FISCAL Technologies offers a pure play cloud-based AI Procure-to-Pay risk management solution that enables modern finance teams to boost efficiency as well as derive useful insights that drive the best decision-making on behalf of the company.
Unlike traditional auditing and automation, which serve different purposes, FISCAL's risk management technology identifies high-risk anomalies before payment occurs by using artificial intelligence (AI) and machine learning techniques to forensically analyse each and every Accounts Payable transaction as it is processed.
This continuous preventative strategy means that working capital is protected for better use, recovery costs are avoided and the audit exercise is simplified. A triple-whammy that contributes to lower costs by addressing the issue of erroneous payments earlier in the process.
Since 2003, FISCAL's solutions have processed over 1 billion transactions with a value of over £5 trillion / $7 trillion in spend and are now relied on by leading private and public sector organisations all over the world.
Our proven solution can turn your AP, P2P or Shared Sevices Function from reactive to proactive, enabling you to:
- Prevents errors before financial impact
- Identify payment duplication
- Measure payment practices
- Identify high-risk anomalies for fraud
- Prevent supplier risk and financial loss
- Cleanse and maintain your Master Supplier file
- Identify regulatory (Sanctions, Payment & ESG) compliance issues
- Measure AP effectiveness
- Drives Procure to Pay Transformation
FISCAL Technologies is based in Reading and North Carolina, and is backed by leading investors including Octopus Investments and Calculus Capital.
Industry
Software Development, Banks & Financial Services
HQ Location
448 Basingstoke Road, Ground Floor
Reading, Berkshire RG2 0LP, GB
Keywords
Accounts Payable softwareRecovery auditAccounts Payable AuditAP Fraud and CompliancePurchase to Pay SoftwareFraud detectionFinancial Supply Chain analysisForensic AnalysisPrevent Invoice FraudSafeguard Profits