Malaysia's first licensed digital bank, GXBank received its approval to commence operations from Bank Negara Malaysia in September 2023, becoming the first of Malaysia's five digital bank licence applicants to do so. It has since grown to more than 1.4 million customers and reported more than 220 million transactions in 2025. Its business banking push has also gathered pace, with about MYR 25 million (approximately $5.6 million) disbursed to micro, small and medium-sized enterprises (MSMEs) through GX FlexiLoan.

Growth has increased the volume and complexity of risk operations. The bank has built three internal AI-enabled tools: FrAIdy and TrAIdy for fraud and anti-money-laundering (AML) case assessment, GuardPlus for document forensics in digital lending, and BI Bytes for governed self-service business intelligence.

Caroline Chong, GXBank's Head of Data, said the tools were designed to lower operating costs and allow analysts and business teams to focus on higher-value work. The bank has positioned AI as an operational support layer, not as a substitute for human judgement in regulated decision-making.

Growth creates a heavier risk and data workload

As GXBank has grown to serve more than 1.4 million customers and processed over 450 million transactions, the volume and complexity of risk operations have significantly increased. In a conventional model, higher transaction and customer volumes would require a proportional increase in analyst headcount.

GXBank developed FrAIdy and TrAIdy as a dual-engine generative AI framework for risk operations. The system uses transaction and behavioural data to prepare risk narratives and recommendations for analysts. It does not make final decisions. Human reviewers remain accountable, particularly for complex or higher-risk cases.

FrAIdy and TrAIdy reduce case assessment time

FrAIdy and TrAIdy automate the most time-consuming part of case handling: collecting information from multiple systems and turning it into a structured assessment. Chong said the tools reduced case processing time from 15–20 minutes to 1–3 minutes, while maintaining up to 95% accuracy in identifying high-risk cases and clearing low-risk alerts.

The bank scaled to one million customers with no additional headcount in the risk operations team. It has also saved about 16,000 working hours annually by reducing manual data retrieval.

"By automating routine tasks, we've been able to handle a much larger volume of cases, allowing our analysts to focus on more complex issues," Chong said.

The AI model is grounded in factual transaction data from GXBank's data warehouse, supported by pre-configured prompts and role-based access controls. Version 2.0 introduced more customer-centric assessment logic and cost optimisation, while the next phase is expected to add batch processing and more advanced predictive analytics.

GuardPlus strengthens document checks in digital lending

In April 2025, the bank identified a sophisticated fraud incident involving tampered income statements within its digital lending applications. This event necessitated a strategic recalibration of credit operations, prompting a temporary adjustment to lending limits while the bank proactively developed and deployed more robust security controls.

GuardPlus was built as an internal forensic layer to detect manipulated income statements before they move through the lending process. Rather than focusing only on the financial information shown on a document, the tool analyses the file's structure, metadata, trailer sequences, embedded objects and content characteristics. This allows the bank to test whether a document has been altered, not just whether the numbers appear plausible.

The system covers EPF statements, 98% of company bank statements and 94% of individual bank statements submitted to the bank. It processes checks in less than 0.1 seconds on average and achieved 100% accuracy, precision and recall in stress tests using known fraudulent documents and forged test files prepared by the cybersecurity team.

The tool is integrated into the credit decisioning workflow as a real-time control. Its role is to preserve straight-through processing for genuine applicants while stopping documents that show signs of tampering. GXBank is also developing a hybrid generative AI model so that the system can adapt more easily to new bank statement formats and reduce manual rule maintenance.

BI Bytes gives business teams governed access to data

BI Bytes was developed to ease pressure on a business intelligence (BI) team fielding more than 100 ad-hoc requests a year, ranging from straightforward extracts to more complex analysis. This created delays for business users and kept analysts focused on repetitive reporting rather than higher-value analysis.

The tool is a generative AI-powered chatbot developed in-house. It allows users in departments such as that allows users across retail, marketing, finance, product and operations to ask questions in plain English. The system translates those questions into Snowflake SQL, generates insight summaries and supports data visualisation through a governed interface.

It achieved a 94% SQL accuracy rate during testing and is designed to absorb 30% of ad-hoc analytics requests across key departments. Chong projected MYR 800,000 (approximately $182,000) in cost savings over three years by reclaiming analyst time and reducing dependence on manual data pulls.

"BI Bytes has empowered our teams to be more self-sufficient in accessing business-critical data," Chong said.

Rather than relying on third-party tools, GXBank created a proprietary semantic layer that embeds verified banking logic, table definitions and approved query structures. This design is intended to reduce hallucination risk and ensure that self-service analytics remains controlled within a regulated environment.

"AI is a tool that supports our team, but we ensure that final decisions are made by analysts, especially in cases with higher stakes or potential risks," Chong said.

The next phase focuses on scale and adaptability

GXBank's next phase will focus on improving the three systems and extending their use across the bank. FrAIdy and TrAIdy are expected to move into more advanced batch processing and predictive analytics. GuardPlus is being developed into a hybrid generative AI solution that can adapt to new document formats. BI Bytes will be expanded into more data domains, including MSME, mobile events and risk.

Whether these tools can maintain accuracy, control and auditability as GXBank continues to grow will be an important test of a digital bank that is still in its early years.