators and chatbots up and running, and then specified pricing terms resulting in lawsuits. The established legal precedent is very clear: a customer channel is an extension of the business, and they are responsible for what an AI system generates. Therefore, we want to be very careful before using them. » said Derek Waldron, director of analytics at JPMorgan Chase.
Not wanting to play the waiting game, much fintech employees bring their own tools to workeven if their companies haven’t officially rolled them out yet. However, caution must be exercised here.
“There is certainly a demand for companies to develop policies and find ways to use these tools, because when people use them maliciously, it can create problems and inequities,” said Business Insider senior correspondent Amanda Hoover on the need for companies to formally adopt these tools internally to ensure consistency.
Use cases of GenAI in banks
Earlier this year, JP Morgan launched Quest IndexGPT, using GPT-4 to improve thematic index construction for institutional investors, and introduced LLM Suite, an AI assistant for 60,000 Chase employees to facilitate tasks such as writing emails. Class First of all in the Evident AI Index 2024, the New York-headquartered financial services company is a leader in AI adoption in finance.
Not wanting to be left behind, Morgan Stanley launched AI debriefing at Morgan Stanley around the same time in an effort to increase advisor productivity. He also launched AI @ Morgan Stanley Assistant, adopted by 98% of advisor teams. Jeff McMillan, head of analytics, data and innovation at Morgan Stanley Wealth Management and Firmwide AI, describes AI as a window of opportunity. “I’ve never seen anything like this in my career and I’ve been doing artificial intelligence for 20 years,” he said. said.
Meanwhile, Visa rival Mastercard has introduced new AI technology that improves payment security by detecting compromised cards twice as quickly and reducing incorrect fraud alerts by 200%. It also identifies at-risk merchants 300% faster, helping to detect complex fraud schemes and protect future transactions.
This upgrade strengthens Mastercard’s Cyber Secure program, giving banks and merchants better tools to protect customer data. With faster, more accurate alerts, banks can act quickly to prevent fraud, block compromised cards and build trust in the payments system.
However, some areas of finance will likely remain AI-proof for a long time to come. “Customer relationships will always be of great value and will be irreplaceable. I think finance will always have a very important element of human trust and relationships will be very important. said Derek Waldron, chief analytics officer at JPMorgan Chase, discussed which areas of the financial sector will win out of AI disruption, but he cautioned that this gap is constantly narrowing.
GenAI Push in India
In India, AI applications are also transforming banking operations. HDFC Bank, for example, has adopted an AI-based approach to fraud detection, which has proven essential as fraudsters continue to adapt to traditional rules-based systems. In 2017, the bank launched Eva, India’s first AI-powered banking chatbot, which instantly handles millions of queries and sets a new standard in customer service.
In 2020, ICICI Bank introduced iPal, enabling transactions via voice commands through Alexa and Google Assistant, but discontinued it in 2021. In 2023, SBI announced an AI initiative aimed at improving decision-making and marketing. operational efficiency, planning advanced data systems and fintech partnerships to improve co-lending.