Chun Chet Ng profile photo

Chun Chet Ng

Chief AI Officer, AI Lens Group

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I lead the AI team at AI Lens Group in Kuala Lumpur. We build software that reads bank statements, payslips and other financial paperwork, so lenders can assess borrowers properly, including small businesses with little credit history. Before that I spent five years on a Ph.D. teaching models to read text in the dark.

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Work

2024–now

AI Lens Group

Chief AI Officer, April 2024 to present

I lead a team of 16 that builds the software banks and lenders in Malaysia use to read financial documents and score credit. It reads bank statements, payslips, identity cards, invoices, financial statements and credit bureau reports, more than 50,000 a month, at over 95% accuracy and under five seconds a page, on the lenders' own servers. The business brings in seven-figure annual recurring revenue (MYR).

I also run our research. Our 3rd place in the ACM ICAIF 2025 retrieval challenge grew into PRISM, my first-author paper at EMNLP 2026, and what we learn there feeds back into what we ship.

More

The stack is Python and FastAPI, React, PostgreSQL, RabbitMQ and Docker, running on Azure and on-premise. I set up our Azure infrastructure and the GitHub Actions pipeline (self-hosted runners, branch gating, release checks), plan the sprints, and mentor engineers across backend, DevOps, OCR and AI system design.

2023–2024

Etch Media

Vice President of Engineering, October 2023 to March 2024

Etch Media runs advertising on LED display boards. Cameras recognized the cars going past (make, model, color) and the people nearby (age, gender, emotion), and an LLM matched what they saw to ad categories, so the board could play a fitting ad in real time.

I built the C# player that schedules and switches content on the custom LED boards, the backend services that connect the AI models to ad delivery, and the CI/CD on Azure.

2023–2025

Tibame Image Recognition

Part-time Instructor, 2023 to 2025

I taught hands-on OCR classes (video) on reading license plates and shop signboards with PaddleOCR and MMOCR. The course materials are open source: license plates and signboards.

2023

AkiraKan

Part-time ML/AI Research Scientist, January 2023 to September 2023

I worked on OCR for traffic-scene photos, reading lamp post IDs and license plates, and on some 3D projects.

2020–2022

ViTrox Corporation

Part-time Research Intern, March 2020 to December 2022

I worked on reading the characters printed on microchips, which are often low-contrast, blurred or broken. With Baidu and partner universities we built ICText, the largest dataset of text on integrated circuits, and ran it as an ICDAR 2021 competition.

More

A curriculum-learning training method I proposed for ICText improved character recognition and led to two papers. I also helped undergraduate interns with image classification and object detection projects.

2018–2023

University of Malaya

Research Assistant, September 2018 to December 2023

My Ph.D. years, in Prof. Chan Chee Seng's lab. I worked on finding and reading text in photos (detection, recognition and spotting) and on brightening low-light images, and helped build the ArT, EST-VQA and ICText benchmarks.

2017

Theta Service Partner

Intern Software Engineer, February 2017 to August 2017

My first job: fixing bugs, building customer requests and writing tests for a bank loan system, in the Centre of Excellence team.

Research

I started out in computer vision, teaching models to read text in awkward places: curved shop signs, tiny print on microchips, photos taken almost in the dark. These days the awkward place is financial paperwork. A few projects I'm proud of, newest first:

PRISM: finding the right page in a financial filing

2025 to 2026, AI Lens Group. EMNLP 2026 Industry Track

Analysts ask questions like "what was the operating margin last year?", and the answer sits on one page of a filing hundreds of pages long. Plain vector search often misses it. PRISM gets there without any training: a tuned system prompt, worked examples chosen for each question, and a retrieve, rerank and refine step before a single LLM ranks the results. We also scored every run on accuracy, latency and cost together, because that trade-off is what decides whether something ships. It started as our 3rd-place entry in the ACM ICAIF 2025 retrieval challenge and later won the Poster Paper Award at the FinLLM Symposium @ IJCAI 2026.

PRISM pipeline: offline prompt library and exemplar store, prompt engineering, retrieve-rerank-refine, ranking preparation, a single LLM listwise ranker, and ranked output
The PRISM pipeline, from the paper.

AI-BAAM: credit scoring from bank statements

2025 to 2026, AI Lens Group. ICLR 2026 workshop; earlier version an oral at ACM ICAIF 2025

Many Malaysian small businesses are doing fine but have too little credit history for a bank to score. Their bank statements tell the real story. AI-BAAM reads six months of statements, pulls out the account details and every transaction, checks the PDFs for tampering, maps who the money moves between, and turns the cash flow into features a credit model can use. Loan officers stay in the loop at every step.

AI-BAAM pipeline: bank statement ingestion, key information extraction, transaction table extraction, fraud analysis, network analysis, and cash flow analysis feeding a credit scoring model, with loan officers in the loop
How AI-BAAM turns statements into credit signals.

Text in the Dark: reading in near darkness

Ph.D. work, University of Malaya. ICPR 2022; Signal Processing: Image Communication 2025

My Ph.D. asked a simple question: does OCR still work on photos taken almost in the dark? Mostly it doesn't. Brightening the image makes it look nicer but leaves the text a smudge. So we built Text in the Dark, the first extremely low-light text dataset, with 3,075 images and 59,975 text instances annotated, and an enhancement method that restores the text itself, not just the brightness.

Three low-light scenes with every piece of text outlined: a shopfront, a wall of posters, and a numbered sign
Annotated scenes from the Text in the Dark dataset.

ICText: the text printed on microchips

2020 to 2024, ViTrox and University of Malaya. ICDAR 2021 competition; Pattern Recognition

The markings on a chip are tiny, low-contrast and often scratched or broken, and factories need to read and inspect every one. With ViTrox, Baidu and partner universities we built ICText, the largest dataset for it, with 10,000 images and 100,152 characters annotated, and ran it as a competition at ICDAR 2021.

Close-up of a microchip with each printed character boxed and labelled
A chip from ICText, every character boxed and labelled.

All conference papers

All journal papers

Workshop papers

Collaborators

People I've worked closely with, and learned a lot from:

Education

2018–2024

University of Malaya

Ph.D. in Artificial Intelligence (Computer Vision), September 2018 to December 2024

  • Thesis: Optical Character Recognition Under Challenging Lighting Conditions.
  • Thesis submitted in December 2023; passed the viva and graduated in December 2024.

2013–2017

TARUMT

Bachelor of Computer Science (Honours) in Software Engineering, May 2015 to May 2017

  • Graduated with Distinction; CGPA: 3.97/4.00.

Diploma in Science (Computer Science and Mathematics), May 2013 to May 2015

  • Graduated with Distinction; CGPA: 3.97/4.00.

Summer schools

Student awards

Volunteer

Outside work, I build and look after software for two Buddhist organizations in Kuala Lumpur, and review papers when I can.

Dhamma Earth

IT Volunteer, 2019 to present

Dharma Drum Mountain

Software Engineer, 2017 to present

Peer review

Certifications

NVIDIA

March 2026

Microsoft

June 2025

DeepLearning.AI and Amazon Web Services

November 2024