The image of the auditor sitting in front of a stack of spreadsheets, with a trusty calculator at the ready, is right out of central casting. So is the investigator on round-the-clock surveillance to uncover fraud or misuse of government funds.
Those techniques have their place, of course, but today’s audits and investigations rely heavily on data analytics and risk models. At the U.S. Postal Service Office of Inspector General (OIG), we have invested in building an analytical, evidence-based culture that depends on data to promote efficiency and effectiveness in government.
The analytic tools we use help our auditors and investigators identify the root cause of a problem and reduce the amount of time it takes to complete an investigation or audit. These tools also help us focus on areas with the highest risk, and thus the biggest payout. All of this significantly increases the return on investment of our work.
Four recently released audits highlight how we are using a tool known as risk models to identify financial anomalies by looking for specific behaviors and patterns that are strong indicators of improper activity. In particular, these risk models were looking for financial anomalies that occurred at field units.
The audits looked at the “internal controls” around various aspects of post offices’ operations, such as retail sales transactions or local purchases and payments, to make sure funds were not being wasted or misused.
For example, we audited the Pottstown, PA, Post Office after a risk model determined it had made about $38,000 in local purchases and payments using no-fee money orders in fiscal year 2016. The Postal Service’s preferred payment method for paying for goods and services is its electronic purchasing system. A no-fee money order, not to exceed $1,000, is actually the third option and only to be used as a one-time emergency.
The risk model helped us identify opportunities for the Postal Service to improve processes and implement internal controls to make sure all personnel use the preferred payment method for purchase.
The three other audits also found opportunities to strengthen internal controls. Two of the audits looked at variances in financial activities at particular post offices (the James A. Farley Station in New York City, and the Cardiss Collins Postal Store in Chicago.) The third focused on retail sales transactions at the Norman, OK, Main Office.
Have you used data analytics in your work? If so, how has it helped you? What data analytics do you think could be used to oversee Postal Service operations and performance?