75% of Acquiring Banks Use AI to Detect Card Fraud

Acquiring banks are under intense pressure to process transactions efficiently while detecting and preventing fraud attempts. That’s a growing challenge due to recent increases in both payments volume and fraud attacks. To manage these trends, many acquirers are using artificial intelligence (AI). 

A new report, AI In Focus, a PYMNTS and Brighterion collaboration based on a survey of 104 executives at acquiring banks, found that 37% of acquirers say payments volume increased in 2021, and 93% of acquirers say their ratio of fraudulent transactions as a share of total transactions increased in the last 12 months. 

Get the report: Waging Digital Warfare Against Payments Fraud 

Acquirers have already widely adopted AI and related technologies to help them safely manage their businesses. In fact, 75% of acquirers use AI to detect card transaction fraud. Some evidence suggests AI can improve payment volume as well. Acquirers that use AI are 2.6 times more likely than those who do not to say their payment volumes have increased in the last 12 months. 

These organizations view AI as an important tool to fight fraud and improve revenues. That’s key because 88% of the acquirers that use AI say reducing fraudulent transactions is a “very” or “extremely” important factor for maintaining profitability in the next year, and 53% say reducing the number of fraudulent or unprofitable merchants on their platform is an important factor for the same reason. 

Acquirers are also aware that making the right investments in technology, including AI investments to bolster fraud detection, can be a differentiating factor to merchant clients in a competitive market. A large share of acquirers that use AI systems, 83%, say acquiring new merchants is a “very” or “extremely” important factor for maintaining profitability in the next year. 

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NEW PYMNTS DATA: AUTHENTICATING IDENTITIES IN THE DIGITAL ECONOMY – DECEMBER 2021

About:More than half of U.S. consumers think biometric authentication methods are faster, more convenient and more trustworthy than passwords or PINs — so why are less than 10% using them? PYMNTS, in collaboration with Mitek, surveyed more than 2,200 consumers to better define this perception versus use gap and identify ways businesses can boost usage.

AI Solutions Aim to Eliminate Manual Work

To take on the challenges of accounts payable (AP) invoice automation and the insurance submission intake, Kanverse has deployed a product that uses several technologies: artificial intelligence (AI), machine learning (ML), optical character recognition (OCR) and natural language processing (NLP).

“It’s actually a hyper-automation platform,” Kanverse CEO and Founder Karan Yaramada told PYMNTS. “AP invoice automation is only one use case for the platform.”

Compared to conventional systems, this hyper-automation platform reduces both the time to implement and the total cost of operations. While making changes to a conventional system requires bringing in an IT team or even the vendor, the Kanverse platform can change by learning on the job.

“In our case, users can turn on the learning mode and do the steps that they would do, and then the system will learn automatically,” Yaramada said. “So, you can pretty much avoid going to the IT team, bringing in a vendor, making the change, testing it and going through the whole nine yards.”

Eliminating Manual Work and Errors

This is particularly useful in insurance, a regulated industry that relies on complex paperwork. Using OCR alone simply takes the paper and converts it into a digital form, which is only about 20% of the solution.

A platform that also uses AI and ML, on the other hand, does much more. “Using AI and ML, you can teach the system, ‘okay, if the user checks this box, make sure these other 10 things are done,’” Yaramada explained.

Catching incorrect data before it goes downstream can save the expense of processing it later. Yaramada noted that it also frees up the people who are now processing this data to instead do things like analyze the business, sell or improve processes and efficiencies. It will also enable companies to reduce costs and eliminate paper.

Making 90% of the Process Touchless

Yaramada said the company is confident that the platform can make 90% of the process touchless. In the remaining 10%, where there may be anomalies or extreme cases, people can still get involved.

“Whether it’s AP invoice automation or the insurance industry submission process, there’s a lot of tribal knowledge that makes people critical in these processes,” Yaramada said. “I think it is unnecessary. People don’t have to be critical in the process; let the process run by itself.”

