Corruption Perception Index (CPI) by Transparency International is the most widely used corruption index. And ironically, India has been constantly ranking only a few notches above the underdeveloped African countries. Corruption hinders the economic growth of a country preventing it from progressing in the right direction. Perhaps the legal procedure and laws have a narrow application for a diverse concept like corruption. Many a time it is highly impossible to differentiate between the so-called welfare measure from the very personal political agenda of the leaders. While financial and banking systems have been put under the scanner for corruption and fraudulent actors by global agencies like the world bank and IMF, corruption in other sectors is more than difficult to identify if not prevent. The organizational infrastructure cannot support the analysis of a vast amount of data and sift through it to connect the dots between different events to find malpractice.
Off late artificial intelligence is proving to be a savior of anti-corruption agencies world over. AI and machine learning, given that they can identify patterns in the data when applied to analyze inputs from different data points, could identify kinks from the mele of complex transactions. Automating public record searches can detect activities of corruption such as Money laundering, tax evasion, suspicious tenders, or bids in public procurements efficiently. However, until a few issues such as biased algorithms and data inadequacy are addressed, AI’s automated systems cannot be set free in the open to catch the thief, in spite of the benefits like objectivity, efficiency and the cost-savings it offers.
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