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HOW ARE SPEECH RECOGNITION AND AI FIGHTING FRAUD?

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Nigel Cannings the founder of Intelligent Voice

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.

Banking

Poor software testing puts banks at high risk of IT failures

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 Sune Engsig, VP Product at Leapwork

 

IT failures have plagued the banking industry for several years. From the TSB computer systems meltdown in 2018 costing the bank £330m and causing 80,000 customers to switch to a competitor, to Lloyds, Halifax and Bank of Scotland suffering an IT glitch on payday this year with customers’ faster payments and transfers being delayed.

Despite MPs calling for regulators to act, condemning the number of IT failures in the financial services sector as ‘unacceptable,’ the industry continues to let them happen leaving more and more irate customers locked out of their accounts. But with bank branches disappearing fast, customers are now far more reliant on online and mobile banking, so ensuring technology systems function correctly is paramount.  When you consider the complex compliance and regulatory setup of banks and other financial institutions, and the fact that they are dealing with incredibly sensitive customer information, those that do experience outages can face irreversible consequences such as loss of customer loyalty, severe reputational damage and regulatory fines.

A critical step in mitigating IT failures is having effective testing capabilities in place to find and fix any errors before new software is rolled out to market or new IT migrations take place. This lowers the risk of software failures and outages occurring after launch. Yet, 70% of software testers in banking and financial services think it’s acceptable to release software that hasn’t been properly tested, so long as it’s patched later, according to research by Leapwork. Furthermore, only 40% think software failures are a big risk to their company. But when the impact of an IT failure is so severe, why do banks still take risks?

 

Software testing challenges

Despite the swathes of software businesses now rely upon, 85% of software testing is still done manually. When it comes to the banking sector, as these institutions continue to develop new digitised products and services with increasingly sophisticated and customised software, it is clear that manual testing can no longer be the default. It is time-consuming, cannot scale amidst a skills crisis, and leaves companies open to human error.

There is a huge amount of pressure on IT teams to develop and release new software or manage new IT migrations. A critical step on this journey is having effective testing capabilities in place, like test automation, to find and fix any errors and bugs before new software is rolled out to market. This lowers the risk of outages and failures occurring after launch, which can negatively impact a company’s reputation and bottom line.

However, while some organisations recognise the value of automation tools, many continue to rely too heavily on code-dependant tools which, while an improvement on manual testing, are incredibly complicated to use and thus require specific skills and experience to operate. This means they too are impossible to scale, as they often depend upon developer skills.

 

Skills shortage forcing banks to take risks

Ensuring you undertake proper software testing seems like a no-brainer, but 40% of software goes to market without sufficient testing. The reason why; one in five (21%) of banking and financial services testers say ‘lack of available skilled developers.’ As companies transition from manual to automated testing, which typically requires coding skills, the major global developer skills shortage is creating bottlenecks, increasing costs and delaying project delivery times as development teams try to upskill manual testers, hire new talent or lean on existing developers.

As a result of the skills shortage, only 30% of testers in banking and financial services say they’re using some element of automation (i.e., an automation tool or a combination of manual and automation). In fact, 40% of CEOs across all industries think the fact that their company still relies on manual testing is the main reason why software isn’t tested properly, with 58% of testers in banking and financial services saying ‘underinvestment in test automation’ is the reason sufficient testing does not occur.

 

Testing issues not on CEOs’ agenda until too late

Across all sectors, 69% of CEOs think it’s acceptable to release software that hasn’t been properly tested, so long as it’s patched later, but 68% of testers claim their teams spend five to 10 days per year patching software. While nearly all testers express concern that insufficiently tested software is going to market, the overwhelming majority (75%) of CEOs say they’re confident their software is tested regularly. These numbers show a huge disconnect between CEOs and testers indicating that testing issues are falling under the radar and not being escalated until it’s too late.

 

Moving toward an automated future

Banking and financial services have been thought of as slow-moving and lacking innovation in the past. That isn’t the case anymore, as we’ve seen the industry take great strides towards digitalisation in recent years. However, with that digital transformation and integration of software comes outages, the consequences of which mean millions of pounds lost.

UK banks are at high risk of IT failures due to insufficient software testing, and a reliance on manual testing. On the current trajectory, more and more banks will struggle with failures and outages which could cost them a significant amount in financial and reputational damage. To minimise risk, they need to transition from manual to automated testing and explore testing options that don’t require coding skills so it’s easier to hire in talent or upskill existing team members, whether that be testers or everyday business users. Only then can they increase productivity and time to market while decreasing risk and costs.

