Retail Investors Urged to Be More Adaptive to AI Developments

Further steps must be taken following the ratification of the Capital Markets Bill. In an era where the world has shifted to real-time artificial intelligence (AI) trading technology, some retail brokers in Indonesia are still clinging to outdated stock trading systems. In advanced markets like the United States (US), the use of real-time data, algorithms, and order flow analysis has become the standard for investment decision-making. This situation renders many decisions irrelevant to the current market conditions. In fast-moving and volatile markets, even the slightest information delay can significantly impact trading outcomes, from delayed entries to suboptimal exits. Retail investors are thus compelled to adapt. Recognising this change, Indo Premier Sekuritas (IPOT) has introduced a new approach through an AI-based real-time stock trading app with live indicators. Retail investors now have access to trading systems previously associated with institutional investors, according to Chief Marketing Officer of PT Indo Premier Sekuritas (IPOT), Sergio Ticoalu, in an official statement on Wednesday (22/4). He added that through various AI-based features such as AI Live, Bandar Action, and Hit Action (HAKA and HAKI), investors can monitor market activities in seconds. Data that was previously available only in numerical form can now be processed into more easily understandable insights. Combined with the Live Order Book and Order Queue, market movement transparency becomes clearer, allowing investors to read demand and supply dynamics directly without relying on assumptions or speculation. This approach is believed to transform the way investors make decisions. Previously, many decisions were based on opinions, rumours, or delayed data; now, decisions can be made based on current market conditions. In practice, the use of real-time data and AI-based analysis helps investors identify momentum faster, avoid delayed entries, and design more measured strategies in stock trading. From an infrastructure perspective, Sergio explained that the system is designed with real-time architecture featuring low latency and high data processing capabilities. With managed funds of around Rp312 trillion and large-scale technology investments, this platform has a foundation that enables the development of a stable and scalable AI stock trading system. Besides performance, security is a primary concern. Amid rising cybercrime risks, IPOT provides a server-based protection system with layered anti-phishing mechanisms. This system is designed to detect suspicious activities, prevent illegal access, and protect against potential threats such as malware and remote access. In an increasingly competitive market environment, the use of technologies like real-time AI trading becomes a significant differentiating factor, he said. Investors with access to real-time data and advanced analysis systems will be in a superior position compared to those still relying on systems with information limitations. This demonstrates that stock trading performance is not only determined by boldness but also by the quality of data and systems used. With the advent of real-time AI-based trading technology, investors now have the opportunity to make faster, more accurate, and more relevant decisions aligned with actual market conditions, he concluded.