The Complete Guide to Using AI in the Financial Services Industry in Viet Nam in 2025

Vietnam's financial services sector in 2025 is being reinvented by AI: the market is accelerating toward multi‑billion‑dollar scale and banks are moving well beyond simple chatbots into core operations like TPBank's voice transfers and Cake by VPBank's GenAI personalization, while 94% of local financial institutions report active interest in AI-driven solutions; see a clear market snapshot in Vietnam's AI market outlook report Invest Vietnam 2025 AI market outlook.

Rapid digital adoption (over 80% smartphone penetration) means digital banking revenue is forecast to top $1B, creating space for AI in fraud detection, dynamic credit scoring, and financial inclusion strategies noted in industry analysis on digital banking transformation in Vietnam GFT digital banking trends in Vietnam.

For teams and managers ready to act, practical upskilling matters - Nucamp's AI Essentials for Work bootcamp - Nucamp registration and syllabus teaches promptcraft and applied AI skills that translate these sector shifts into operational wins.

AI matters for Vietnam's financial services because it turns scale and data into tangible value: faster, personalized service for an increasingly digital customer base, wider financial inclusion for rural and thin‑file borrowers, and steep cost and risk reductions that directly hit the bottom line.

Local reporting shows banks are already using AI for everything from 24/7 virtual assistants and alternative credit scoring to real‑time fraud detection and predictive cash management - practical benefits summarized in industry coverage like AI banking in Vietnam - Bestarion overview and AI's role in Vietnam banking - VNEconomy analysis.

That combination of customer gains and operational efficiency is not abstract: TPBank credits AI-driven analytics with cutting cash reserve needs by up to 25% at its 500 LiveBank branches, a vivid example of how smarter forecasting turns vast transaction flows into immediate savings.

At the same time, adoption brings clear challenges - talent shortages, data quality, and investment costs - so the real opportunity lies in pairing technology with governance and upskilling to make AI work reliably across Vietnam's fast‑growing digital finance ecosystem.

“Through data analysis and AI models, we can predict customer behavior at each transaction point and calculate appropriate daily cash reserves for our 500 automated LiveBank 24/7 branches. This has enabled us to reduce our cash reserve needs by up to 25 per cent.”

Regulation is shifting from uncertainty to active stewardship, and for Vietnam's financial firms that's good news: after years of policy building around the National AI Strategy and MoST's nine principles for responsible AI, regulators moved decisively in 2025 - culminating in the new Digital Technology Law that frames AI with a practical, risk‑based approach and sectoral responsibilities; see Vietnam Briefing's overview of the evolving AI legal landscape Vietnam Briefing: Vietnam's AI Sector in 2025 and the June 14, 2025 passage of the Digital Technology Law that creates the country's first comprehensive AI and digital industry statute Vietnam Passes First‑Ever Law on Digital Technology Industry.

Key practical effects for finance teams: high‑risk AI systems will face stricter compliance and technical standards, AI‑generated products must be clearly labeled for transparency, personal data protections are being upgraded via the Draft PDP Law (scheduled for final review in May 2025 and expected to take effect in late 2025), and a regulatory sandbox lets innovators trial services under oversight for up to two years - while targeted incentives (for example generous R&D deductions and tax breaks for talent) make investing in compliant AI more affordable.

The takeaway for banks and fintechs is clear: treat regulation not as a brake but as a roadmap - prepare documentation, risk assessments, and labeling workflows now so new AI deployments meet both the letter and the spirit of Vietnam's fast‑maturing rules while unlocking the law's practical incentives.

Data, privacy and backbone infrastructure are the backbone decisions that will determine whether AI in Vietnam's finance sector is a risk or a competitive edge: the new Law on Data takes effect 1 July 2025 and creates wide‑ranging rules for digital data, while the draft Decree on Data‑related Activities tightens licensing, local‑entity and infrastructure requirements for data intermediaries, aggregators and exchange platforms - meaning some providers must be established in Vietnam and even deposit at least VND 5 billion (≈US$200,000) with a local bank to operate, a concrete cost that forces early planning rather than last‑minute fixes (see the Vietnam Briefing coverage of the draft Decree on Data-related Activities).