Although the product is still in its early stages, the company has already received “great feedback” from customers. Yaramada reported that an AP invoice automation customer said tasks that used to take days to process now take seconds, and that an insurance industry customer said the platform is going to differentiate them from their competitors because they can move fast now.

“They can deploy all these people that are doing these jobs to do the productive tasks and the more exciting, value-added kind of work,” Yaramada said.

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NEW PYMNTS DATA: AUTHENTICATING IDENTITIES IN THE DIGITAL ECONOMY – DECEMBER 2021

About:More than half of U.S. consumers think biometric authentication methods are faster, more convenient and more trustworthy than passwords or PINs — so why are less than 10% using them? PYMNTS, in collaboration with Mitek, surveyed more than 2,200 consumers to better define this perception versus use gap and identify ways businesses can boost usage.

How A Digital-First World Has Changed AML/KYC

The economy’s digital shift started long before the global health crisis, but the past 20 months have definitely accelerated digital-first trends in eCommerce and banking. Leading financial institutions (FIs) now recognize that to engage digitally-savvy consumers, they need to provide convenient, streamlined and interactive banking experiences — already strong suits for emerging digital-only banks and FinTechs.

PYMNTS research has found that half of consumers increased their use of online or mobile banking between July 2020 and July 2021, with young adults and affluent consumers showing the most significant gains. More than 20% of consumers who use a digital banking app “significantly” increased their usage between July 2020 and July 2021. Digital banking app adoption rates saw significant gains at national and digital banks as well: consumers increased their use of mobile payment apps by 31%, and digital wallets by 28%.

Consumers also have come to expect greater access to more complex digital banking services, such as opening a new account or the ability to be approved for a mortgage or loan. However, banks often struggle to deliver these services sufficiently online or via banking apps due to the high risk of cybercrime. Banks are required to verify customers’ identities based on anti-money laundering (AML)/know your customer (KYC) regulations, procedures that are not always easy to complete online as data breaches can provide fraudsters with access to customer information.

This month’s Deep Dive examines the challenges FIs face in meeting AML/KYC regulatory requirements as digital banking becomes more popular. It also looks at how advanced technologies such as biometrics, artificial intelligence (AI) and machine learning (ML) are helping banks adapt to the changing market while remaining AML/KYC compliant and keeping their customers safe from online threats.

Why FIs Need to Adopt AML/KYC for the Digital-First Market

Digital-first banking — an umbrella term that encompasses traditional banks, digital-only banks and FinTechs — continues to make inroads across the globe, providing consumers with efficient and secure access to online banking services. While laying the groundwork for fully digital banking offerings to emerge, regulators in various countries also have allowed traditional banks to tap into new innovations that enable them to move to digital-first banking.

Open banking, for instance, enables data sharing across networks and third-party transactions. It also provides new opportunities for non-banks to compete, offering consumers access to a wider variety of personalized services. Meanwhile, cloud hosting helps banks scale their infrastructure and access next-generation systems. It also enables FIs to comply with local data hosting and protection regulations.

As with traditional banking, AML/KYC compliance remains paramount, and electronic know your customer (eKYC) technologies can help. This technology, along with eSignatures for remote customer validation, enables digital onboarding that works with data analytics to check customers’ identities and mitigate AML.

One option banks are turning to when opening new accounts is digital identity verification using facial comparison technology. This option allows banks to comply with AML/KYC regulations and stop bad actors from using stolen identities for new accounts. New customers can use their smartphone cameras to capture their government-issued ID and to take a selfie. The documents then are verified using advanced computer vision and biometric facial comparison technologies.

Banks also are adopting advanced technologies, such as behavioral biometrics, to mitigate identity theft and account takeover (ATO) fraud. Fraud teams can continually monitor user behavior during a mobile banking session, pinpointing anomalies in finger pressure or navigation and swipe patterns, and then trigger additional authentication requirements if the user does not seem legitimate.

