Finance is a vital yet daunting aspect of our lives, often alienating people due to its intricate language and formidable entry barriers, despite its significance.
Imagine having a knowledgeable consultant offering personalized advice and simplifying complex financial terms when contemplating financial products. Picture receiving a preliminary assessment before investing, all available at any time and place, and without the usual high costs associated with professional services.
This prospect isn’t some distant future—it’s closer than one might think, thanks to the rapid integration of artificial intelligence (AI) into finance.
In banking, the focus is on deploying advanced AI bankers capable of supporting or potentially replacing human workers. These AI bankers promise continuous assistance, significantly enhancing banking efficiency.
For instance, KB Kookmin Bank led the way in 2022 by introducing AI assistants in various branches to aid customers with document handling and offer insights on financial products. The bank is currently beta testing to extend the assistant, initially available as a kiosk, to its mobile platform.
Woori Bank also disclosed plans on Nov. 8 to fully develop an AI banker system, expected to launch by the first quarter of 2024, accessible via the bank’s mobile app.
An official at Woori Bank stated, “The service aims to understand inquiries and deliver fitting responses, aspiring to match in-person branch consultations, even through remote channels.”
AI is also revolutionizing insurance claims processing. Samsung Life Insurance collaborated with local AI startup Upstage, significantly automating the claims process. Upstage’s AI handles submitted documents, extracts relevant data, and assists in providing insurance funds, particularly useful during periods of frequent claims.
Investments are witnessing a surge in AI presence too. Shinhan AI, a subsidiary of Shinhan Financial Group, plans to launch an advanced chatbot service by year-end, offering stock market advice surpassing previous models with more comprehensive responses based on historical and current financial data.
Park Dae-woo, head of Solution Chapter at Shinhan AI, highlighted its ability to address customer queries about domestic stocks and economic issues, bridging information gaps among financial consumers.
According to Korea Credit Information Services (KCIS), the finance industry holds the largest share (19%) of the AI market, with its valuation skyrocketing from 300 billion won ($229 million) in 2019 to 600 billion won in 2021. Forecasts predict a valuation of 3.2 trillion won by 2026, with an annual growth rate of 38.2%.
Oh Soon-young, a managing director at KB’s Financial AI Center, emphasized how generative AI is pivotal for the industry’s advancement, enhancing efficiency through automation.
KCIS outlines four primary uses of AI in finance: revenue generation through data analysis, improved customer experiences via tailored services, cost efficiency through automation, and ensuring compliance with stringent financial regulations using AI-powered systems.
However, despite its potential, market watchers caution that integrating AI into financial services is still in its infancy.
Oh notes, “We’re at an early stage of utilizing generative AI. For now, AI must assist humans. Entering banking fully requires addressing compliance and securing sensitive customer data, which will take time.”
This cautious approach stems from unresolved issues with generative AI in finance, such as ensuring consistent accuracy and avoiding biases inherent in outputs, particularly critical in finance where credibility matters significantly.
Notably, the Apple Card incident in 2019 highlighted concerns about gender bias in credit limits, sparking discussions on societal implications of AI models.
Gary Gensler, chair of the U.S. Securities and Exchange Commission, warns of a potential financial crisis within a decade without prompt regulatory action to address AI’s unregulated trends.
The OECD also flags increased cyber risks due to rapid financial digitalization, including indiscriminate data collection and potential exclusion of older adults from financial services.
Oh stresses the urgency of AI governance, emphasizing the need for financial firms and governments to focus on immediate AI governance to ensure broader social responsibility and inclusion.
Building trust in AI-based financial services requires not just regulations but also ensuring safety, transparency, and fairness. One solution could be Explainable AI (XAI), providing clarity on AI’s decision-making processes to enhance understanding and trust.
Park underscores the importance of collaboration between financial experts and AI specialists for successful AI-based financial innovations, emphasizing continuous communication and cooperation.
