A data-driven approach can serve as an efficient and expedited starting point for agencies to identify and investigate fraud.
Local governments can and should begin to use data more often in order to root out and eliminate corruption, a new study has found.
The study, Taking a Byte Out of Corruption, emphasized that while major advancements in data analytics have given law enforcement agencies and policymakers new tools that could potentially fight public corruption, a lot of work remains before systems are established to ensure such data is used fairly and effectively. In the report, the authors speak often of this being a starting point for municipalities that want to bridge this gap.
The study, the result of a yearlong effort, was conducted by the Center for the Advancement of Public Integrity (CAPI) Data Analytics Working Group at Columbia Law School in New York City, and support for it was provided by the Laura and John Arnold Foundation. It involved working with a group of leading practitioners, scholars, engineers and civil society members, and Jennifer Rodgers, executive director of CAPI, said such research into data’s potential to fight corruption is a relatively new arena.
“Unfortunately, there’s still a way to go before cities are really going to be in a position to do this in a meaningful and broad-based way,” Rodgers said. “It’s a bit at its beginning, but there have been such successes in other areas of city management using data, and corruption-fighting is going to be one of the next frontiers, we think.”
The report, of course, is detailed and annotated, but broadly speaking it points to nine types of fraud that data can potentially help investigators identify, a list that includes transgressions as minor as HR violations like manipulating a time card to larger malfeasance such as fraud or corruption by elected officials at high levels.
For each sort of fraud, the report gives examples of how data might be used to combat it. For example, with corrupt inspectors, the study suggests that keeping a database of incidences can help spot outliers, such as individuals giving excessively high or low numbers of violations, or logging passing grades too soon after failures, which might be an indicator of fraud.
Rodgers said a data-driven approach to fraud investigation can also benefit existing watchdog agencies, even if they’re doing good work, such as the offices of the inspector generals that operate in both New York City and Chicago. New York, for example, has 45 city agencies that employ more than 300,000 people, with one anti-corruption office to oversee them all.
Throughout the report the authors are careful to note that data is not going to be a magical cure for corruption, nor will it be able to identify fraud beyond a doubt. Data, if kept and cleaned properly, is simply a tool that can point investigations and watchdogs in the right direction, improving both efficiency and the frequency at which wrong-doing is identified.
Gabriel Kuris, deputy director of CAPI, said another point the report seeks to stress is that data as a corruption-fighting tool can create a permanent system of checks, rooting out systematic issues, but, again, for most city governments this sort of work remains in the future.
“This is truly the first iteration of this,” Kuris said. “We really hope to improve it over time, and we certainly welcome any feedback. And any government that is working on this stuff that wants to share with us their efforts, we’d like to partner.”