Overpayments, duplicate payments, underpayments, payments made without substantiation are all too familiar topics in government sector dealings and transactions.
The growing call from the public and politicians to identify, report and mitigate or at least minimise the effects of waste, fraud and corruption, abuse and errors is reflected in stricter laws and regulations and sustained public outcry against such indiscretions.
Most business leaders, especially prime contractors to government, and civil servants recognise that these expectations to proactively deal with the scourge of fraud and corruption will likely lead to an increase in investigations with the purpose of recovering irregular payments. However, these stakeholders may not understand the extent to which they need to detect, respond and prevent fraudulent activity.
Rather than relying primarily on whistle-blowers and tips to unearth problems, it has become imperative for government and business alike to start using sophisticated analytics to identify and investigate irregular payments that have already been made. Some government institutions and businesses are beginning to use predictive analytics and near-real-time transaction monitoring tools to catch errors before payments are made.
These changes have implications for both prime suppliers/contractors and subcontractors/suppliers. Prime contractors/suppliers are generally subject to greater scrutiny into their use of subcontractors/ suppliers. The prime contractors/suppliers are responsible for irregular payments made to their subs, even if they are not aware of, or involved in, the irregular or fraudulent action/payment.
How can companies lessen the risk of becoming a national news story due to irregular payments caused by misdeeds of a subcontractor or its own employees? Also, from an internal operational efficiency perspective, how can they curb their own losses attributable to fraudulent payments?