FIs also utilize real-time behavioral analytics to monitor banking transactions for fraudulent activity, relying on data recognition of consumer behaviors to recognize changes, rather than aggregated consumer data. Powered by AI and ML, the latest adaptive behavioral analytics technologies provide real-time insights into customer trends and fraud detection. These cutting-edge tools enable FIs to better understand customer behavior, detect anomalies, identify suspicious activity and prevent fraud before it happens.

The Benefits of Adopting AI and ML Technologies for AML Compliance

Historically, FIs have invested a great deal of time, money and effort to comply with AML/KYC regulations — regulatory compliance costs U.S. banks $25 billion a year. With banks struggling to adapt to consumers’ growing digital habits, compliance caseloads are rising, and AI and ML technologies can be a viable solution. Increased interest in AI and ML can be attributed to the soaring rise of digital transactions for goods and services brought on by the pandemic, along with skyrocketing online fraud and identity theft. The health crisis has burdened AML compliance teams with new security demands that existing technologies and processes cannot address.

Such anti-fraud tools have relied on deterministic systems and have trouble understanding changes in online behavior, resulting in more false positives and less productivity. AI and ML are viable alternatives because they are dynamic by nature and can both adapt to changing behaviors and respond better to emerging risks. Some AI and ML solutions even integrate into existing compliance infrastructures.

According to a recent survey of FI decision-makers on the impact of the pandemic on their AI and ML adoption plans, AI and ML for AML compliance has seen significant adoption among mid-market and tier II institutions. According to the study, 15% of participants reported they are piloting AI solutions, 21% said they had implemented an AI solution, and another 21% said they have plans to do so in the next 12 to 18 months. Still, 27% of FIs said they have no current implementation plans.

Recognition of the benefits of AI and ML for AML compliance is driving adoption, along with support from regulatory bodies, as 66% of survey respondents said their regulator was supportive of AI/ML adoption. Regulators in the U.S., United Kingdom and Singapore are among those encouraging, but not enforcing, technical innovation for AML compliance.

These findings indicate that traditional FIs have access to cutting-edge tools that can help them attract and retain digitally-savvy banking customers while also remaining AML/KYC compliant. They can move to a digital-first banking environment and continue to mitigate identity theft and online fraud while providing consumers with an engaging and secure digital banking experience.

Why Banks Embrace AI Platforms-as-a-Service

Sudhir Jha, senior vice president and head of Mastercard’s Brighterion unit, told Karen Webster in the most recent On the Agenda discussion that artificial intelligence (AI) can strengthen credit and risk management and broaden its value well beyond simply improving day-to-day operations.

But to get there, enterprises need a bit of guidance.

“What used to be cutting-edge technology five years ago is no longer cutting edge,” he said, and enterprises that try to keep up with the rapid changes in data science and analysis on their own can be quickly overwhelmed. The enterprise that starts with regression and pattern analysis solutions might scale rapidly and find benefit from neural networks.

For banks, acquirers and healthcare payments executives, he said, using vendors’ AI-based solutions help to avoid undue losses from fraud, the abuse and misallocation of funds and poor underwriting decisions.

Jha’s comments came against a backdrop in which 88% of financial institutions (FIs) said the pandemic has made lending and credit more challenging. Jha said that the pandemic has underlined that firms need fraud fighting systems in place that are adaptable and that change as the fraudsters change.

“Every month, even every day can be different,” he said, adding that “as an enterprise, there is only so much that you can react to.”

Although most executives see the value of deploying AI systems in their risk-management efforts, many executives are unsure of just how to proceed in making the aspiration a reality. AI tech talent is hard to find and takes years to train, and building models and solutions in-house can take years.

Given those challenges, it makes sense to work with outsourced providers (Brighterion among them), where tapping into what Jha termed a fully baked solution can be no different than the way buying an HR solution a decade ago might have been.

We’re moving toward turnkey solutions where AI modeling is baked in, with the different, disparate data elements that firms need to boost their own fraud defenses.

“Your own data gets into the system, and as the model trains on that, you’ll get more and more value — and you can get started pretty quickly,” he said. “That’s the next evolution for AI solutions.”

