Banking automation
built for Nepal.
Manual reconciliation, slow regulatory reporting, and fraud detection that's hours behind the transaction. We automate the parts of banking operations that genuinely cost money.
Where Nepali banks lose the most operational time
From engagements with banks and fintechs across South Asia, the same three patterns waste the most operator hours:
- Manual reconciliation between core banking, payment gateways, NEPSE settlements, and internal ledgers. Often a daily multi-hour job done by a small team.
- Regulatory reporting for NRB — AML, BFI returns, large-cash reports — assembled by hand from queries against the core system.
- Fraud review happening after the chargeback window. Detection by exception report, not by real-time signal.
None of these require new core banking infrastructure to fix. They require a data and automation layer on top of what already exists.
What we typically build
- Real-time fraud detection — rules + ML scoring. We pull transactions as they happen, score against a model trained on your fraud history, and route high-risk cases to review.
- Regulatory reporting automation — NRB returns generated on schedule, with audit trails so any number can be drilled back to source transactions.
- Reconciliation engines — automated matching between core, payment gateways, and ledgers. Exceptions surfaced to a queue rather than buried in spreadsheets.
- Customer-intelligence dashboards — segmentation, lifecycle stage, churn risk, cross-sell signals. Powered by a data warehouse that updates daily.
- AI-assisted customer service — LLM-backed agents drafting responses to common queries, escalating complex cases to humans.
Integrating with existing core banking
We do not replace your core banking system. We integrate with whatever you have — Finacle, Flexcube, T24, Mambu, or in-house core — via APIs, file feeds, or direct database connections (read-only where required). The automation layer sits alongside, not in the critical transaction path.
Compliance and data residency
For Nepali banks we deploy to NRB-approved hosting (typically an in-country data center for production, with disaster recovery in Singapore or Mumbai). We implement role-based access, encrypted storage, full audit logging, and PCI-DSS controls where cardholder data is involved.
The data stack
For most banking engagements we deploy:
- Postgres for transactional storage of automation events.
- ClickHouse for sub-second analytics over billions of transactions — anomaly detection, customer segmentation, real-time dashboards.
- Apache Kafka for streaming transaction ingestion.
- Airflow + dbt for scheduled reporting jobs and the model layer.
- MLflow for fraud-model lifecycle management.
This pattern is the same operational data platform we use across sectors, adapted to banking compliance.
Implementation timeline
Banking automation engagements vary significantly by scope. Indicative timelines:
- Single reporting automation: 4–6 weeks.
- Fraud detection (rules + ML): 8–12 weeks.
- Full data warehouse + 3–5 automated reports: 12–20 weeks.
- Complete customer-intelligence platform: 16–24 weeks.
Questions about banking automation in Nepal.
Yes. We integrate with most core banking platforms via APIs, file feeds, or direct database connections — without replacing the core. We add a data and automation layer on top so it works with the systems you already operate.
Yes. We automate regulatory reports for Nepal Rastra Bank (NRB) — AML, BFI quarterly returns, large-cash transaction reports, and custom prudential reports — by pulling from your core banking data and applying the required calculations on a schedule.
We start with rule-based detection (velocity rules, geography rules, amount thresholds) which catches most fraud cheaply and explainably. We layer ML-based scoring on top for cases the rules miss. The model trains on your historical fraud cases and runs in real time against incoming transactions.
Yes when required. We design to PCI-DSS standards for any system handling cardholder data: tokenization, network segmentation, encrypted storage, audit logging. For systems handling only non-card data, we still apply equivalent controls.
Ready to automate banking operations?
Tell us about your bank and the current operational bottleneck. We respond within 24 hours.
[email protected]