How AI Is Helping Financial Services Companies in Viet Nam Cut Costs and Improve Efficiency

Vietnam's financial sector is in the fast lane: a young, tech‑savvy population with over 80% smartphone penetration and booming mobile payments is pushing banks and fintechs to adopt AI to cut costs and boost speed, from automated onboarding and fraud detection to generative‑AI chatbots that deliver 24/7 service.

Market research points to a growing AI industry (USD 554M in 2023) and a cloud investment surge that supports large deployments, while digital banking revenue is poised to top $1B as e‑wallets and fintechs expand financial inclusion - yet legacy cores and data governance remain hurdles.

Smart adopters like VPBank and Techcombank are proving the business case for AI, and industry guides on digital banking transformation in Vietnam explain why governance, talent and modern platforms are the prerequisites for scaling impact (see GFT's analysis and Vietnam's generative AI coverage for examples and numbers).

“Generative AI transforms the landscape by providing immediate, game-changing solutions. This doesn't mean that staff will no longer be needed. Instead, their roles will evolve…” - Augustine Wong, VPBank (VNS)

AI adoption in Việt Nam's financial services is moving from pilots to production as banks and fintechs lean on cloud, data and generative models to automate onboarding, personalise offers and spot fraud in real time: with over 80% smartphone penetration and mobile payment transactions “doubling every year,” digital banking revenue is set to top $1 billion and institutions are racing to scale AI use cases from chatbots to eKYC (see GFT's analysis).

Local leaders like VPBank and Techcombank are rolling out generative‑AI assistants and internal copilots while market data point to a fast‑growing AI sector (market outlooks value Vietnam's AI market in the high hundreds of millions USD).

Adoption momentum is broad - surveys show roughly nine in ten banks are actively pursuing AI opportunities - but success hinges on clean, secure data, cloud platforms and targeted reskilling rather than technology alone, a point echoed across industry commentary and government programmes that aim to balance innovation with governance and cybersecurity (read more in Vietnam News and the market outlook).

The result: quicker loan decisions, 24/7 virtual support that reduces late‑night call‑backs, and a real chance to expand services to SMEs and underserved customers if institutions pair ambition with disciplined implementation.

Metric	Value / Source
Smartphone penetration	Over 80% - GFT
E‑wallet users	89% (Visa survey) - Vietnam News
Digital banking revenue (forecast)	Set to top US$1B - GFT
AI market value (2024)	US$753.4M - Nexdigm
Public cloud spend (2024)	US$803M - Vietnam News / IDC
Institutions eyeing AI	~94% - WFIS / Finastra

“In the global context, AI is becoming a fundamental technology, having a profound impact on all fields, including finance and banking.” - Dr Nguyễn Quốc Hùng, Vietnam Banks Association (Vietnam News)

Core AI use cases in Vietnam's banks and fintechs cluster around customer-facing automation, identity and risk, and back‑office streamlining - each delivering measurable time and cost savings.

Conversational AI and NLP‑powered chatbots are already mainstream for 24/7 query handling and personalised offers (about 41% of institutions use NLP to tailor marketing), boosting young‑user satisfaction and reducing routine contact volumes; see the Vietnam Briefing survey for details.

Onboarding and eKYC are moving to AI biometrics: TPBank's facial‑recognition program evaluates 128 criteria to identify customers, while VietinBank's FaceID kiosks cut transaction processing time by ~30%.

Fraud detection and predictive analytics tie those threads together, spotting anomalies across large datasets so teams can intervene faster. Meanwhile, document automation and legacy modernisation trim onboarding cycles and lower maintenance overheads - a practical lever for banks scaling digital services in a market where AI customer‑service spend is expanding rapidly (projected to grow from about US$4.8B in 2025 to US$19.6B by 2031).

For institutions charting priorities, investing in robust chatbot development, eKYC accuracy and tidy document workflows turns AI from a headline into concrete cost reduction - imagine shaving days off manual verifications and replacing stacks of paper with instant, auditable decisions.

