Key Takeaways
- Banks adopting IDP can shorten loan approval times by up to 70%, improve fraud detection by 50%, and cut document-related operational costs by 40%, replacing slow, error-prone manual processing at scale.
- IDP impacts the entire document lifecycllifecycle, from KYC onboarding and credit file review to L/C trade finance and invoice processinprocessing, with ACB processing over 150 million documents per year as a real-world proof point.
- For Vietnamese banks, choosing the right IDP solution means prioritizing accuracy on Vietnamese documents, local data residency compliance, and on-the-ground technical supporsupport, factors where domestic platforms have a clear edge over international alternatives.
Today, every bank is operating on a massive volume of documents: loan applications, KYC forms, L/C documents, account statements, credit agreements and more, flowing into the system every single day. Most of these are still processed manually. Staff have to key in every line, review every page and cross-check every field – a time‑consuming process that is hard to scale and inherently prone to human error.
This is the reality for hundreds of banks across Vietnam and Southeast Asia. The solution is no longer a new concept: Intelligent Document Processing (IDP) combined with modern OCR is gradually reshaping how financial institutions operate, from front-office interactions to back-office operations.
How is IDP different from traditional OCR?
Traditional OCR (Optical Character Recognition) focuses on a single task: converting images into plain text. It does not understand context, cannot reliably classify documents, and quickly runs into limitations when dealing with non‑standard banking forms.
IDP significantly extends these capabilities. By combining OCR with NLP (Natural Language Processing), Generative AI and large language models (LLMs), IDP can not only “read” but also understand, classify and extract structured data from almost any type of document – from printed forms and scanned images to mobile photos of handwritten documents. A 2025 study published on ResearchGate reports that banks adopting IDP can shorten loan approval times by up to 70%, improve fraud detection rates by 50%, and reduce document-related operational costs by around 40% compared with manual processing.
Which banking processes benefit the most?
IDP does not solve just a single use case. It has a broad impact across the entire document lifecycle – from customer onboarding at the front line to core systems and risk/compliance functions at the back end.
- KYC and customer onboarding: IDP can automatically extract information from national ID cards, passports, employment contracts, bank statements and other supporting documents, cutting KYC processing time by an estimated 70–80% in some deployments, according to KlearStack. This enables banks to implement remote eKYC journeys, reduce dependence on branch visits and still maintain strong compliance and risk controls.
- Credit files and loan approval: Traditional loan processing cycles often take 45–60 days, largely due to manual document review, data entry and cross‑checking. With IDP, data from financial statements, payroll slips, contracts and supporting documents can be extracted automatically, helping reduce processing time to about 15–30 days while maintaining credit risk controls and adherence to internal policies.
- Trade finance documents (L/C): Letters of credit typically involve large document packages spanning multiple pages and formats, making them one of the most complex document sets in commercial banking. IDP helps automatically classify, extract and normalize data from these documents, significantly reducing the risk of input errors, payment delays or discrepancies against UCP requirements.
- Payments and accounting: IDP platforms can handle high volumes of VAT invoices, payment orders and accounting vouchers each day through standardized workflows, with human‑in‑the‑loop steps triggered where manual review is required. This preserves processing speed while maintaining the level of control needed for audit and compliance.
Real‑world example: GreenNode IDP processes over 150 million documents per year at ACB
In Vietnam, ACB is one of the pioneer banks deploying IDP at scale. According to Ms. Chu Hong Hanh, Head of the Innovation Lab at ACB, the GreenNode IDP OCR solution enables the bank to automatically extract information from thousands of complex banking forms and automatically classify documents from long, unstructured bundles – reducing document processing time by more than 90% and saving hundreds of billions of VND each year. ACB currently processes over 150 million documents annually through this system.
GreenNode IDP is developed by a team of Vietnamese engineers and is purpose‑built for Vietnamese banking and financial document workflows. The system delivers over 99% field‑level accuracy for printed forms, processes each page in under 1.5 seconds, supports more than 200 document types and can be integrated into existing systems within around five days via APIs or SDKs. A key advantage over international platforms such as ABBYY Vantage or Microsoft Azure AI Document Intelligence is that all data is stored and processed on local infrastructure, ensuring compliance with the Personal Data Protection Law 2025 and Decree 356/2025/NĐ-CP, as well as current regulations on financial data residency in Vietnam.