Along the way, rapid, accurate decisioning allows FIs (and other enterprises) to build new credit products and services — evident in the explosion in buy now, pay later (BNPL) offerings in just the past year across traditional FIs and digital-only FinTechs, he said.

Improving Credit Risk Management

Jha noted that AI has particular value in managing credit risk. It can leverage real-time data to help lenders make better decisions at origination and spot hiccups and potential fraud before losses hit results.

There’s a bit of lopsided embrace of AI as 79% of banks with more than $100 billion in assets use AI, but only a fraction of smaller banks do. And although progress has been made, the greenfield opportunity is significant. In 2018, 5% of FIs reported using AI systems in areas like credit risk management and fraud detection. By 2021, that figure had increased threefold to 16%.

Jha posited that smaller firms might not have enough data (particularly as the initial credit application is made) to build AI models. Even on the delinquency side of the equation, there is not enough data on hand to be predictive. He said that platform models have broader options that enterprise clients can access to build the best models possible.

The urgency to tap into the platform model is there, as 93% of all acquirers said they are seeing more fraudulent transactions than one year ago. Ninety-eight percent of all acquirers that use AI use it to detect fraud, and 79% of them consider AI to be the most important tool in their fight against fraud.

“Everybody’s struggling with onboarding hundreds and thousands of small businesses that they want to do business with,” he said.

The Approval Dilemma

Acquirers face a dilemma when fighting fraud, said Jha. On one hand, they want to make sure that the fraud is stopped early, before those suspect transactions are submitted to the issuers. But they also want to increase approval rates — in Jha’s terms, “because the issuer knows you’re a good acquirer.”

But acquirers must also worry about the risk of onboarding fraudulent merchants. Machine learning (ML) and AI technologies can accelerate the process. He told Webster that Brighterion is bringing its data assets together to create a data onboarding solution that can assess credit risk at that initial point of contact.

“You’re building more safety into the system,” he said, as each transaction and customer is viewed holistically.

Looking ahead, Jha said that we’ll see a continued shift away from enterprises continuing to invest in AI by building solutions from scratch.

“You’re not actually going to get any differentiation by doing that,” he said. “If you can actually have a vendor that can provide you a turnkey solution and will invest in innovation going forward, you are much better off just adopting that, and then making some custom improvement on that.”

As he told Webster, in credit risk and anti-fraud efforts, “adaptability has become the name of the game.”

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NEW PYMNTS DATA: AUTHENTICATING IDENTITIES IN THE DIGITAL ECONOMY – DECEMBER 2021

About:More than half of U.S. consumers think biometric authentication methods are faster, more convenient and more trustworthy than passwords or PINs — so why are less than 10% using them? PYMNTS, in collaboration with Mitek, surveyed more than 2,200 consumers to better define this perception versus use gap and identify ways businesses can boost usage.

Fighting Digital Banking Fraud With AI Tools

The banking industry has been faster than most in adopting artificial intelligence (AI). Banks have found that AI is extremely useful in fighting fraud because it helps to flag suspicious transactions in real time. This feature is especially useful in the high-volume business of processing card transactions for retailers and other merchants. AI helps acquiring banks and merchants determine appropriate responses when suspicious transactions are flagged.

These are among the key findings from AI In Focus: Waging Digital Warfare Against Payments Fraud, a collaboration between PYMNTS and Brighterion, a Mastercard company. We examine how acquiring banks use AI and effective merchant monitoring to combat credit, debit and prepaid card fraud. The playbook is based on a survey of 104 executives from acquiring banks in the United States from Sept. 22 to Oct. 14. The executives have leadership responsibilities and a deep understanding of the merchant debit, credit and prepaid card acceptance business. Their expertise covers risk management, transaction fraud, fraud detection/analysis and merchant monitoring.

More key findings from the study include:

Seventy-five percent of acquiring banks use AI to fight fraud, and 88% of those that do not use AI plan to adopt such systems to combat fraud within the next year. Acquirers’ increased reliance upon AI coincides with the rapid changes and increased transaction volumes that have come about from the pandemic. Online shopping has increased sharply, as has the use of credit, debit and prepaid cards and other digital and online payments.

