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HOW CAN THE PAYMENTS INDUSTRY PREPARE FOR SCA WITH BIOMETRICS?

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By Vince Graziani, CEO, IDEX Biometrics ASA

 

Significant developments are afoot in the retail and payments industry, with vendors needing to prepare for Strong Customer Authentication (SCA). It’s set to be the most significant change to how people pay for things, not only online but also for card-present retailers across Europe. The deadline for compliance with the regulation has recently been extended again, this time to March 2022.

This is now the third time the deadline for retailer compliance has been pushed back, with the Financial Conduct Authority (FCA) worried vendors are not prepared for the new payment security approach. Which raises the question, will SCA every really take off?  Well, for retailers the extended deadline can be viewed in a positive light. The fact that there are now a further ten months to pilot and then launch their response gives retailers more time to adapt their authentication and verification tools. But it’s also a benefit for banks and payment providers too.

The ongoing delay to the SCA will give the payments industry extra time to prepare for the rollout of the directive so they can deliver a secure SCA payment option to consumers. If the payment ecosystem fails to use this time to prepare or implement the right technology to comply with this new ruling, it will open consumers up to a significant threat of card fraud.

 

Vince Graziani

The challenges faced within the retail space

There has been a large amount of focus on the implications of SCA when shopping online; however, face to face purchases will also need to be revisited. Even when using a card physically, SCA will require two-factor authentication for every purchase made over the contactless limit. This additional layer of protection provides a more stringent authentication process that will help to keep millions of accounts safe from both traditional fraudsters and cybercriminals.

Two-factor authentication means that not only will the user need to provide their details when making a purchase, they’ll also have to confirm their identity with:

  • something they know (a PIN or password),
  • something they have (such as a smartphone),
  • or something they are (biometric face or voice features or a fingerprint).

Once implemented, this will be beneficial in protecting consumers, however, getting to this stage will be a challenge. The requirements are set to cause widespread disruption to the retail space. The introduction of SCA will require in person merchants and card issuers as well as online Payment Service Providers (PSPs), such as PayPal and WorldPay, to have in place the technical enhancements and testing needed by the deadline.

 

Educating the shopping public on SCA

This presents a significant logistical challenge; maintaining effective fraud prevention while keeping an optimised customer experience is not easy. But perhaps the biggest challenge of all is that consumers themselves still aren’t entirely aware of SCA or what will be expected of them come March.

The introduction of SCA demands collaboration within the industry to educate consumers, but ultimately it is up to payment providers to provide a reliable, secure and SCA-approved method of payment to consumers. Providers must also ensure that the method they choose is not only up to standard but is affordable and accessible to all.

 

Preparing for the future of secure payments with biometrics

Biometric payment cards offer the answer for payment providers to help prepare for SCA. Not only will these cards – with inbuilt fingerprint sensors to verify ownership – provide strong customer authentication, but they also come with the added benefit of convenience. Validating your payment with a fingerprint speeds up the transaction process and removes the requirement of PINs or the use of a smartphone.

Biometric fingerprint payment cards offer banks and payment providers, an opportunity to embrace payment innovation that will help them meet these new secure forms of authentication with confidence and ease.

It is worth noting that some payment card manufacturers, such as IDEMIA, are already preparing biometric payment card solutions. These will be ready for banks and card issuers to adopt so they have the time they need to pilot and roll out the new payment method before the new SCA deadline is imposed.

The FCA has also outlined previously that long-term authentication through biometrics and mobile app-based solutions is the future of secure payments. The use of biometric payment cards to authenticate online payments will offer an important way for retailers to balance security measures that comply with the SCA regulation whilst also delivering ease of use for the consumer.

 

Technology

HOW ARE SPEECH RECOGNITION AND AI FIGHTING FRAUD?

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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.

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IS THERE A CASE FOR APPOINTING A DIGITAL TRANSFORMATION OFFICER?

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By

Stefano Maifreni, founder of Eggcelerate

 

You can tell the business world’s direction by the new roles that start to pop up in the C-Suite. With titles like chief transformation officer, chief change officer, and digital transformation officer, it’s clear what’s on a business leader’s mind these days. Each of these roles is a response to rapidly changing market and customer trends and an avalanche of technological advances that are causing businesses to rethink the way they operate.

