# LONGPORT Whale Enters Malaysian Market with Next Generation Trading Infrastructure for Local Brokerages

- Link: https://www.thailand-business-news.com/pr-news/longport-whale-enters-malaysian-market-with-next-generation-trading-infrastructure-for-local-brokerages
- Published: 2026-05-05T13:00:00+07:00
- Author: PR Newswire

**_LONGPORT Whale, with proven track record across 100+ institutional clients in
Asia, makes its Malaysia debut at Bursa Malaysia Stockbroking Trade Fair 2026_**

KUALA LUMPUR, Malaysia, May 5, 2026 /PRNewswire/ — LONGPORT Whale, a provider of
AI-Ready securities trading infrastructure, is making its entry into the Malaysian
market at the Bursa Malaysia Stockbroking Trade Fair 2026. The move comes as Malaysia’s
Capital Market Masterplan 2026–2030 (CMP4) continues to hone in on local brokerages
to modernise core systems, balancing investor experience, regulatory compliance,
and operational resilience simultaneously.

Malaysian brokerages are increasingly confronted by a challenge that goes beyond
front-end upgrades. Legacy architectures struggle to keep pace with digital-native
investor expectations, rising cybersecurity standards, and the demand for multi-
market expansion simultaneously. For many such brokerages, the question is no longer
whether to modernize, but how to do so without adding complexity or disrupting the
business continuity that clients depend on.

Zhong Hua, CEO, LONGPORT Whale, said, "Core trading infrastructure must support 
continuous evolution — in investor experience, compliance, and AI readiness — without
adding unnecessary complexity. **The brokerages that lead the next decade won’t 
be the ones with the best system today; they’ll be the ones whose systems are designed
to keep getting better.** LONGPORT Whale aims to bring its Asia-proven experience
to help Malaysian brokers strike that balance."

Built on a cloud-native microservices architecture and trusted by more than 100 
institutional clients in Asia, Whale’s platform is engineered by industry professionals
and refined through years of first-hand operational experience. For the Malaysian
market, it addresses four priorities: a best-in-class trading experience validated
across competitive, highly regulated markets in Asia; system resilience and performance
built for institutional scale, with high system performance and output, real time
risk management, and low system latency; global market connectivity spanning Malaysia,
Singapore, Hong Kong SAR, US, and Japan without requiring system rebuilds; and an
API-first, data-unified architecture that gives brokerages a practical foundation
for AI adoption.

Hong Kong SAR and Singapore, where Whale serves online brokers, traditional banking
firms, banks and wealth management institutes in a stringent regulatory environment,
serve as the primary reference market for its Malaysia expansion. The company said
it aims to work with local industry participants as both an infrastructure partner
and a contributor to broader conversation on responsible modernization under CMP4.

**About LONGPORT Whale**

LONGPORT Whale provides integrated securities trading infrastructure to brokers,
banks, fund houses, wealth managers, and family offices across Asia. Its cloud-native
platform supports multi-market, multi-asset trading across front-, middle-, and 
back-office workflows, with a deployment model designed for regulatory alignment
and long-term scalability. Website: [www.longportwhale.com](https://www.longportwhale.com/)

**Media Contact**
**LONGPORT Whale PR Team****Email: ****[media@longportwhale.com](https://www.thailand-business-news.com/pr-news/media@longportwhale.com)**

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  |  This article was produced by Cision PR Newswire, our trusted news partner. The views expressed and the content presented here are solely those of the author and may not fully reflect the opinions of Thailand Business News. |

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**Read the original article :** [LONGPORT Whale Enters Malaysian Market with Next Generation Trading Infrastructure for Local Brokerages ](http://www.prnasia.com/story/archive/4949983_AE49983_0?rand=184833)