Key criteria for selecting an IDP solution for banks
Not every IDP solution is a good fit for the realities of Vietnamese banking. The following factors are critical when evaluating vendors:
- Accuracy on Vietnamese documents: Many global platforms are trained primarily on English‑language data. Vietnamese banking forms have specific layouts, diacritics and unique field structures. It is essential to verify that the models have been optimized for local language and document formats.
- Compliance and data residency: Under current regulations, many categories of financial and personal data must be stored within Vietnam. The solution needs to run on domestic infrastructure and avoid routing data offshore. This is why many banks prefer providers with cloud infrastructure located in Vietnam rather than relying solely on foreign hyperscalers.
- Human‑in‑the‑loop and audit trail: In financial documents, silent errors are unacceptable. The system must automatically flag low‑confidence extractions for manual review and maintain a complete audit trail of user actions for internal control and external audits.
- Integration with core banking: A viable solution should integrate seamlessly with core banking systems, ERP platforms and internal applications via standard APIs, without forcing a major re‑architecture of existing IT systems.
- Implementation time and local support: For 24/7 systems, incidents can happen at any time, including outside office hours. Having a local technical support team that understands the bank’s architecture and can respond quickly is a major advantage. This is where vendors with on‑the‑ground teams in Vietnam, such as GreenNode, have a clear edge over international platforms without a local presence.
Criteria for choosing an IDP solution for banks
Not all IDP platforms align with the legal, data and operational requirements of Vietnamese banks. Some of the most important criteria include:
Accuracy on Vietnamese documents: Many international platforms are trained mainly on English‑language data, while Vietnamese banking forms have their own layouts, visual conventions and field structures. It is therefore essential to thoroughly assess how well the model performs on Vietnamese content, especially non‑standard forms and semi‑structured documents.
Compliance and data residency: Current regulations require many types of financial and personal data to be stored and processed within Vietnam, and impose additional obligations on cross‑border data transfers. As a result, banks tend to favor solutions that can run on local cloud infrastructure or be deployed on‑premise, limiting data transfer to foreign data centers and reducing compliance risk.
Human‑in‑the‑loop and audit trail: For financial documents, errors cannot be allowed to “slip through unnoticed”. An IDP system should be able to flag low‑confidence extractions, route them for manual review and log the full history of actions for audit, internal investigations and risk management.
Integration with core banking and the existing ecosystem: A suitable IDP solution needs to connect with core banking, ERP, LOS, LMS and internal applications via standard APIs, without requiring banks to overhaul their current IT architecture. This is key to fast deployment, lower integration costs and minimal operational disruption.
Implementation timelines and local support: In always‑on environments, incidents can occur at any time. On‑site technical teams who understand the bank’s infrastructure and internal processes play a crucial role in shortening incident response times. This is also a differentiator for providers with local teams in Vietnam, such as GreenNode, compared with international platforms that lack local presence.
From POC to real‑world production
In many institutions, the main barriers to IDP adoption are not purely technical, but lie in data governance, process redesign and change management. A pragmatic approach is to start with a focused use case – for example, incoming invoice processing or KYC automation – and then gradually expand to other workflows once there is enough operational data and internal confidence.
A modular rollout model gives IT teams better control over risk while demonstrating ROI early in the journey. With GreenNode IDP, the time from API integration to production use is typically under five days, thanks to pre‑built templates for banking use cases and an AI Platform optimized for production environments. In parallel, GreenNode runs deep‑dive workshops for financial institutions, sharing real‑world case studies and practical AI deployment roadmaps.
Ultimately, the key question for banks is no longer “Is IDP the right fit?” but rather “Which processes should we automate first, and how quickly can we measure tangible results?”. With growing experience and datasets from the Vietnamese market, the answer to that question is becoming increasingly clear.
