Singapore Retail Investors Turn to AI Assistants for Portfolio Decisions

Growing Reliance on In-App Intelligence

Retail investors across Singapore are integrating artificial intelligence into their trading workflows, turning to brokerage-embedded assistants for market interpretation and portfolio guidance. Platforms including Tiger Brokers, Moomoo, and Longbridge have rolled out AI features that parse news feeds, evaluate earnings reports, and surface actionable insights without requiring users to leave the app.

Tiger Brokers reported a 500 percent year-on-year rise in conversation volumes on its TigerAI assistant among Singapore users as of June 2026, with monthly active users climbing 65 percent over the same period. According to Jingxin Du, TigerAI product lead at Tiger Brokers, the shift reflects a move from single-question lookups to sustained dialogue, enabling the tool to learn individual risk profiles and trading objectives.

When reciprocal U.S. tariffs took effect in August 2025, queries spiked as investors sought clarity on exposure. The assistant delivered stock-specific impact assessments and sector-level sentiment reads, helping users reposition holdings in hours rather than days.

Case Studies in Execution and Restraint

Tiger Brokers highlighted two instances where the tool influenced timing. A high-net-worth client planning a short-term entry into a tech stock during a rally consulted TigerAI, which flagged elevated sentiment, an imminent earnings release, and recent insider selling. The investor delayed the trade; the stock dropped after results. In a separate case, a user uncertain about holding a tech position received analysis of an upcoming product launch, after which the stock gained.

Longbridge Group chief Nowa Zhu and Singapore regional chief Gavin Chia noted that every major market event in the past year correlated with measurable increases in daily active users and query volumes. Close to 30 percent of Longbridge's global user base has engaged with its AI suite, with roughly 18 percent interacting monthly.

Longbridge's agentic AI scans portfolios proactively, drafting action plans based on holdings and past behavior. It suggests moves but requires explicit user approval before execution, a design choice intended to preserve control while automating surveillance.

Depth Across Experience Levels

Moomoo chief growth and marketing officer Erika Chiang described three tiers of use. Beginners lean on AI to translate earnings transcripts, options chains, and financial jargon into plain language. Intermediate traders deploy it to compare data points quickly and track sector developments. Advanced users apply it to multi-factor screening, options modeling, and backtesting strategies.

Engagement with Moomoo AI in Singapore has accelerated since the tool launched in June 2025, according to Chiang, who noted that usage has expanded from equities into options, initial public offerings, bonds, and exchange-traded funds within twelve months.

Timothy Tham, a 30-year-old public relations professional who uses Moomoo, said he prefers brokerage-integrated AI over standalone services. He trusts that platforms have vetted data privacy and security protocols, and he uses the tool to scan holdings for relevant news, generate diversification ideas, and aggregate industry snapshots from multiple sources in one query.

Infrastructure and Talent Bets

Longbridge plans to establish a Longbridge AI Lab in Singapore, partnering with local universities and recruiting AI specialists to the city-state. Zhu and Chia framed AI as a mechanism to broaden investor access to Singapore-listed names beyond the major banks, arguing that algorithmic insight can level informational asymmetries.

Tiger Brokers intends to extend TigerAI from information retrieval into trade assistance, though execution authority will remain with users. Moomoo is embedding AI across its education platform, Moo Academy, to support learning pathways alongside live trading tools.

Behavioral Incentives and Transparency

S. Kishan, founder of AI software development firm Analytico AI, cautioned that brokerage AI carries directional bias. Trading platforms benefit from user activity, and recommendation systems may be optimized to encourage action rather than inaction. He urged platforms deploying AI to disclose the behaviors their models are tuned to promote, ensuring users understand the incentive structure beneath the interface.

The adoption curve suggests that AI is transitioning from novelty to infrastructure in Singapore's retail trading ecosystem. As platforms deepen integration and expand capability, the challenge will be maintaining transparency around how these tools shape decision-making and whether they truly serve investor outcomes or platform engagement metrics.