AI features that improve every finance decision — without silently changing the money.
BancoOS runs on seven AI capabilities purpose-built for finance operations in Vietnam. Together they turn invoices, POs, contracts and ledger events into ranked recommendations — with the human always in the loop for anything that moves money.
The trust principle
AI improves the recommendations. It never silently changes the money. Every posting, payment or override still runs through your approvals, your policies and your audit trail.
Seven AI capabilities
OCR + LLM extraction across invoices, POs, GRs, contracts and bank statements. Handles Vietnamese, English and mixed-language documents.
invoice ↔ PO ↔ goods receipt matched with fuzzy logic, tax and FX tolerance, and line-level explanations.
8 deterministic signals (duplicate risk, price variance, vendor drift, GDT validity, MST format, tax code fit, budget fit, contract fit) scored on every document.
a live semantic layer over your ledger, AP, AR and cash so every agent and dashboard reads from the same numbers.
bilingual natural-language interface that drafts replies, resolves exceptions, and explains its reasoning in plain language.
recommendations tuned to CFO, controller, AP lead or analyst — the same data, framed for the decision each role owns.
every correction improves the model at three levels: this user, your organisation, and the global BancoOS network — with strict tenant isolation.
How a match happens
- Invoice arrives — Intelligent Capture extracts header, lines, tax and MST.
- Intelligence Engine scores the 8 signals and attaches confidence.
- AI 3-Way Matching finds the PO and GR, resolves fuzzy line matches.
- Copilot drafts the posting and, when needed, the vendor reply.
- Role-Aware Advisor routes to the right approver with a plain-language summary.
- Human approves — Hierarchical Learning records the outcome to sharpen the next match.
Interactive AI capability explorer
Matched to PO-24-1187 and GRN-88421 at 98% confidence; 1 line held for price variance.
Hierarchical learning
User learning fine-tunes to how you code, code, approve and reject. Org learning captures your vendor norms, policy exceptions and approval graph. Global learning improves capture accuracy across the network — never sharing your raw data.
What it delivers
- 90%+ touchless invoice rate on well-behaved vendors.
- 8 explainable signals on every document — no black-box scores.
- Bilingual EN + VI throughout, including Copilot and audit trail.
- Full audit log per action — model version, inputs, outputs, reviewer.
Vietnam AI finance case studies
3-way matching for high-volume FMCG invoices
Weekly deliveries from 120+ vendors reconciled against POs and goods receipts. AI 3-Way Matching flagged tax and MST mismatches before posting; Copilot drafted vendor replies in Vietnamese.
- Touchless rate
- 92%
- Cycle time
- -71%
- Duplicate loss avoided
- 218M VND / yr
GDT e-invoice validation at ingest
Every inbound e-invoice checked for GDT validity, MST format and price variance against contract before it ever touched the ledger. Exceptions routed to controllers with a plain-language reason.
- Invalid invoices caught
- 6.4%
- AP close
- 8 days → 2 days
- Auditor questions
- -58%
Role-Aware Copilot for portfolio review
CFO, credit and ops each get a Copilot lens on the same book. Weekly exec digest surfaces vendor drift, overdue reconciliations and cash concentration — bilingual, one click to source documents.
- Time to weekly close
- -64%
- Exceptions per FTE
- 3× throughput
- CFO self-serve queries
- 180 / week
Security, compliance & data handling
Every AI feature is built on four operating commitments: strict tenant isolation, human-in-the-loop, full audit logging, and no foundation-model training on customer data.
- Tenant isolationRow-level security per org
- No model training on your dataFoundation models stay frozen
- Human-in-the-loopAI never posts or pays alone
- Full audit logModel, prompt, inputs, outputs, reviewer
- GDT & SBV alignedVietnam invoice + reporting rules
- Architecture readyISO 27001 / SOC 2 controls path
Where is our data stored?+
In-region (Singapore or Vietnam) on isolated tenants. No cross-tenant reads, ever. Backups are encrypted at rest with per-tenant keys.
Do you train foundation models on our invoices?+
No. Foundation models stay frozen. Learning happens in a platform layer scoped to your user, your organisation, or aggregated + anonymised network patterns — never raw invoices, ledger rows or PII.
Who can see AI decisions and prompts?+
Only users with the right role in your tenant. Every AI action is logged with model version, prompt, tool calls, inputs, outputs, confidence and reviewer — exportable for internal audit, GDT and SBV.
What happens if the AI is wrong?+
AI drafts and recommends; humans approve. Wrong recommendations are corrected in the review UI, feed hierarchical learning, and never bypass your approval matrix.
Download the AI features brief
Frequently asked questions
›Does AI ever move money on its own?
No. AI ranks, drafts and recommends. Postings, payments and overrides always pass through your approval chain and audit trail.
›What are the 8 signals in the Intelligence Engine?
Duplicate risk, price variance, vendor drift, GDT validity, MST format check, tax-code fit, budget fit and contract fit — each scored deterministically per document.
›How does hierarchical learning protect our data?
User and org learning stay inside your tenant. Global learning uses only aggregated, anonymised patterns — never raw invoices, ledger rows or PII.
›Which languages are supported?
Vietnamese and English across capture, Copilot and reporting, including mixed-language documents typical in Vietnam.
›Do we need to change our ERP?
No. BancoOS layers on top of MISA, Business Central, SAP, Oracle and others via typed connectors.
›How are AI decisions audited?
Every action logs the model version, prompt, tool calls, inputs, outputs, confidence and reviewer — exportable for SBV, GDT and internal audit.
›Can the Copilot answer in Vietnamese?
Yes. Copilot is fully bilingual and preserves the source language when quoting invoices, contracts or ledger entries.
›Is customer data used to train foundation models?
No. We do not train foundation models on customer data. Learning happens inside the platform layer with strict tenant isolation.
›How long to see value?
Typical customers see touchless rates and Copilot resolution improve within the first 30 days as user learning kicks in.
›Can we build our own signals or agents on top?
Yes. The Intelligence Engine and Agent SDK are extensible — teams add domain signals without forking the platform.