On 19 Aug 2024, the HKMA released survey results indicating 75% of retail-focused authorized institutions are adopting or planning to adopt big data analytics and AI (BDAI), while 39% are doing the same for generative AI (GenAI). The survey highlighted BDAI's broad operational use across customer-facing and internal functions, whereas GenAI adoption remains primarily internal with limited customer-facing applications.
This article was generated using SAMS, an AI technology by Timothy Loh LLP.
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Survey Overview
On 19 Aug 2024, the Hong Kong Monetary Authority (HKMA) published a survey report detailing findings on consumer protection aspects related to the use of big data analytics and artificial intelligence (BDAI) and generative artificial intelligence (GenAI) by authorized institutions. The survey, conducted in May 2024, covered 28 authorized institutions primarily serving retail customers, with results summarizing adoption rates and use cases.
BDAI Adoption and Use Cases
Seventy-five percent of surveyed institutions reported adopting or planning to adopt BDAI across general banking products, services, and daily operations. Use cases spanned customer-facing activities (e.g., identity authentication, credit assessment), middle-office functions (e.g., AML and fraud detection), and back-office operations (e.g., operational automation). Third-party service providers were widely engaged for BDAI applications, with the most common use cases being operational automation (20 institutions), AML/fraud detection (19), and identity authentication (18).
GenAI Adoption and Use Cases
Thirty-nine percent of surveyed institutions reported adopting or planning to adopt GenAI, predominantly for internal business functions such as summarisation, translation, coding, and internal chatbots. Customer-facing GenAI applications remained nascent, limited to drafting customer responses and preparing sales/marketing materials. Most GenAI solutions were sourced from off-the-shelf third-party providers, with summarisation and translation (10 institutions) being the leading use case, followed by coding (4).
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