Industries
The most data-rich industry, and the most tightly constrained. BigAI deploys so that customer data never leaves the bank, every model is explainable, and every number traces back to its source.
Context
The barriers BigAI encounters repeatedly across companies in this sector.
For banks, BigAI almost always recommends starting with the data layer rather than the model. The reason is simple: the highest-value AI use cases in the sector — credit scoring, fraud detection, churn prediction — all depend on data consolidated across systems. Without that layer, every model stops at the pilot stage.
Core banking, cards, lending, treasury, CRM and acquired platforms — each with its own data model and refresh cycle.
Central bank filings, IFRS 9 reporting and ad-hoc requests all demand consistent, verifiable numbers on deadline.
Customer data cannot leave the bank; every access must be logged and defensible under audit.
A declined application needs a stated reason. Black-box models do not clear risk approval.
Applications
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| Business problem | BigAI solution | Measurable benefit |
|---|---|---|
| Slow financial close and reporting<br><span class="small muted">Manual reconciliation across systems</span> | Central lakehouse, automated reconciliation pipelines, certified metric set | −42% close cycle down to 7 days |
| Credit scoring locked to hard rules<br><span class="small muted">Good customers outside the template get rejected</span> | Scorecard plus explainable ML with SHAP, wired into the approval flow | +15% approval rate at the same risk level |
| Fraud detected after the fact<br><span class="small muted">Batch review, slow discovery</span> | Real-time transaction risk scoring on a streaming platform | −31% detection under 300 ms, 31% lower losses |
| Account opening takes too long<br><span class="small muted">Manual data entry and document checks</span> | eKYC with Vietnamese ID OCR, face matching and liveness detection | 3 min account opening in 3 minutes |
Case studies
From 14 disconnected sources and manual reconciliation to a single governed lakehouse serving both regulatory reporting and internal analytics.
Read case studyCompliance
Everything runs on-premise or on cloud infrastructure located in Vietnam, aligned with Decree 13/2023 on personal data protection.
Every data access and every model decision is recorded and exportable for internal audit and regulators.
Model documentation, feature attribution analysis and bias testing — a package fit for committee review.
A BigAI solution engineer will review your current data estate with you, identify the highest-value problem to solve and sketch a realistic roadmap. No commitment.