With the number of digital-only ‘neobanks’ in the UK on the rise, the top four alone have over 12 million account holders between them, according to research by Insider Intelligence.
As a rapidly expanding niche, they represent a major shift in a traditional market, driven by the ubiquity of connected devices and a younger generation of customers who gravitate towards digitally-native services.
Operating without physical branch networks and complex legacy technology infrastructure, neobanks are considered by many to be the future of the industry. And while their emergence has done much to challenge the status quo, promote innovation and competition, they operate within a financial monitoring ecosystem that is still based on the assumption of a human-centric relationship between bank and customer.
With neobanks’ customer relationships defined by apps and APIs, this creates a particular set of challenges at a time when financial crime is becoming increasingly sophisticated and successful.
If that wasn’t enough, the integration of digital technologies and criminal strategies that exploit cybersecurity vulnerabilities is threatening to elevate issues such as fraud to a scale not seen before. The desire to acquire as many clients as possible via frictionless onboarding processes can often leave insufficient time for rigorous financial crime prevention methods.
Indeed, financial and cybercrime are becoming increasingly unified, as criminals look to exploit cybersecurity vulnerabilities to focus on everything from document and identity fraud to account takeovers and card crime.
Tags: Anti-Money Laundering/AML, Artificial Intelligence/AI, Banking, Challenger Bank, Cybersecurity, Data & Analytics, Financial Crime & Fraud, Innovation, Machine Learning Resistant AI BankingTech, FinTech Analysis, Industry Comment Worldwide
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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