 

 

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Business

Black Friday, Cyber Monday and beyond: The inevitable shift to mcommerce

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Arunabh Madhur, Regional VP & Head Business EMEA at SHAREit Group

 

Last year, we saw explosive growth in Black Friday sales; a culmination of Covid-19 lockdown restrictions easing, shifting traditional shopping behaviour, and accelerated digital transformation. Notably, we witnessed the mobile economy gain momentum, with consumers enjoying the ease and convenience of a streamlined purchase process at the touch of their fingertips. At SHAREit, we have also noticed that peer-to-peer sharing has become increasingly popular and a habit. The unprecedented ability and speed allowing app sharing between family and friends have only brought people closer together. Whether it’s a product recommendation or sharing discount codes with loved ones, digital interactions are built on offline relationships. In fact, ‘social commerce’ is highly dependent on trust within a community, the interactions of users, and word of mouth.

Arunabh Madhur

The global pandemic has spearheaded the adoption of mobile technology around the world, including in emerging markets. In turn, in-app purchases spiked worldwide in this time, especially in emerging markets like Southeast Asia, the Sub Indian continent, the Middle East and Sub-Saharan Africa, as consumers spent more of their income online. According to recent data, there are now 13 markets where users are spending more than four hours per day using apps. To name but a few, these include Indonesia, Singapore, Brazil, Australia, Japan and South Korea. This was anticipated, due to social distancing measures and lockdowns globally, most people turned to digital channels to find products and services.

 

How mobile is redefining shopping experiences

Mobile shopping has already become a huge part of our lifestyle. According to eMarketer, mobile commerce remains the most preferred channel among consumers globally. By 2024, global mobile commerce retail sales are expected to reach nearly $4.5 trillion, accounting for 69.9% of total retail e-commerce sales.

The pandemic saw a large set of people moving to mobile transactions largely in the space of e-commerce, medicine buying and food delivery business. These were supported by a very strong mobile commerce and payments which lead digital payments push and the entire conversation around the mobile commerce category.

 

The value of consumer personalization: how payments can help

It’s also important to not forget the rise of e-payments that has been pushing digital shopping towards wider adoption. Digital payment methods, such as Apple Pay and Google Pay, which enable card payments via smartphones, have not only streamlined the customer journey but also facilitated access to e-commerce, especially to the large unbanked population in emerging markets. With digital wallets becoming a core part of payments and online shopping experiences, mcommerce transactions will continue to grow.

In addition, the rise of micropayments has built a  strong mandate in driving mcommerce internationally and in emerging markets, with digital payments expected to account for 91% of total e-commerce spending by 2025. This is an up-tick from 80% in 2020. Therefore, the key for retailers is to support as many digital payment mechanisms as possible to help meet consumer demands and minimise the rate of transaction abandonment. Merchants and payment providers also need to work together on optimizing websites and payment solutions for smartphones in order to remain competitive and appealing to consumers.

 

New digital habits and why there is no going back

It is easy to see that digital habits learned during the pandemic have now been fully integrated into people’s daily routine. Improvements in productivity and efficiency brought about by increased adoption of mobile services is benefitting both consumers and brands. As a result of this, mobile is now at the heart of business strategies for consumer brands, which helps when reaching audiences at scale, improve customer shopping experiences while boosting online conversions. This is also a preferred route for people worldwide right now as it provides a convenient channel to shop whenever and wherever.  Therefore, we expect that the majority of Black Friday and Cyber Monday purchases will come from online and mobile purchases. For companies, that want to grow over the next few years, investing in mcommerce transactions and creating bespoke experiences for their customers will be pivotal.

Further to these fast-growing mcommerce across emerging economies, mcommerce is also experiencing growth across Europe. In the UK specifically, 60% of total retail online sales now come from mobile phones – that’s more than any other county in Europe. In fact, only the US and China are ahead when it comes to the mcommerce market. Mobile phones are now the primary choice when it comes to making online purchases and it is expected to surpass £100 billion by 2024 in the UK. As a result of the rise of mcommerce, SHAREit now works with leading global e-commerce brands, in Southeast Asia, South Africa in Europe and Middle East with a performance ad solution and the retargeting solutions.

The evolved mobile shopper has new expectations and seeks richer experiences from existing brands. For companies with their eyes firmly set on growth in the coming year, brands need to adapt to this change, and create bespoke experiences for their customers in order to thrive.

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