In this article, however, we’re going to take a closer look at the Digital Transformation Officer (DTO). This professional is specifically focused on an organisation’s digital strategy and transformation.

Not every company needs to hire someone for this position, however. Sometimes it’s better to get every senior officer involved and lead the company’s digital transformation as a team.

To help you decide whether to bring in a DTO, we’ll offer some points to consider below.

 

What is a DTO, and What Do They Do?

Today, an organisation’s success and long-term sustainability heavily depend on its digital infrastructure combined with a data-driven culture. Smart, automated IT systems enable critical modern business capabilities such as personalisation, adaptability, and innovation. A data-driven culture then leverages the business and market data captured and analysed by these systems to guide business decision making at all levels of the organisation.

Even technology-based businesses, such as fintech companies and SaaS providers, don’t always have the most effective and efficient digital infrastructure in place. Moreover, establishing a well-oiled data-driven culture takes much time, research, and consideration.

It is where a DTO comes in. A DTO is a member of a company’s senior management team. They are responsible for leading a business’s digital transformation in response to the emergence of new critical technologies, significant shifts in the market, or the development of new business products or services, among other events. These professionals work closely with the CEO and the C-suite, but at the same time, they must also collaborate with employees at virtually every level of the company.

Having a strong, focused senior leader at the helm of such an undertaking is thus critical to its success.

 

Three Necessary Qualities to Look for in a DTO

If you decide to hire a DTO, the person you choose for the role must possess several essential qualities to steer your company through a successful digital transformation. These qualities are in addition to technical expertise and general industry knowledge:

 

They can see the big picture.

A DTO must take in the whole picture of your company and determine the critical areas where people, data, and infrastructure interact. They can then leverage that knowledge to implement digital initiatives for every significant business process’s strategic innovation and business transformation.

They must be able to consider the customer’s experience and needs as the agent and driver for change, on the one hand, while understanding the unique needs and culture of your business on the other. It includes understanding how people and departments interact and how third-party vendors and service providers fit into the system. The goal is to balance the company-wide need for change and adaptation with consideration for employee needs for consistency, stability, and clarity.

 

They possess good communication and collaboration skills.

While the role requires a wide range of soft skills, abilities in communication and collaboration are at the top of the list. A DTO must speak to a broad spectrum of people at every level of the company. It is crucial not only for gathering information and feedback but for encouraging employee buy-in in response to change. It (almost) goes without saying that a big part of communication is not just speaking to others but listening to what is being said or reported honestly.

 

They are humble and able to learn from others.

This role involves gathering a lot of input from employees at the lowest ranks of a company, particularly those directly involved with customers, such as sales and customer service representatives. At the same time, DTOs must report to the CEO and collaborate with other C-Suite executives. To do this properly, a good DTO must be open and willing to learn from others, consider different ideas and opinions, and be ready to course-correct when an initiative goes off track.

 

Not Every Company Needs a DTO

While many companies may want to pass the responsibilities of a DTO on to a specific individual, so they are free to focus on other areas of the business, it may not be the best decision. Here are a few reasons why:

  • Unlike traditional C-Suite roles, the DTO is transient by design. It means that companies usually employ a DTO to get a digital transformation off the ground. Once the change is fully integrated into the company’s operations, the DTO is no longer needed. With the proper infrastructure and data-driven culture in place, digital transformation and innovation self-perpetuates.
  • Another issue is that companies typically hire an outsider to fill the role of DTO. While this may give the company access to a fresh perspective, an outsider working in a transitory position may not be willing or able to reach the level of understanding– whether of the company or the market it serves– needed to make the most effective decisions.
  • Because digital infrastructure and adaptability are key business competencies, direct involvement in the digital transformation process helps senior leaders improve their strategic decisions overall.

While companies that rely on analogue processes may benefit from a dedicated DTO, in many cases, appointing a DTO is not in the best interest of an already digitally aligned company. It may be much more effective to create a company-wide commitment with a team of senior leaders responsible for the digital transformation, rather than passing the details and management of the transition off to one individual.

 

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