Use case	Impact / metric (source)
Chatbots / NLP	41% use NLP for personalised marketing; improves youth satisfaction (Vietnam Briefing / JCLI)
eKYC / Facial recognition	TPBank: 128 biometric criteria; VietinBank FaceID: ~30% faster transactions (Vietnam Briefing)
Document automation & legacy modernisation	Reduces onboarding time and lowers maintenance costs (Nucamp Bootcamp)
Customer‑service AI market	Projected from US$4.8B (2025) to US$19.6B (2031) in Vietnam (MobilityForesights)

Read more on AI chatbot implementation in Vietnam and how document automation accelerates onboarding.

AI is already translating into hard savings and faster operations across Việt Nam's financial sector: national modelling pegs automation and predictive analytics as delivering US$60–75 billion in cost savings as the AI economy scales (Tuoi Tre national AI report for Vietnam), while finance alone could capture roughly US$10–15 billion of that value; in practical terms, banks are using RPA, eKYC and real‑time fraud models to turn slow, paper‑heavy workflows into near‑instant decisions.

Local case studies show the impact - facial recognition and kiosks trim transaction times by about 30% at some banks, and outsourced accounting partners report up to a 40% drop in manual workload within months after deploying AI tools (Bestarion case study on AI in banking).

Conversational AI and NLP adoption (roughly 41% of institutions) cut contact volumes and let teams focus on complex cases, while cloud and data‑center expansion gives scale and predictability to these deployments; the result is not just lower costs but faster customer journeys - imagine a loan queue that used to stretch days being resolved in a blink.

Metric	Value / Source
National cost savings from automation	US$60–75B - Tuoi Tre national AI report
AI contribution: financial services	US$10–15B - Tuoi Tre national AI report
Manual workload reduction after AI adoption	Up to 40% in months - Bestarion case study on AI in banking
FaceID / transaction time improvement	~30% faster - Vietnam Briefing analysis (Finastra)
NLP adoption for marketing	41% of institutions - Vietnam Briefing report on NLP adoption

At the technical heart of Vietnam's financial AI movement sits machine learning - the dominant approach identified by UEH - with a toolbox that ranges from artificial neural networks and support vector machines to random forests, clustering, LASSO and evolutionary algorithms, plus NLP for text and voice data; each method maps to concrete finance problems like profit/risk forecasting, asset classification, portfolio optimisation and automated information extraction from news and social media (see UEH research on AI technology trends in Vietnam).

While adoption in asset management, risk management and robo‑advice is still emerging rather than universal, these methods already enable models that capture nonlinear market behaviour (ANNs and SVMs outperform classic GARCH in some volatility tasks) and support automated advisors that rebalance portfolios and reduce behavioural bias.

Practical deployments rely not only on algorithms but on modernised document workflows and legacy‑system lifts to feed clean data into models - a point explored in practical guides on document automation and legacy modernisation - and the payoff is tangible: faster, more auditable decisions and scalable advisory services that can reach more customers without ballooning headcount.

Technique	Common application (UEH)
Artificial Neural Network (ANN)	Profit/risk forecasting; portfolio optimisation
Random Forest	Asset classification and return/risk forecasting
Support Vector Machine (SVM)	Return/risk forecasting; volatility prediction
Cluster Analysis	Grouping investment assets
Evolutionary Algorithm	Portfolio optimisation under complex constraints
LASSO Regression	Feature selection for improved out-of-sample forecasts
Natural Language Processing (NLP)	Extracting business intelligence from reports and media

Deployment activity in Việt Nam already reads like a playbook: Vietcombank's VCB Digibot, built on FPT Smart Cloud's FPT.AI platform, handled over 2 million interactions in its first six months and now manages roughly 88% of user queries - more than 50,000 customers and about 350,000 interactions each month - freeing contact‑centre teams to focus on complex cases and reducing routine volumes (see the VCB Digibot case study).

Local systems are complemented by specialised vendors and techniques: chatbot integrators and consultancies (TPBank and Vietcombank are cited as live deployments) are pairing Vietnamese‑language NLP with core‑banking APIs, while transfer‑learning approaches showcased by BytePlus speed model reuse for fraud detection, risk scoring and customer‑service automation across banks like Techcombank and BIDV. The result is a maturing vendor ecosystem - platforms, cloud partners and boutique AI firms - delivering measurable scale (multi‑channel chatbots, real‑time fraud models and transfer‑learning pipelines) so banks can turn pilots into production without rebuilding everything from scratch.

