Is Artificial Intelligence the future tool for anti-corruption?

The World Bank report suggests that the amount of goods and services that governments purchase to discharge their official business is a staggering $10 trillion per year – and is estimated at 10 to 25 percent of global GDP. Unless an effective public scrutiny mechanism is not in place, there are high chances of the money being lost to corruption. To address these issues, citizens are now demanding a more transparent mechanism to ascertain the process of government contracts. Corruption is like an octopus which has its tentacles dangling in every sphere of our society. It hurts the poor most as access to basic essential services and necessities like health, education, and nutrition is reduced.

The fight against corruption has taken a new dimension with Artificial Intelligence, a technology where its power can be harnessed to promote transparency in all aspects of government administration. Artificial Intelligence (AI) can be seen as an effective tool to combat corruption given its potential to handle big data. It is packed with the ability to detect patterns or anomalies, especially in a financial transaction. With systems and procedures riding on the wave of digitization, it presents a greater opportunity to leverage the data and red flag incidents which indicate corruption and other risks associated. A study carried out by the Higher School of Economics (HSE), and the University of Valladolid predicts that data analysis can detect corruption. In January last year, researchers from Valladolid, Spain, created an Artificial Intelligence system which can predict the risk of corruption in Spanish provinces and other variables associated with greater corruption such as the establishment of new companies, real estate tax, housing prices, the opening of bank branches and others.

Let us analyze the possibilities of artificial intelligence as a future tool for anti-corruption.

  • Corporations can implement artificial intelligence to design more effective and efficient internal compliance programs. Artificial intelligence can assist- through analysis of relevant laws and regulations- decision makers to make accurate decisions using past cases of compliance or non-compliance. The AI system has the ability to understand the context and content of regulations and learn to recognize the patterns with respect to compliance and non-compliance. This will help to identify risk areas which will allow corporations to build an individualized compliance program. In the case of subsequent revision, the same can be incorporated without any human intervention.



  • Just like Spanish researchers developed a tool to predict corruption, governments can use artificial intelligence systems to identify potent vulnerabilities, both by sector and geographic locations. This will enable governments to target their efforts and focus more on strict measures in possible risky areas. AI will also assist to identify loopholes with the national or regional regulatory framework and send out alerts when required.



  • Artificial Intelligence can assist in Anti-Money laundering contexts as well. This will help investigators by increasing the efficiency and accuracy of detection and due diligence. Artificial Intelligence technology also helps to reduce “false positives” in banks’ current transaction monitoring systems (TMS). A PWC industry survey states that 90% to 95% of all alerts are false positives as the traditional transaction monitoring systems are built on unsophisticated model extracting data from fairly broad/crude human-identified risk factors.



Although there have been questions and issues revolving around the ways artificial intelligence is applied in society, citing the risk of privacy and individual freedom as an important matter. But, the lack of transparency in governments and corporations around the world along with misappropriation of resources is widespread and causes a hindrance to economic development.  Artificial Intelligence has the potential to unearth the truth hiding amid thickets of data, and in so doing empower both public and private sector actors to fight corruption more effectively.