Reserve Bank of India to Leverage Data Analytics for Identification of Fraud Cases

The central bank of India, RBI has decided to encourage the use of data analytics to recognize fraud cases and manage the instant response and recovery actions to it. The move is a part of RBI's vision 2019-21 for payments and settlements in electronic space. Along with this, certain other measures are also included in the vision aiming at deepening digital payments and reduce the circulation of cash with time.

The central bank has set 4 goals of Vision 2021 which includes 36 peculiar actions over the time span of 36 months. These action points will usher in ease for the users and improve the efficiency of electronic/digital payments. The measures also include coordinating the turnaround time for solving customer complaints.

Major highlights/quotes from the Vision document:

•  "The RBI will be addressing the various facets in this regard, with the objective of optimal timelines expected to result in customer delight and certainty of the conclusion."

•  "Recourse to technology-driven dispute redressal mechanisms that are rule-based, transparent, customer-friendly and involve minimum (or no) manual intervention will be advocated/encouraged/appreciated."

•  RBI will also promote the adoption of digital payments through feature phones and offline payments.

•  "Consumer behavior has been driving the growth of digital payment systems as more and more consumers are embracing mobile technology. Though mobile internet speed has risen, connectivity issues remain unresolved in large areas. Therefore, providing an option of off-line payments through mobile devices for furthering the adoption of digital payments shall be a focus area during this vision period."

•  RBI will also function for designing a framework for gathering data on frauds in the payment system.

•  "To further strengthen the confidence in payment systems and minimize instances of frauds, there is a need to monitor the types of frauds that may be taking place in various payment systems. To this end, there is a need to share fraud-related data for payment systems. Such data can be used analytically for differentiating fraudulent and legitimate transactions; oversight and supervision, and also for providing guidelines to entities for minimizing risks of similar frauds."

•  "This would also help in improving resilience and trust in the system. The RBI would promote the use of such analytics to proactively identify instances and aspire for prediction of frauds to help instant response and recovery actions, such as blocking irregular transactions, before the payment authorization. The fraud data will be used to influence regulatory decisions and for reducing the incidence and level of frauds in the payments eco-space."