Cybersécurité

What makes Indian fintech fast and furious, but also a little fraudulent?

First, Paytm was asked to freeze its banking business, a crackdown so severe that India’s pioneering digital payments firm bled out nearly 60 per cent of its market value in two weeks. Then came the regulatory diktat to Visa Inc. The network was told to halt the use of its business cards for commercial payments where a fintech is in the middle. And now, media reports suggest that more nonbank intermediaries may expect a rap on the knuckles. Just what has made the Reserve Bank of India so cranky all of a sudden?

The answer to that question may lie in the cloud. Or, to be more precise, in cloud computing.
The growth of neo-banking is courtesy of Amazon Web Services, which has allowed the world’s most-populous nation to move very large numbers of small payments instantaneously. However, fast and furious has also created more room for fraud in a country where documentation has always been patchy. Even “Aadhaar,” the biometrics-based unique number and card through which Indians are supposed to establish who they are, is not to be relied upon as proof of date of birth, the manager of the world’s largest identity project said recently.
Know-your-customer, or KYC, regulations aren’t easy anywhere. But fintech adoption in India has done more than just open the floodgates to financial inclusion. The cloud has added complexity — and risk — to the landscape. Three years ago, Sunny Leone, a Bollywood actress, was scammed by someone using only her name and her tax identity number to take out a $27 ghost loan that ended up spoiling her credit score. All other data, including her address, phone number, email, date of birth and bank account, were fake, according to a report by The Ken, a news website.

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

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