Nigel Cannings is the founder of Intelligent Voice
Speech recognition and AI provide innovative methods for businesses to significantly develop and improve their fraud detection systems. With the technology and techniques used by fraudsters rapidly changing, AI can evolve and adapt to provide more comprehensive protection, assisted by the use of machine learning. The acceptance of AI as a crucial asset to fraud detection and prevention is already being recognised, with 31% of CIOs having already reported the implementation of AI systems in their business, and a furth 23% expressing intent to have the technology deployed within the next year. Crucial to the effective implementation of this technology, however, is having a basic understanding of how it functions and will assist business needs.
What are the roles of AI and machine learning in fraud detection and prevention?
AI can take a variety of forms, with the core systems required for anti-fraud measures being Conversational AI, Natural Language Processing (NLP), and Automatic Speech Recognition (ASR). Automated, voice-enabled applications rely on the use of Conversational AI to allow efficient communication between technology and humans. ASR is the model tasked with translating verbal data into different formats, facilitating the recording and processing of data. The crucial bridging of the gap between the rules of human language and machine learning is carried out by NLP systems, allowing technology to process the sentiment and intent that can be derived from human interaction.
Together, these AI systems are used to both develop and augment machine learning models. The machine learning process involves the application of data from previous interactions with the intent to enable algorithms and analysis to develop and evolve alongside rapidly changing fraudulent technology and techniques. Through the collaboration between machine learning, Conversational AI, NLP, and ASR, data that would have previously been considered difficult or impractical to apply to anti-fraud measures can be repurposed. Fraud detection procedures such as checking for consistency in the details of claimant stories, identifying connections between claimants and witnesses that may be problematic, or detecting more complex behavioural indicators can be carried out more effectively, enabling a more comprehensive anti-fraud system.
What are the features that AI can recognise, and how does this help prevent fraud more efficiently?
Modern AI systems have the capabilities to detect a range of both speech and behavioural patterns, providing a more comprehensive analysis of the mannerisms and language features displayed in customer-facing interactions. There are several features that have been traditionally associated with fraudulent intent, with the most notable being frequent pauses in speech, hedging, delaying responses, indirectly answering questions, and displaying heightened emotional responses. AI not only has the ability to detect these traditional features of fraud, but it will also use its recorded history of confirmed fraudulent calls to continue tracking trends in behaviour and speech by fraudsters. Customers who have been identified to be displaying suspicious behaviour can be more closely monitored, and if the potential for fraud is confirmed, customer records can be updated with the necessary information and warnings concerning their claim. Currently, it is possible to also use AI systems to record a biometric voiceprint of known fraudsters, allowing their detection even when they call back with a new claim and different details. Through these measures, it can be possible to detect fraudulent intent from the first phone call.
However, it is important to be aware that these systems and tactics are not static, and constantly evolve depending on the new techniques being adopted by fraudsters to avoid detection. The most recent development in fraudulent operations is the use of “deepfake” technology, which can be used to mimic audio and mask a human voice in real-time. This allows fraudsters to create entirely new identities to recommit fraud with the same company, without being detected by biometric voiceprint technology. Traditional anti-fraud measures without the input of AI and machine learning will struggle to adapt to these new technological challenges. AI-based systems provide the flexibility and adaptability to allow businesses to keep up with these evolved techniques quickly, often with minimal human involvement.
How can speech recognition AI impact wider business goals?
The reach of AI is not limited to efficient fraud detection – important business goals such as the improvement of customer services also benefit significantly from the implementation of AI-based systems. Functions such as sentiment and emotion analysis now allow businesses to detect and interpret the nature of customer experiences, identifying positive and negative language and speech indicators. This enables businesses to gain a better understanding of their customer interactions and where improvements or reviews may be required. This form of analysis can also provide more detailed information about whether customers are displaying a sense of urgency, frustration, contentment, or confidence in response to their experience. Details provided by this analysis allows businesses to create more specific targets and methods to increase customer satisfaction.
