Financial monitoring in a mining operation is as complex as the stages of operating one as it involves substantial capital expenditure with revenue dependent on several dynamic factors such as production level, the value of ores and assets, cost of mining and milling, and transportation requirements.

Mining companies have multiple transactions ranging from grading ore, the prices received for metals, costs per ton for mining and milling, costs per foot for development, upward or downward tendencies in costs, ore settled or in transit, cash on hand, stocks of supplies on hand, and labor costs. With most costs and values dynamic, they are in a critical position to put in place modern transaction monitoring to avoid fraud, better manage costs, and improve revenue.

Large individual transaction volumes and the permeation of fraud and processing errors demand secure, scalable solutions, able to handle growing transaction data estates, and the need for unprecedented levels of monitoring and testing.

Modern mining transaction analytics augments the CFOs operations with super-human memory, processing power, and insights to generate timely, consistent, deliberate, and reliable analytics for a greater chance of success. Monitoring can be run off-site (for separation of duties) or deployed internally to trusted teams.

Automatically Test Big Data with Ease

High ROI, Low Investment, Quick Wins

• Organisations typically lose between 0.5% and 2% of their accounts payable due to financial leakage and fraud.
• Automated processes that can be run externally or deployed internally at a low cost and with minimal internal involvement.

Ingest, Compute, Transform, Store & Consume

• Analyse large data sets including accounts payable, payroll, superannuation, employee expenses, supplier data and more.
• Validate against external data including ASIC, ABR and ATO.
• Pay for compute and storage only when you use it through cloud deployment and resource automation.
• Fully managed cloud-based platforms and security.
• Data science, machine learning and artificial intelligence to be real-time and autonomous around transaction analytics.

Some Examples of the Tests We Conduct

• Missing Vendors in Master File, Ghost Employees and Suppliers.
• Remittances, settlement sheet from buyers, cash and voucher records, shipment books.
• Records of mine weights and assays, schedule of prices, bills of lading, contract of carriage .
• Invoices on weekends, outside work hours, rounded invoices, duplicated or overpaid (or underpaid) invoices, foreign high-risk invoices, and those outside Benford’s Law tolerances.
• TFN or ABN failing ATO checksum, repeated or consecutive characters, incorrect lengths and containing alpha.

Outcomes of doing Mining Transaction Analytics

• Analyse all your data; not just sample testing.
• Highlighting recoverable savings including duplicate invoices and financial leakage through fraud, overpayments, GST, etc.
• Automated alerts and monitoring when solution is deployed.
• Handle large volumes of data with scalability & performance.
• Perform super-human levels of analysis and decision making.
• Identify areas for controls, training and process improvement.
• Identify potential fraud (ghost employees, fictitious entities, conflict of interest, invoice splitting and more) whilst using a third party to eliminate the risk of internal data manipulation.
• Supplier rationalisation and analysis.
• Verification of entitlements including super and leave.