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1Q26 Elderly Investment Scam Losses Surge Nearly 70% YoY to HKD330 million; Police, HKMA Join Forces to Combat Mule Account Transfers
Police recorded 1,264 elderly fraud cases in 1Q26, of which 329 were investment scams, involving losses of HKD330 million, up nearly 70% YoY. Total fraud cases in the quarter reach...
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1Q26 Elderly Investment Scam Losses Surge Nearly 70% YoY to HKD330 million; Police, HKMA Join Forces to Combat Mule Account Transfers
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Police recorded 1,264 elderly fraud cases in 1Q26, of which 329 were investment scams, involving losses of HKD330 million, up nearly 70% YoY. Total fraud cases in the quarter reached 9,427, with 1,961 arrests related to various fraud offences, up 14% YoY. Investment scams accounted for 10% of the total, with 1,003 cases and losses amounting to HKD680 million.

The largest loss involved a 67-year-old foreign businessman who developed an online romantic relationship with a person claiming to be an "investment expert". Over six months, he transferred crypto assets worth HKD84.79 million to the fraudsters e-wallet and only realized he had been deceived when he was unable to withdraw returns.

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At a police press conference, a retired woman in her sixties with a bachelors degree shared that after viewing an investment advertisement on Facebook last year, she was added to a messaging group where someone impersonated a veteran investor, Kwok Sze-chi, to talk up thinly traded penny stocks. After ramping up share prices, the fraudsters quickly offloaded their holdings to cash out. They falsely claimed compensation could be arranged and advised her to transfer her remaining stock balance to mule accounts. After receiving HKD10,000 in compensation, she "did not attempt to believe she had fallen into a scam" and proceeded to make more than ten transfers to multiple accounts, ultimately losing over HKD1 million.

Police research indicated that individuals with investment experience tended to be more overconfident and thus more susceptible. Experienced investors suffered average losses of HKD1.05 million, double that of those without investment experience. In addition, the higher the education level, the greater the losses. Those with a masters degree incurred losses four times higher than individuals with only primary school education.

To curb investment scams, the Police, the Hong Kong Monetary Authority (HKMA) and the Securities and Futures Commission (SFC) have introduced a series of measures, including plans to lower the daily transfer limit for newly onboarded remote account-opening customers to third parties to no more than HKD100,000 within the year, increasing the difficulty for fraudsters to use mule accounts for fund transfers.

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Chan King-hung, Executive Director (Enforcement and AML) of the HKMA, said the SFC will share an alert list with banks covering suspicious investment products or platforms. Through bank network analysis, potential victims can be identified, and customer information can be shared via the interbank information exchange platform (FINEST) to enable early contact with victims. As of end-March, 16 banks had joined the platform, with a target to cover 28 banks in 2Q26, representing 95% of the market.

Chan added that banks will monitor account usage and, if satisfied that an account is not a mule account, may adjust transfer limits upward based on a risk-based approach. He noted that most customers transfer less than HKD100,000, with only a small number requiring higher transfer amounts, and thus the impact on the general public is expected to be limited.

In addition, the HKMA and Police will pilot cross-agency account-opening data analytics to identify mule accounts at an early stage. Chan explained that in the past, some individuals opened multiple accounts within a short period via online banking in the early hours, or overseas individuals visited several branches in Hong Kong simultaneously to open accounts, which individual banks might not detect. By combining account-opening data with suspicious account intelligence provided by the Police, a machine learning model assessing mule account risk will be developed, enabling banks to adopt a "red flag system" to identify and monitor accounts at an early stage.(da/j)

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