Implementing wider behavioural analysis through AI systems also provides new opportunities for businesses to provide improved safeguarding for vulnerable customers. Employees can be notified when customers are displaying worrying indicators of being uncertain, confused, or concerned as a result of their interaction, and respond accordingly. These more vulnerable customers are often unemployed, young, or older adults that may require a more in-depth explanation of how the business can serve their personal needs. Follow up contact, reassurance, or in more extreme cases, welfare checks can be provided to these customers. The introduction of more thorough AI-based analysis can feel more intrusive to some customers – however, this technology also enables the provision of better customer care. The shift towards more analytical, adaptive technology increases our capabilities to care for the most vulnerable in society.
Nigel Cannings is the founder of Intelligent Voice, a company leading the international development of proactive compliance and technology solutions for various forms of media. His experience in both technology and law provides a unique insight into the future of these technologies and the legalities surrounding them.
Cloud technology in banking: Why adoption is on the rise
Alpesh Tailor, Executive Director at digital transformation specialist GFT
The banking sector has never shied away from innovation, whether it is new products to improve customer savings habits or new ways of interacting with people and business, but embracing new technologies such as cloud has, until recently, been relatively slow. However, leading global financial institutions such as Goldman Sachs and Deutsche Bank have accelerated their adoption of cloud, which can provide insights for efficient technology transformation across the sector.
We conducted research to measure 21 medium-size and large banks’ sentiment and operations regarding cloud technology. Examining the relationship between cloud technology and banking professionals, our research provides an insight into the overall finance sector’s perception of cloud technology and how its application can improve banking procedures and efficiency.
A significant trend showed that the way people use their finances and banking systems has changed, particularly when it comes to payments and transfers. Our research revealed that 86% of bankers have adopted cloud services to harness its virtually unlimited scalability, citing a definitive change in transaction behaviour as the main reason for moving to the cloud.
In the world of retail banking, buy-now-pay-later, open banking, and contactless payment systems have revolutionised the way people use their bank, making financial management easier and more efficient. However, despite these evolutions, high street banks are playing catch-up to the challenger banks who possess fewer legacy processes and, therefore, an easier migration to new technologies, such as the full utilisation of cloud and artificial intelligence.
The cloud provides a dependable, scalable, and flexible data system that allows traditional banks to modernise quickly and stay abreast of the innovations that ‘born-in-the-cloud’ challenger banks are bringing to the market. An increasingly popular way of doing this is by adopting a hybrid and multicloud approach.
Most organisations are considering diversifying their cloud technology, with 76% of bankers now agreeing with the importance of implementing multicloud systems in order to benefit from resilience and security improvements made by the main cloud providers. These cloud ‘hyperscalers’ also provide regular updates and continue to release exclusive new services and platforms as they continue to innovate.
Our research indicates that cost optimisation is a primary reason that banks are looking toward the cloud for their future storage needs, with 81% of bankers confirming they have adopted cloud technology to save costs.
Installing and maintaining on-premise IT systems is lengthy and costly for financial institutions. When using the cloud, however, purchasing and installing hardware is no longer required as the cloud service provider hosts all the required infrastructure. The management of the hardware is included within this, reducing the overall cost of IT support further.
Technological innovations are usually heralded for their ability to streamline operations, making them quicker and more secure. Our research illustrates that 62% of bankers believe organisational culture and inertia to be a key challenge within the sector. Besides being flexible for scalability and cost, adopting cloud technology can bolster organisational efficiency, since banks can spend fewer resources managing the relationship between trading volumes and payment infrastructure. Bankers acknowledge this opportunity, with 95% of organisations understanding that cloud technology can reduce time-to-market.
Overcoming misconceptions with cloud technology
Misconceptions usually exist around any emerging technology and our research found that this theme continues with cloud technology.
43% of the bankers we spoke to admitted that security concerns have impeded full cloud migration – a concern that has frequently been confirmed when speaking to financial services institutions. However, cloud providers invest heavily in the security of their cloud infrastructure which, as a result, makes it almost always safer than its on-premise, client-owned counterpart.
One aspect of adopting the cloud that continues to cause concern, is that which is commonly termed the ‘digital skills gap’. More than half of banks claim a lack of cloud-savvy employees internally has slowed down adoption. At GFT, we understand that this is a major issue for the adoption of cloud technology in all sectors, including banking, and have committed to training and encouraging young people to learn the required skills and enter the sector. We recently launched our Manchester Innovation Hub – a dedicated location to support the upskilling and growth of tech roles in the north.