Ninety-three percent of all acquirers say they see more fraudulent transactions now than one year ago. Acquirers also recognize the threat that fraud poses to their business, as 88% said they believe that reducing fraud is crucial to their ability to increase or maintain merchant-processing revenue. No acquirer is immune to credit and debit card fraud, but those that use AI for fraud detection face attacks somewhat less frequently than those that do not.

Forty-one percent of acquirers using AI systems to detect transaction fraud say its ability to flag suspicious transactions is its most important benefit. Another 41% say AI’s anti-fraud features are an important benefit, but that other benefits matter too. AI systems can improve operational efficiencies and enhance acquirers’ broader anti-fraud efforts. Nearly half of the acquirers that use AI to detect fraud also say it has helped them reduce the personnel needed for their anti-fraud efforts.

Acquirers are under significant pressure to protect themselves and their merchant clients from payments fraud, and they are turning to AI systems for help. This is not surprising, given the high importance of the merchant card business for acquirers and how fraud detection strongly impacts revenue growth. PYMNTS research shows a high adoption rate for AI systems and finds no signs of this trend abating. Most banks that have yet to implement these systems will have done so by this time next year. Acquirers are using AI to fight fraud and reap the benefits of increasing payments volumes.

To learn more about how acquiring banks use AI to combat payments and transaction fraud, download the playbook.

Leveraging AR Automation With Remote Work

Cash flow considerations are not limited to one sector or business type. Delays or errors in the process can have colossal ripple effects in all industries. Firms that lack the free capital to ensure timely payroll, vendor payments and a host of other necessities could find themselves in a world of issues. It is the job of accounts receivable (AR) departments to ensure that customers’ payments arrive on time and with all the necessary information or they will find their firms’ downstream cash flows to be imperiled.

Ensuring this is much harder on paper than in practice, however, with data entry errors and payment processing delays plaguing AR departments around the world. One potential answer to these AR challenges is automation, which reduces the potential for human error by implementing systems that rely on artificial intelligence (AI). These systems delegate everyday processes, like collections and invoicing, to AI-aided systems, accelerating the complex calculations that often frustrate and bog down human analysts.

The November edition of the Working Capital Playbook®, a PYMNTS and YayPay collaboration, explores the latest in the world of accounts receivable, including the challenges that AR teams face in their day-to-day business, how AR automation can help close the performance gap and how the pandemic has affected the AR field as employees are working from home.

Developments From Around the World of Accounts Receivable

Payment errors and delays can have massive ramifications for many industries, with the construction sector serving as a prime example. The construction industry loses $100 billion annually due to delays that stem from two primary sources: aging infrastructure that transfers payments via the postal mail or electronic means, and delay in payments documentation, approval and communication. Net-30 terms are typical in the construction sector, but nearly half of all firms wait up to 90 days to receive payments. This suggests that digitization and AR automation could go a long way toward helping construction firms maximize their efficiency and save costs.

AR automation is working to close this payments gap and has seen widespread implementation within the business world. The Institute of Finance and Management (IOFM) reported that the global AR automation market is projected to grow by nearly 13% annually within the next five years, up to $3.9 billion in 2026 from $1.9 billion this year. The IOFM said the pandemic has been a key growth driver in this regard. Many companies’ accounting employees are working from home, limiting the efficiency of manual AR procedures.

For more on these stories and other working capital developments, read the Playbook’s News and Trends section.

VironIT on Leveraging AR Automation to Make Remote Work More Efficient

Record numbers of employees began working from home during the past two years, but this change has brought a fair amount of challenges in the form of communication and collaboration mishaps. Accounting departments were especially affected by this, but many found that AR automation helped reduce the amount of delayed payments and errors.

In this month’s Feature Story, PYMNTS talked with Alexey Grakov, co-owner of software development company VironIT, about how AR automation kept remote work hiccups to a minimum.

