Overview

VaultFlow is an automated cash reconciliation platform built by Bacancy Technology for banks, cash-in-transit operators, and retail networks handling physical cash. It helps teams schedule cash replenishment based on demand, automates reconciliation, directs discrepancies into a claims procedure, and unifies bank statements, machine activity, and cash counts into a single view.

Technologies Used

.NET
C#
Microsoft Azure
Microsoft SQL Server
.NET MAUI
Jira

Project Highlights

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Reconciliation engine matching bank statements, machine logs, and physical counts with configurable one-to-one and many-to-many rules

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OCR reads denominations straight off counter slips and photos, removing manual count entry entirely from the process

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Demand forecasting per machine, with route scheduling that accounts for holidays and one-off local events and demand spikes

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Dedicated Azure environment per customer, with each login automatically scoped to its own organization's data

The Challenges

1

Cash moving through ATMs, CDMs, recycling machines, and vaults was tracked in different places, making it difficult to reconcile bank statements, machine logs, and physical counts from one shared view.

2

Physical counts came in as paper slips or counter photos, so someone had to enter the figures manually. It was slow work, and even a small denomination entry error could make its way into the records.

3

Without forecasting behind the refill schedule, machines either ran dry or sat overloaded, and collection routes ignored holidays and one-off events, so runs were regularly missed or wasted entirely.

4

Discrepancies had no formal home, so chasing a mismatch meant digging through spreadsheets, and the commission owed to partner banks was calculated manually, differently for each customer.

Solutions by Bacancy

1

With experience delivering reliable fintech web development services, our developer built a reconciliation engine using adjustable one-to-one and many-to-many rules to match bank statements, machine logs, and physical counts. Mismatches appeared immediately as the algorithm checked all sources in one pass.

2

Counter slips and photos no longer had to be entered manually. Our fintech AI development approach used OCR to read the denominations from the images and add them to the count record, cutting out the manual step that slowed down physical counts and could result in mistyped figures reaching reconciliation.

3

Historical cash and machine activity fed a forecasting model that predicted demand at each machine, while route scheduling accounted for holidays and one-off events when planning each run. Field agents access routes and updates through a .NET MAUI mobile app, so refill decisions reach the ground in real time instead of guesswork driving the schedule.

4

Every mismatch opened a claim that tracked through to resolution, and commission was coded against configurable bands for ATM, retail, collections, and vault holdings. Invoicing followed the same process for every customer, built with the same attention to detail our developers bring to complex fintech systems.

Core Features

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Automated reconciliation across bank statements, machine logs, and physical counts

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OCR-based denomination capture directly from counter slips and photos in real time

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Demand forecasting and holiday-aware route scheduling per machine for each run

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Discrepancy claims tracking with configurable commission and invoicing bands

No. of Resource

1

No. of Resource

Time Frame

November 2025 - July 2026

Time Frame

Project Snapshot

Automated Cash Reconciliation Platform

Outcomes

Unified cash reconciliation across ATMs, CDMs, and vaults

Cut manual count entry by 85% with OCR capture

Reduced machine dry-outs by 60% through demand forecasting

Automated commission invoicing across 4 configurable band types

Routed 98% of discrepancies into a tracked claims process

Gave field agents full route access via mobile app

Technical Stack

Backend .NETC#
Database SQL Server
Cloud Infrastructure Microsoft Azure
Storage Azure Blob Storage
Data Extraction OCR
Forecasting Statistical Forecasting
Reconciliatio Rule-Based Matching
Access Control Multi-Tenant Architecture
Notifications Azure Notification Services
Mobile .NET MAUI
Testing Automated Testing
Project Management Jira

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