Maximising productivity with AI-powered fraud detection


Darryn Welsh, Head of Sales for Finance, Insurance and Professional Services at Vodafone Business, explores the role that AI can play in the future of security for finance organisations.

  • Financial institutions face the constant threat of increasingly sophisticated cyber-attacks, and traditional methods of reactive fraud detection often fall short.

  • By integrating AI, finance organisations can now detect fraudulent activities in real time and eliminate the need for long post-incident investigations.

  • Quick responses help to safeguard financial assets, while the time saved enables financial institutions to focus on more strategic initiatives, like enhancing customer experience.

The future of security in finance

The importance of security in finance is obvious. But did you know that artificial intelligence (AI) now plays a pivotal role in real-time fraud detection?

Steve Knibbs, Head of Vodafone Business Security Enhanced (VBSE) services, believes that AI will allow businesses to identify and respond to threats faster and more effectively than ever – but only when used with careful consideration:

“AI is a concept that will have a revolutionary impact on the world, not least when it comes to cyber security. The technology has the power to supercharge fraud detection and protect organisations everywhere from the damaging effects of successful attacks. For this reason, AI will no doubt change how companies operate at a foundational level, but it needs to be managed in a sustainable and responsible way.”

Here’s why, in our opinion, the future of security lies with AI – when managed in the right way.

The demand for swift action 

Today’s financial institutions face the constant threat of increasingly sophisticated cyber-attacks. In 2022, around £2,300 was lost every minute to fraudulent activities, totalling £1.2 billion for the year across nearly three million confirmed cases.¹

Swift action is vital because delays can exacerbate breaches, risking data compromise, financial loss and reputation damage. Quick responses enable containment, protection of assets, compliance with regulations, preservation of trust, and the prevention of prolonged disruptions to critical services. 

However, while most organisations already have traditional forms of protection in place, the approach of reactive fraud detection, with its reliance on post-incident investigations, often falls short in the fast-paced world of finance. Enter AI.

“AI will no doubt change how companies operate at a foundational level, but it needs to be managed in a sustainable and responsible way.”

Significant productivity gains

AI-powered security offers tangible productivity gains by eliminating the need for long, drawn-out post-incident investigations.

With the time saved, financial institutions can redirect their resources toward more strategic initiatives, such as enhancing customer experience, developing innovative products, and staying ahead of regulatory compliance requirements.

Up to 30% productivity gains can be achieved across analyst roles by processing information at speed and scale that were not possible before.⁴ And current generative AI and other technologies have the potential to automate work activities that absorb 60-70% of employees’ time today.⁵

AI’s role in real-time fraud detection

With the integration of AI, finance organisations can now detect fraudulent activities in real time. Machine learning algorithms, powered by vast datasets and continuous learning, enable swift identification of suspicious patterns and anomalies.

It’s a more proactive approach to fraud prevention. And it’s why 91% of financial institutions have either narrowly or widely deployed predictive AI in fraud detection and back-office functions with recorded benefits.²

AI also plays a crucial role in user authentication and access control. It’s perhaps why "increased fraud detection" now ranks as the primary driver behind AI investment, reflecting the finance industry’s unwavering commitment to protecting customers from transaction fraud.³

Up to 30% productivity gains across analyst roles

AI powered security enables faster information processing at a scale that was not possible before.⁴

Up to 70% of employees’ time saved

Generative AI technologies can save up to 70% of employees’ time by automating work activities.⁵

91% of financial institutions have deployed predictive AI

Predictive AI has been deployed in fraud detection and back-office functions with recorded benefits.²

Further business benefits

Beyond productivity, AI-powered security offers many other business benefits: 

  • Efficiency in resource allocation
    AI-driven security enhances the speed of fraud detection, allowing finance organisations to allocate human resources strategically and adapt to emerging threats in real time.

  • Precision in fraud detection
    AI continually refines algorithms through machine learning and reduces the occurrence of false positives. This ensures that legitimate transactions are not incorrectly flagged.

  • Innovation in financial security
    The incorporation of cutting-edge technologies, such as deep learning and neural networks, enhances AI's ability to detect new and complex threats such as “deep fake” patterns.

A strategic imperative

It’s easy to see why AI-driven fraud detection should be a strategic imperative for financial institutions. The ability to prevent fraud in real time not only safeguards financial assets but also provides the power to transform a business’s operations. At Vodafone Business, we can help by delivering:

  • High-speed connectivity: fast, reliable internet connectivity to ensure seamless communication and data transfer between devices and AI systems.

  • Edge computing: solutions that reduce latency and process data closer to the source, enhancing the efficiency of AI applications.

  • IoT connectivity: supporting IoT devices with connectivity solutions, enabling businesses to collect and transmit data from sensors and devices for AI analysis.

  • Cloud services: integrated solutions that facilitate AI model training, deployment and management in the cloud.

  • Network slicing: allowing businesses to allocate dedicated network resources for their AI applications, ensuring consistent performance and reliability.

Interested in learning more? Talk to us to find out how to achieve more efficient operations, improved decision-making and enhanced business outcomes.

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