“With a leading market position in terms of customer scale, particularly among those transacting through digital channels, diversifying and improving the effectiveness of our support channels has been a challenge we have deliberated over for years. The trend of deploying chatbots and AI has presented a valuable solution, and we quickly adopted it. Although we have achieved initial success, we remain committed to developing VCB Digibot into a fully intelligent virtual assistant capable of providing multi-channel support. We hope customers will continue to embrace VCB Digibot as their 24/7 companion in utilizing the bank's services.” - Nguyen Thi Kim Oanh, Deputy General Director of Vietcombank

AI is becoming a practical lever for financial inclusion in Việt Nam: by using non‑traditional data and automated underwriting, AI‑driven micro‑lending and personalised mobile services can reach thin‑file customers and rural smallholders who were previously excluded, turning lengthy paperwork into near‑instant decisions and tailored offers that land on a customer's phone; this is the core promise highlighted in Bestarion's overview of AI banking in Vietnam, which lists improved financial inclusion and cost efficiency as direct benefits.

That promise is backed by national-scale investment and policy - Vietnam's AI market (US$753.4M in 2024) and the National Data Development Fund (NDDF, initial capitalization US$38.4B) signal a real market opportunity and the infrastructure to scale localized models and datasets.

On the ground, banks are already translating tools into reach: HDBank's digital‑first, AI‑driven SME lending ecosystem served over 60,000 SMEs, showing how targeted AI products can expand credit access while controlling risk - imagine a micro‑loan approved in minutes on a remote entrepreneur's smartphone rather than after weeks of paperwork, a vivid shortcut from exclusion to participation.

Metric / Example	Value / Source
Vietnam AI market (2024)	US$753.4M - InvestVietnam
National Data Development Fund (NDDF)	Initial capitalization US$38.4B - InvestVietnam
HDBank AI SME lending reach	Served over 60,000 SMEs - The Asian Banker

Scaling AI in Việt Nam's financial sector promises big efficiency gains but hinges on confronting a tight knot of risks and prerequisites: poor data quality and high annotation costs slow model rollout, with data work consuming as much as 80% of development time (see research on data quality and labeling costs), while a severe talent gap - only about 1,000 graduates with deep AI skills and fewer than 300 “true” experts - creates hiring and retention pressure that inflates wages and delays projects.

Dependence on rented GPUs and foreign cloud suppliers raises costs and sovereignty questions, and the legal landscape remains nascent: personal data protections and sectoral guidance are still being strengthened even as the DTI Law moves toward formalisation (see updates on the DTI Law), so banks must pair tech pilots with rigorous data governance, privacy-compliant pipelines, model explainability and targeted reskilling programs.

Practical prerequisites therefore include clean, well-labelled data stores, dedicated compute budgets (or local cloud alternatives), clear compliance roadmaps, and vendor partnerships that transfer know‑how - otherwise pilots risk stalling or creating opaque, non‑auditable systems that undermine trust instead of saving costs.

Risk / prerequisite	Metric / source
Data processing time	Up to 80% of AI development time - Rikkeisoft
AI talent depth	~1,000 with in‑depth AI skills; <300 top experts - VNEconomy
Compute dependency	Rent GPUs / cloud from foreign providers; limited domestic supercomputers - VNEconomy
Regulatory status	Specialised AI rules nascent; DTI Law nearing implementation - Lexology

“An AI product is a synthesis of many different materials, and data is one of the essential components. According to statistics, up to 80% of AI product development time is spent on data-related processing.” - Nguyen Minh Tan, Vice Managing Director of Rikkei AI (Rikkeisoft)

Vietnam's new regulatory architecture is moving from intent to action, and the message for banks and fintechs is clear: use the State Bank's sandbox as a disciplined runway to scale AI safely.

Decree 94/2025 (effective 1 July 2025) sets a transparent, supervised path for pilots in credit scoring, open APIs and P2P lending - complete with application dossiers, reporting regimes and strict operational limits - while recent commentary and analysis explain how sandboxes balance consumer protection with faster innovation; see the official Decree 94/2025 summary and an independent regulatory sandbox review.