Deep Dive: How Paper Payments Are Hindering AR Automation Implementation

AR automation can provide numerous benefits to corporate accounting teams, reducing payment errors and delays that can lead to big costs in downstream cash flow issues. Automated solutions’ implementation is severely hindered by the persistence of paper-based payments, however, which are still commonplace in the business world despite the increasing prevalence of digital solutions.

This month’s Deep Dive explores why paper-based payments are delaying the implementation of AR automation and what firms stand to gain from taking their payments digital and going all-in on AR automation.

About the Playbook

The Working Capital Playbook®, done in collaboration with YayPay, is your go-to monthly resource for updates on trends and changes in accounts receivable.

Reducing Fraud With Behavioral Analytics, AI

In response to the increasing severity of cyberattacks during the pandemic, IT departments incorporated stronger security processes and customer verification methods into cybersecurity defense systems.

Incorporating these extra precautions was important, as 35% of companies said digital processes resulted in fraudulent user profiles, and 38% said digital authentication adoption is more imperative now than pre-pandemic. Some measures can create friction for customers, however, which threatens both consumer satisfaction and revenue streams.

Behavioral analytics have demonstrated great success in protecting sensitive data without compromising the customer experience. Deploying a multilayered authentication approach can help examine user behavior and differentiate between genuine customers and bad actors. It also helps organize applications and allows cybersecurity employees to focus their attention on high-level threats by analyzing large masses of data to prioritize security responses.

In the latest Monetizing Digital Intent Tracker®, PYMNTS examines how behavioral analytics can help businesses protect their digital platforms from bad actors without causing irreparable harm to their client relationships.

Around the Behavioral Analytics Space

The wave of consumers who migrated to digital channels during the pandemic inspired bad actors to execute more cyberattacks. As a result, identity theft losses reached $712.4 billion in 2020, up 42% year over year from $502.5 billion. Cybersecurity professionals responded with heightened security protocols and more complex defense systems. Some digital fraud solutions negatively impact the customer experience, leaving many legitimate users frustrated and locked out of their accounts. Most promisingly, behavioral analytics uses a series of techniques to analyze customers’ digital activities and prevent fraud while reducing false positives.

Cybercriminals have learned how to evade detection and surpass many companies’ defense systems. These breaches can have damaging effects on customer trust, as 80% of breaches contained users’ personally identifiable information (PII), according to a report. The uptick in attacks has left cybersecurity professionals exhausted, especially because many of the reported threats come from genuine users who have forgotten their credentials or entered them incorrectly. Automation and behavioral analytics can ease some of the burden placed on IT departments by increasing the speed of data collection and analyzing the input of users’ information to determine whether a party is legitimate or not.

Children have inherited their parents’ poor digital hygiene habits as they continue the practice of recycling passwords across various accounts. A survey of 1,500 children ages 8 to 18 found that most participants admitted to reusing passwords. Digital service providers should implement other authentication tools, such as behavioral analytics, to combat the adverse effects of such practices and add a layer of security to traditional identity verification procedures. This account validation procedure will help protect the consumer’s information if the account’s password is compromised.

For more on these and other stories, visit the Tracker’s News & Trends.

How AI and Behavioral Analytics Reduce Friction in the Digital Authentication Process

As many citizens strive for a sense of normalcy after months of pandemic-related restrictions, cybercrime prevention remains a top priority for internet security professionals. Several technological advancements emerged during this time to help combat the innovative tactics of increasingly sophisticated bad actors. Behavioral analytics presents significant potential for fraud prevention and user authentication, explained Kostas Noreika, co-founder of the FinTech company Paysera.

To learn more about why businesses are flocking toward artificial intelligence (AI) and behavioral analytics to better understand the actions of both their clients and potential fraudsters, visit the Report’s Feature Story.