Going forwards, cloud technology is the primary option for banks seeking to evolve and scale their business, whilst minimising risk, time and cost. Bankers recognise these benefits and the overall findings of our research suggest they will continue to grow their investment in cloud technology. Whilst evolving traditional legacy systems is very challenging, cloud technology continues to advance and we believe that over time it will become a powerful mainstay within the financial services industry.
A Smarter World: What role will electronics play in 2022
There has been a sharp increase in technology and devices designed to make our lives simpler, faster and more productive in recent years.
Industry 4.0 is taking the digital revolution of the late 1900s one step further, combining cyber-physical systems with the power of the internet of things (IoT) to automate computerised decision-making and enhance efficiency. As a result, intelligent technology has surpassed the simple tools and gadgets people enjoy using every day; it has become a driving force for innovation and problem-solving for businesses worldwide.
The first generation of ‘smart’ technology products provided enhanced connectivity, allowing people to stream video on smart televisions or communicate wirelessly between devices. But with the development of artificial intelligence (AI) and machine learning (ML), our devices do more than simply talk to each other; they collect and interpret data to inform user experience and automate processes that would typically require human guidance.
From watches to phones, building controls to medical equipment, we are heading towards a ‘smarter’ world at lightning speed. So, in 2022 and beyond, technology will continue to evolve and improve its capabilities to deliver personalised, mechanised solutions that will optimise functions and enhance our day-to-day lives.
How will smart tech change our way of life?
The pandemic has significantly impacted global technology trends, with lockdowns contributing to heightened activity within the consumer electronics industry.
The demand for games consoles, smart televisions and other entertainment devices led to an 18% increase in the global consumer electronics market (excluding North America) in the first half of 2021, reflecting pandemic-related behavioural changes and consumers’ growing expectations for premium electronics. Following the outbreak of COVID-19, the public is also more conscious of their health and the limitations of our health services than ever before. Wearable technology such as smartwatches — which can remotely monitor and record physical health data — is, thus, becoming increasingly appealing.
As more and more businesses embrace remote working models, employees are enhancing their homes with innovative home technology, too. Demand for devices such as mobile stereo headsets and headphones spiked in the wake of lockdowns. Organisations are also embarking on digital transformation to secure online networks and optimise energy efficiency in modern offices.
The future of the electric vehicle market also looks bright. With governments facing global pressure to reduce carbon emissions, major automotive manufactures like Bentley, Volkswagen and Audi have pledged to cut fossil fuel cars from their product portfolios by 2030. And despite the pandemic-related semiconductor shortage that crippled the automotive industry, UK electric vehicle sales jumped 186% in 2020.
How will the electronics industry meet demands?
In a digital world, technology is embedded in everyday objects, and ubiquitous computing connects devices through continuous networks of sensors and servers — all of which must be carefully designed and produced by electronics manufacturers. As a result, the future of electrical engineering will depend on the industry’s ability to address the technical and logistical considerations for delivering these advanced systems and equipment.
From smart grids to intelligent lighting, IoT has the potential to revolutionise the way we live. With technology permeating so much of our lives already, local governments are investing in ‘smart cities’ that will harness data collected through the IoT and cloud-based technology to tackle social issues and improve urban life, sustainability and transport. However, the IoT will also be essential to developing new electronics.
Brexit, the pandemic and labour shortages have impacted supply chains and threatened to stunt the industry’s ability to keep up with ever-increasing demand. But embracing IoT can streamline processes, provide accurate real-time data to mitigate supply chain disruption and improve the overall quality of printed circuit boards (PCBs) and other core components within electronics. Plus, as sustainability is a core focus for businesses across sectors in 2022, developments in AI and ML will be crucial to ensuring systems are operating with the minimum energy output.
From remotely controlled wire cutters to industrial robotics performing monotonous tasks in factories, investing in robotics will also be crucial for electronics manufacturing services providers. While the industry focuses on training the next generation of engineers, adopting robotics will reduce the likelihood of human error that might affect manufacturers’ abilities to continue delivering high-quality electronics products at scale.
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