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AI’s Role in the Battle Against Cyber-Attacks

Xena Lappin, EVP Transformation and Innovation at Teleperformance, discusses the expanding threat landscape in this new world of dispersed business operations, and how Artificial Intelligence is helping financial services build a frontline for cybercrime prevention.

Posted: 30th November 2020 by Katina Hristova
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The world’s biggest work-at-home experiment has now shifted into a more permanent structural change, leaving companies grappling with the next operational challenge – intensifying cybercrime. Prior to the pandemic, businesses typically over-relied on in-office cybersecurity systems to protect data, because they rarely had to worry about threats to data outside of the workplace. Fast forward to March 2020, and companies had to quickly recalibrate their entire operations or face their business model being rendered redundant. Since the crisis took hold, approximately 90% of banking and insurance workers worldwide transitioned to a work-at-home set-up[1], the majority of whom are accessing corporate and customer data online on insecure devices.

The scope for cybercriminals to exploit the vulnerabilities of remote technologies to commit financial crimes has increased exponentially for customers being onboarded, and having their financial matters dealt with online. While safeguarding customers remains at the top of the corporate agenda, providing a seamless, omnichannel digital experience cannot be compromised. In this fast-evolving FinTech landscape, financial services must seek to leverage technology that can meet both increasing expectations for an elevated customer experience, whilst fighting internal and external cybercrime. The industry has an important opportunity to leverage Artificial Intelligence (AI) solutions, used in the front-office, to prevent and react to threats, potentially saving billions in lost funds – not to mention protecting brand reputation.

Fast-evolving threat landscape

According to a recent report, the financial services sector fell victim to over half (51%) of all opportunistic cyber-attacks during the crisis[2]. Fraudsters have been launching sophisticated attacks to impersonate financial organisations, by luring in customers with fake emails or phone calls offering financial assistance, only to extract customer data. In fact, impersonation scam cases in the UK were up a staggering 84% in the first half of the year compared to the same period last year[3].

As financial services companies expand their omnichannel offerings, to meet the demand for real-time access to services, so too does the opportunity for potential vulnerabilities. Interacting with customers requires access to their personal information on a granular level, with each interaction involving a traditional phone call, but likely to also include a communication via chat, email, SMS, social media, or all channels combined. Out of 5.2bn financial transactions in the first half of the year in the UK, 84% of these are through mobile devices, broadening the number of access points and the opportunity for exploitation.

Safeguarding data with AI

Customer-facing AI chatbots present an affordable solution in fraud detection and payment protection –capable of identifying anomalous activity that could be easily missed by human agents. This helps to rectify a staggering 90% of data breaches in the UK that were down to human error last year[4]. Used to assist customers in a number of financial transactions, such as reviewing accounts and making payments, chatbots allow users to handle simple tasks on their own, but in a highly secure manner.

Leveraging deep Machine Learning (ML) capabilities, AI-powered chatbots are programmed to learn patterns of work across multiple banking channels. By monitoring vast datasets that have been collected from past incidents, companies can recognise inaccuracies in payment information or unusual behaviours of users to continuously improve detection capabilities. Alleviating pressure from IT teams in the process, security analysts can refocus their time and resources toward actual cases of fraud and strengthen trust with affected customers. Lessons learned can then be quickly communicated and translated into targeted training for affected work groups and used to tailor customer experiences accordingly.

By prioritising AI for risk reduction systems, financial services can avoid hefty fines for failing to detect fraud and improve acquisition and retention. Customers are more likely to choose or stick with trustworthy banks that have a good track record of preventing cyber-attacks.

Banking on an AI-enabled future

It has fast become table stakes for financial institutions to build and implement robust security software and include fraud prevention and detection tools at a keystroke level. Leveraging technologies that are already used on consumers’ digital channels, and using these to secure each point of interaction, can help build an ecosystem of trusted devices while maintaining a consistent user experience. As a self-learning solution, AI-powered chatbots can assume future attack scenarios in the uncertain post-pandemic world – keeping the internal infrastructure running smoothly for employees, whilst maintaining consistent and safe online transactions for customers.





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