The Law also defines

“important” and “core” data

and restricts cross‑border transfers of those classes, requires periodic risk assessments for administrators of sensitive datasets, and recognizes four levels of data analysis (from human‑only to fully automated Level‑4 AI), so teams must map which systems will need human oversight versus automated pipelines.

Expect a National Data Centre and National General Database to be rolled out in 2025, centralizing government datasets that banks and fintechs will increasingly integrate under new access rules (overview in the Hogan Lovells Law on Data summary).

At the same time, regulators are opening a controlled path for innovation: Decree 94 launches a fintech regulatory sandbox from 1 July 2025 to pilot credit scoring, open‑API and P2P solutions under supervision, which is a practical place to test secure data flows before scale (see DFDL guidance on Decree 94 and the fintech sandbox).

These changes mean compliance, security architecture, and clear consent and data‑localization plans must be part of any AI roadmap from day one.

Common AI use cases in Vietnam's financial services are already concrete and measurable: electronic KYC and biometric verification lead the pack, shrinking onboarding from hours to seconds and cutting fraud - solutions from local and regional vendors report verification times as fast as 2 seconds with 99% accuracy and even sub‑second claims in bank pilots, while platform rollouts have dropped manual onboarding from 12 hours to under 5 minutes for large apps; see TPS Software eKYC solution results, HyperVerge Ahamove verification case study and Cake Digital Bank FaceAuthen on Vertex AI case study.

Beyond onboarding, banks use biometric eKYC to satisfy regulatory requirements while LLM‑powered chatbots and recommendation models speed product approvals and personalize offers (Cake reports loan/card decisions in roughly two minutes), and fraud‑detection stacks combine liveness, OCR and anti‑spoofing to reduce false positives and lift conversion rates.

The practical takeaway for product teams: prioritize reliable, certified eKYC and end‑to‑end biometric flows first - they deliver the fastest customer impact and create safe data pipelines for downstream AI in credit, customer service, and fraud prevention.

“HyperVerge has a lot of experience in the eKYC field, so their solution is complete and meets many of Ahamove's requirements. Their system is also very stable.”

Choosing AI tools, models and vendors in Viet Nam means being pragmatic: prioritize Vietnamese‑language performance, data sovereignty and a vendor's ability to curate clean local datasets rather than chasing headline model sizes.

Domestic LLMs are already competitive - Zalo's KiLM and VinBigData's ViGPT sit on the VMLU leaderboard - so shortlist vendors who offer Vietnamese fine‑tuning and clear data‑handling workflows, or pick open models that can be adapted locally with tools like Llama‑based stacks and local runtimes (Ollama, Llama.cpp, GPT4All) when on‑prem privacy or cost matters.

Treat data curation as a non‑negotiable step - NeMo‑style pipelines that remove low‑quality content and preserve domain diversity are why some Viettel and university efforts succeed - and factor in practical barriers to cloud‑first approaches (some global LLM access requires a US phone and paid tiers that can equal “a week or two” of food for many users).

For financial firms, the right vendor will combine verified eKYC/data‑annotation partners, a roadmap for regulatory compliance, and clear SLAs for model updates and human oversight; start with a short, controlled pilot that measures Vietnamese‑language accuracy, latency and auditability before scaling.

For further reading on local model progress and data pipelines see the VMLU Vietnam Generative AI Progress Report and the NVIDIA NeMo Curator Vietnamese data processing notes.

“The increase in the number of LLMs in Vietnam indicates significant interest from numerous companies and individuals in enhancing the applications of GenAI. In the future, I believe the trend will lean towards utilizing open LLMs like Llama, adapting them for specific problems and domain data. However, there will still be research groups that continue to train their own large language models.”

Building AI talent and teams for Vietnam's financial firms is a practical, business‑led effort: assemble cross‑functional squads that combine product owners, ML engineers, data architects and compliance specialists so technology delivers measurable customer outcomes rather than isolated proofs‑of‑concept - exactly the “Talents and Team Capabilities” GFT highlights as critical to digital banking transformation GFT report on digital banking transformation in Vietnam.

Recruit selectively and reskill aggressively - Adecco's Q2 2025 market update shows near‑30% growth in job demand with banks and fintechs targeting AI/ML, cloud, cybersecurity and data governance roles - so blend targeted external hires with internal upskilling programs and short, product‑focused learning sprints to close gaps quickly Adecco Vietnam Q2 2025 talent market update.