Firms should design experiments that meet the Decree's infrastructure and data rules (IT systems and backups hosted inside Vietnam for certain P2P pilots), embed NCIC reporting and incident notifications from day one, and treat the maximum two‑year testing window (with extensions) as a chance to prove measurable customer benefit without running afoul of licensing rules; think of it as a time‑boxed lab where models are stress‑tested against real oversight rather than deployed into darkness.

Engaging early with the SBV, documenting risk‑management plans and aligning pilots to financial‑inclusion goals will speed transition from sandbox to scaled product while preserving trust in a rapidly evolving market.

Policy item	Key facts / source
Decree 94/2025 adoption & effective date	Adopted 29 Apr 2025; in force 1 Jul 2025 - LuatVietnam / DigitalPolicyAlert
Eligible sandbox solutions	Credit scoring; Open API data sharing; P2P lending - Decree 94
Testing period	Maximum 2 years (extensions permitted); formal reporting and supervision required - Decree 94

“The official launch of the Regulatory Sandbox Decree is a milestone in Việt Nam's journey towards digital financial transformation, and a shining example of what strong partnerships and shared vision can accomplish.” - Thomas Gass, Swiss Ambassador (Vietnam News)

A practical roadmap for Vietnamese banks must start with a tight business case and strong C‑level sponsorship, then move quickly to build the plumbing - clean, interoperable data stores, a clear cloud strategy and modular APIs - so pilots don't stall on legacy debt; GFT's playbook stresses governance, cost strategy and customer‑centric design as non‑negotiables (GFT guidance on digital banking in Vietnam).

Prioritise high‑value, low‑risk proofs of concept (chatbots, eKYC and real‑time fraud models), choose cloud or hybrid deployment with IP and data sovereignty in mind, and use Vietnam's regulatory sandbox to run time‑boxed experiments that meet Decree and reporting rules (see Vietnam Briefing analysis of Vietnam's AI regulatory framework and sandbox opportunities).

Pair each pilot with a measurement plan (cost‑to‑serve, speed, false‑positive rates), an agile operating model to iterate rapidly (Techcombank's “Techcomway” is an example of local scaling), and a reskilling programme so staff shift to higher‑value, relationship work; the payoff is tangible - imagine a loan queue that once took days being closed in minutes as models and workflows are proven and then scaled with vetted vendors and documented governance.

For hands‑on implementation details and compliance checklists, follow cloud/on‑premises decision steps recommended by practitioners.

Phase	Key actions	Representative source
Plan	Business case, governance, talent map	GFT
Build	Data lakes, cloud/hybrid choice, modular APIs	Adnovum / Vietnam Briefing
Test	Sandbox pilots (eKYC, chatbots, fraud) with KPIs	Decree 94 / Vietnam Briefing
Scale	Measure ROI, vendor handoffs, reskilling and ops maturity	GFT / Saigon Technology

“Agile is the ‘superglue' that brings all components together: platforms, digital, data, and talent.” - Vu Tung Lam, Head of Agile, Techcombank (VnEconomy)

Vietnamese financial leaders closing this report should convert momentum into disciplined action: pick two high‑impact pilots (chatbots, eKYC, AML triage) with clear KPIs, run them in the SBV sandbox, and bake governance, security and human‑in‑the‑loop checks into every release - exactly the operational controls ABeam recommends when moving generative AI from experiment to production ABeam generative AI implementation checklist.

Learn from local proof points: Cake Digital Bank paired Vertex AI and cloud scale to reach millions of customers and cut decision times to roughly two minutes for some credit approvals, showing what measured, cloud‑native ops can deliver Cake Digital Bank Vertex AI case study.

Treat data work and multilingual knowledge bases as first‑class deliverables, use RAG and review loops to prevent hallucinations, measure cost‑to‑serve and false‑positive rates, and run concurrent reskilling so staff shift to high‑value, relationship work - training such as Nucamp's AI Essentials for Work bootcamp can accelerate that transition Nucamp AI Essentials for Work bootcamp.

The prize is concrete: faster customer journeys, lower operating costs, and wider inclusion - if pilots are time‑boxed, governed and measured from day one.

“Our mission is to propel the digital finance future of Vietnam to popularize and facilitate people's access to financial solutions in a smart and easy way.” - Tu The Hien, CTO, Cake Digital Bank