From Hyper-Personalized Financial Products to Risk Management... AI Innovation in the Financial Sector

Samjong KPMG "Global Top 50 Banks Increasing AI·ML Investment Share"
Financial Firms Enhancing AI-Based Anomaly Transaction Detection Systems for Proactive Fraud Response
Concerns Over Data Bias and Personal Information Leakage... Need for Responsible AI Use Measures

As artificial intelligence (AI) continues to advance based on enhanced computing power and the popularization of big data, trends in AI investment and technology utilization in the global financial sector have been presented.

According to the report "Finance Dyed in AI, the Booster of Innovation" published by Samjong KPMG on the 27th, AI-related investments by the world's top 50 banks have increased in number since 2016. The proportion of AI and ML (machine learning) investments also significantly rose from 0.2% ten years ago to 4.0% in 2023.

Regionally, investments in AI-related companies have been concentrated in North America, while the share of Europe expanded by 14.4% in 2023 compared to the previous year. Although large-scale deals decreased, various AI companies such as the U.S. SirionLabs ($110 million), Austria's GoStudent ($95 million), and Canada's Certn ($80 million) successfully secured funding. By investment type, venture capital (VC) accounted for 90.6%, with late-stage VC investments mostly targeting companies with stable revenue models.

Over the past five years (2019?2023), the business models of major AI companies invested in by the global top 50 banks have varied widely, ranging from cloud-based platforms for AI development and management (Databricks) to transportation matching platforms (Frete.com). The countries of key investee companies also diversified, including the U.S., China, France, and Brazil.

AI utilization is expanding across financial organizations, from human resources and risk management to marketing. This trend is expected to accelerate with advancements in natural language processing and generative AI.

In the front office, AI chatbots are used to provide flexible responses to customer inquiries. Personalized services through AI virtual assistants such as BoA’s Erica and RBC’s NOMI are also evolving. Additionally, Vanguard and DBS have introduced robo-advisor services that recommend investment plans and portfolio settings based on customers’ goals and investment preferences, differentiating their services through generative AI utilization and algorithm enhancement.

In the middle office, AI and ML-based fraud detection systems that learn user records and abnormal transaction information provide financial fraud detection services tailored to customers’ usage patterns. Notably, Mastercard and Visa have built AI models that detect fraudulent payments in real time to prevent losses. Meanwhile, as global regulatory compliance complexity increases, collaborations between banks such as Citibank, Valley Bank, and Australia’s Commonwealth Bank with AI platform providers or solution companies are also observed.

In the back office, the focus is on operational efficiency and speeding up service processes through AI. Swiss Re, Daido Life Insurance, and JP Morgan Chase are reducing time spent on reviewing and analyzing medical and legal documents using AI, while Goldman Sachs, Morgan Stanley, and Barclays have established automated systems for tasks such as earnings report summarization to achieve efficiency.

Meanwhile, concerns about data bias and discrimination, personal information leakage, and lack of explainability related to AI usage have increased the need for “Responsible AI” utilization and the establishment of AI governance systems within organizations.

The EU became the first in the world to enact AI legislation, differentiating regulations according to AI risk levels. The U.S. Biden administration emphasizes AI model stability evaluation, standard setting, and personal data protection through executive orders. South Korea has been preparing a series of policies to promote AI use and enhance trust in the financial sector, starting with the 2021 "AI Guidelines for the Financial Sector." In March 2024, the "Financial Sector AI Council" will be launched to discuss policy directions for activating generative AI use and ensuring safety, including network separation and securing high-quality data.

Lee Dong-geun, Executive Director of the Samjong KPMG AI Center, forecasted, “Beyond traditional areas such as credit evaluation, robo-advisors, chatbots, recommendations, and fraud detection, the use of generative AI will accelerate innovation across the entire financial value chain.” He added, “When domestic financial companies promote AI, it is important to set AI goals to achieve business outcomes, establish AI utilization architectures under financial security regulations, and build safe and ethical AI governance.”