Make cloud and operationalization a core competency too: Temenos notes leading local banks are moving core platforms to cloud, which raises the value of engineers who can ship models safely into production and work alongside IT to meet regulatory and latency needs Temenos analysis of Vietnam cloud and AI shift.

With over 80% smartphone penetration, the most memorable payoff comes when a small, well‑aligned team turns local language data into a mobile feature that improves onboarding or fraud detection within months, not years.

“The hiring landscape will remain strategic,” Chuong shared.

For beginners in Vietnam, a practical step‑by‑step AI roadmap starts by picking one high‑value, low‑risk use case - customer support automation, eKYC, or AML triage - where outcomes and compliance are clear, then run a short, measured pilot rather than a big‑bang rollout; ABeam's playbook shows a PoC can be delivered in as little as 1.5 months and, with iterative feedback, reduce workloads dramatically (one case cut email handling by ~80%) so early wins fund the next phase ABeam Consulting generative AI implementation guide for financial services in Vietnam.

Next, map data flows and fix quality issues up front - UEH research stresses that synchronized, clean financial data and standardized disclosures are prerequisites for reliable ML models and safer deployment UEH research on artificial intelligence in Vietnamese financial services.

Build governance and human‑in‑the‑loop checkpoints to catch hallucinations and satisfy regulators, measure ROI and user impact continuously, then scale into the fintech sandbox or controlled production once accuracy, latency and auditability meet business and legal thresholds; Vietnam Briefing's market snapshot underlines broad institutional appetite - 94% of local firms are already interested in AI - so start pragmatically and document results to unlock broader support Vietnam Briefing survey on AI adoption in Vietnamese financial services.

Risk management and ethical AI in Vietnam's financial sector are no longer optional backstops but central business imperatives as regulators step up scrutiny: the State Bank of Vietnam will deploy monitoring measures to assess banks' compliance with Basel III standards and newer internal‑control rules, which raises the practical bar for any AI model used in credit, AML or liquidity forecasting (SBV Basel III monitoring guidance for bank risk management in Vietnam).

Banks face real operational constraints - higher capital targets (the CAR climb to about 10.5%), patchy industry data for Loss‑Given‑Default modeling, and gaps in IT systems - so model validation, industry data repositories for SMEs, and standardized stress scenarios become essential governance tools rather than academic exercises.

Corporate governance and legal capacity also matter: Vietnam's history of large internal frauds and a compliance‑first culture means legal teams must be empowered and resourced to review AI policies, while boards need clear audit trails and accountability for model decisions; independent legal and risk reviews are a practical hedge against reputational and criminal exposure (Financier Worldwide: legal risk management in Vietnam's banking sector).

The single memorable test: if an AI‑driven credit decision can't be explained to an exam‑ining regulator in plain Vietnamese within a business day, it's not ready for scale.

“This is one of the SBV's important orientations to improve governance efficiency, ensuring the safety of the banking system in the context that many new challenges are arising.”

Vietnam's financial services sector can treat 2025 as a launchpad: the AI market is now racing toward multi‑billion‑dollar scale and a clearer legal framework is turning regulatory uncertainty into practical opportunity, so banks and fintechs should move from pilots to governed pilots - pick one high‑value use case, map data needs, and test in the new sandbox under supervision while preparing compliance and labeling workflows ahead of the Digital Technology Industry (DTI) Law timetable (investment incentives begin 1 July 2025 and the law takes full effect 1 Jan 2026) - this approach converts policy momentum into safe, repeatable wins rather than risky experiments (see Vietnam's 2025 AI market outlook Invest Vietnam 2025 AI market outlook and practical legal incentives under the DTI Law Baker McKenzie Vietnam DTI Law summary).

Invest in local language models, verified eKYC and robust data governance, and build cross‑functional squads that pair product owners with compliance, data engineering and ML ops; for teams scaling fast, focused upskilling is the most pragmatic hedge - Nucamp's 15‑week AI Essentials for Work bootcamp teaches promptcraft and applied AI skills for non‑technical professionals and can shorten the time from idea to compliant pilot (Nucamp AI Essentials for Work bootcamp registration).

A smart final note: treat the sandbox and fiscal incentives as a practical runway - run a controlled pilot, measure accuracy/latency/auditability, document results, then scale.