Procure to Pay (P2P) is the process of requisitioning, purchasing, receiving, paying for and accounting for goods and services. This is one of the most complex and critical business processes that involves huge cash flows and often span across multiple systems, operations and geographies. Despite all the advanced technologies and automation engines, offered by numerous Enterprise Resource Planning (ERP) vendors, P2P remains an area highly prone to fraud, money leakage, and inefficiencies and thus posing great challenges to businesses in dealing with it.
Many countries in the world have strict laws and acts to suppress financial frauds and bribery including UK Bribery Act, Sarbanes-Oxley Act and North American Foreign Corrupt Practices Act etc. Government enacted these Acts in response to revelations of widespread bribery of foreign officials by national companies. These Act are intended to halt corrupt practices, create a level playing field for honest businesses, and restore public confidence in the integrity of the marketplace. To remain complaint with government laws, Companies are forced to take pro-active and re-active measures to detect corrupt practices and financial frauds, and report any suspicious or fraudulent activity to respective government agencies and thus companies are bound to perform an in-depth analysis of internal Accounts Payable controls.
Most of Enterprise Resource Planning (ERP) vendors offers highly flexible and robust internal controls to implement pro-active measures through preventive approach mechanism. There are some Data Warehouse (DWH) and Business Intelligence (BI) vendors that offers P2P KPI's through analytics solutions (re-active mechanism) and provides the visibility into entire life-cycle of a transaction from requisitions to vendor selection to the final invoice generation and payments with adjustments Although these offerings make business processes more stringent and reduces the possibility of frauds to a great deal, there implementation remains a biggest challenge as it requires very strong techno-functional skilled resources. Finding the Red Flags related to P2P transactions through automated process is still a long-way-to-go for business users.
With the advent of Artificial Intelligence (AI) and Big Data era, it became possible to process enormous amount of business data. Business focused applications using machine-learning algorithms made it possible to detect the trends and anomalies in the business data with great accuracy. P2PXAP is a next-in-line machine learning and cloud based product that detects and predicts exceptions and anomalies in procure to pay transactions by utilizing specialized AI based Machine Learning algorithms and a robust rule based engine. It offers businesses an effective and efficient way to generate areas of concern related to P2P transactions and helps businesses improve and reinvent their processes, enforcing accurate compliance reporting and driving efficiency.
Detect/Predict potential suspicious transactions, possible frauds and corrupt practices with high accuracy.
A highly Effective and Efficient way to identify process gaps that leads to improve and refine the Supply Chain P2P processes.
Potential cost savings through prevention of money leakage.
An Effective and automated method to meet government compliances reporting expectation like FCPA, SOX etc.
Specialized machine learning anomaly detection algorithms for each individual red flag.
Highly Secured Cloud Environment where Data Security and Confidentiality is maintained with supreme importance.