Research

AI-Driven Financial Services

Our programs strive to advance transformative and commercializable research in the fields of finance and technology. We focus on developing pioneering solutions that enhance capital management, risk assessment, and operational efficiency in today’s dynamic markets.

We leverage AI and blockchain technologies to create intelligent systems capable of real-time portfolio management and dynamic risk assessment. Our initiatives include AI-driven platforms for e-commerce loan securitization and attention-based agents for customer interaction. In the area of Web3, we optimize next-generation distributed ledger designs for data infrastructure and address regulatory technology (RegTech) by exploring automated threat modeling solutions for virtual asset markets. We also contribute to retirement savings by proposing a passive, low-cost downside-risk management framework that redesigns the structure of Mandatory Provident Fund (MPF) equity.

By engaging with industry stakeholders and harnessing cutting-edge technologies, we aim to deliver scalable and practical financial solutions that empower users, enhance decision-making capabilities, and promote sustainable growth across various financial ecosystems.

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Research

AI-Driven Financial Services

The AI-driven Financial Service program strives to advance game-changing commercializable research in the spaces of retail lending, production & supply-chain financing, capital markets, institutional banking, and financial regulation. We support R&D efforts in broad areas of business and finance, emphasizing fresh approaches and novel solutions that are driven by AI and big data.

These include extracting business value from data that is transferable across behavioral scenarios, developing augmented intelligence to facilitate credit and insurance decision-making, promoting novel practices of financial risk management to strengthen financial stability, and FinTech applications to hedging and financing in production and supply-chain.

From wealth management to blockchain and token technologies, we support cutting-edge research with commercial potential in optimization and machine learning algorithms, deploying reinforcement learning and deep neural networks.

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Research

AI-Enhanced Financial Technology

The AI-enhanced Financial Technology program commits to nurturing ground-breaking technologies with in-depth research potential that are relevant to contemporary business and finance.

We support projects with commercial potential in novel wealth management solutions utilizing advanced ideas from data science, optimization and control.

We deploy machine learning algorithms including reinforcement learning and deep neural networks, leveraging federated machine learning structures and their application in asset pricing and investor behaviour. We also support blockchain and token technologies for application in securitization and asset management; smart contracts, and digital currencies.

Social media provides a gold mine of data for understanding and forecasting financial market environments. We aim to leverage the power of AI-driven technology and the availability of social media big data to serve a wide range of clients from regulators to investors.

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Research

Social Media Analytics for FinTech & Services

Social media provides a massive quantity of data, constantly updated, which may be used to understand and forecast financial market environments. This data directly affects how the economy operates, how investors make decisions, how regulators function, how the public responds, and how economies/markets interact. We aim to leverage the power of AI-driven technology and the availability of such data to develop and deploy a set of intelligence systems in three key domains; financial opinion, international financial relations, and the financial darknet.

These systems can be commercialized in two formats: syndicated products such as trend reports, and customized services such as live-monitoring visualizers.

Research Overview

AI & Blockchain-Driven Regulatory Technologies

The project addresses the need for automated threat modeling in dynamic virtual asset markets to map attack vectors and perform multi-layer risk scoring across…

Risk-sensitive Markov Decision Processes and Reinforcement Learning for Liquidity Management

The project will deliver an Integrated RWA Liquidity Engine that combines risk-sensitive optimization with multi-agent reinforcement learning to jointly manage AMM spreads and funding…

Passive and Low-Cost Downside Risk Management for Hong Kong’s Mandatory Provident Fund (MPF)

The project proposes a passive, low-cost, cross-sectional downside-risk management framework that redesigns MPF equity building blocks. The HKAIFT SafeSelect Index will select the most…

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Units 1101-1102 & 1121-1123,
Building 19W Science Park West Avenue,
Hong Kong Science Park,
Shatin, Hong Kong

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Research

AI-Driven Financial Services

Research Overview

AI & Blockchain-Driven Regulatory Technologies

AI & Blockchain-Driven Regulatory Technologies

Risk-sensitive Markov Decision Processes and Reinforcement Learning for Liquidity Management

Risk-sensitive Markov Decision Processes and Reinforcement Learning for Liquidity Management

Passive and Low-Cost Downside Risk Management for Hong Kong’s Mandatory Provident Fund (MPF)

Passive and Low-Cost Downside Risk Management for Hong Kong’s Mandatory Provident Fund (MPF)

Address

Units 1101-1102 & 1121-1123, Building 19W Science Park West Avenue, Hong Kong Science Park, Shatin, Hong Kong

Units 1101-1102 & 1121-1123,
Building 19W Science Park West Avenue,
Hong Kong Science Park,
Shatin, Hong Kong