Deep Dive: How Behavioral Analytics Are Strengthening Cybersecurity Protocols Without Jeopardizing the Customer Experience 

During a time of many in-person restrictions and limitations, digital platforms showed the boundless capacity to serve consumers. The pandemic tore down physical barriers for many businesses and their customers, but the increased digitization also had negative repercussions. Bad actors became increasingly sophisticated, and as a result, 47% of organizations reported scammers and identity theft adversely impacted their operations in 2020. Cybersecurity professionals worked quickly to combat the rising fraud rates, incorporating advanced technology into their internet defense systems and hitting a few road blocks along the way.

To learn more about how behavioral analytics can reduce false positives without compromising the security software’s ability to prevent fraud, visit the tracker’s Deep Dive.

About the Tracker

The Monetizing Digital Intent Tracker®, a PYMNTS and Neuro-ID collaboration, is the go-to monthly resource for updates on trends and changes in behavioral analytics.

Vivaldi’s Browser is Behind the Wheel

Today Vivaldi Technologies launched their web browser in The Polestar 2, a battery-electric car from the pure play, Swedish premium electric car company Polestar.

As the first-ever browser available for Android Automotive OS, Vivaldi web browser is one of the first full-featured browsers available in cars. Answering one of the top desires from Polestar owners, the inclusion of a full-scale web browser in the car now allows people to browse the web as they might on their mobile devices from the comfort of their car. This takes the next step towards smarter browsing and safer driving with Vivaldi and Polestar 2’s interactive, adaptive, and transparent development for web browsing on the go. 

This breakthrough browser was designed with safety and privacy at top of mind. To ensure safety, the browser can only be used when parked, with streaming content only able to continue with audio if driving commences. Some restrictions do apply on a case-by-case basis—for example, files cannot be downloaded once the car is put into drive. On the privacy side, when logged into a Vivaldi account, browsing data may only be shared between other devices logged into the same account. However, no browsing data is stored by the car itself, and data is never shared with Polestar.

Developed exclusively for Polestar 2 by the Vivaldi team in Norway, the app brings full browser functionality to the 11-inch center display of the Polestar car and functions similarly to how a browser would on an android mobile device. An important milestone in the browser space, Vivaldi’s attributes help improve the user experiences of drivers—allowing Polestar drivers to simply go to the Google Play Store and install the browser.

Innovative Browsers: Driving to New Lengths 

Having launched in 2016, Vivaldi is a flexible, fully customizable browser that adapts to its users and offers more features than any other modern browser. Embracing the two ground rules that privacy is a default, and everything’s an option—Vivaldi aims to create new experiences at work, at home, and now even in cars. With this adventurous step into the automotive world, they have showcased their spirit for innovation and experimentation. 

Building software that protects users’ privacy and also does not track how they use it, Vivaldi believes private and secure software should be the rule rather than the exception.

On top of state-of-the-art security measures, the Vivaldi browser for Polestar 2 doesn’t compromise on innovation—boasting many features such as tabbed browsing, streaming ability, and online shopping. The browser is also built around flexibility while simultaneously embracing security, with safeguard measures including a built-in ad blocker, privacy-friendly translation tool, notes function, tracking protection, and encrypted sync functionality.

The Vivaldi browser for Polestar 2 is now available in all European, North American, and Asia Pacific markets. Vivaldi for Android Automotive OS will receive regular updates alongside its other supported platforms including Windows, macOS, Linux, and Android. Changing the way browsers interact with a variety of interfaces, Vivaldi is driving to new lengths for innovation and forging the future of web browser experiences.

Disclaimer: This article mentions a client of an ESPACIO portfolio company.

Barkibu: Bringing Health Coverage to Man’s Best Friend

Pets are a part of the family, and protecting them has become more than just an extra effort by pet owners but rather an increasingly needed contingency for animal ownership. This growth comes from the fact that pet healthcare, and by proxy pet insurance, has perpetuated a broken system to date. Many pet parents have been forced to pay through the nose in order to take care of their furry friends’ needs, with scant options for coverage—leading to most paying expensive bills out of pocket.

As a human, you go to a different doctor for different things—heart, skin, eyes, teeth, etc. Under the care of different health centers focused on these specialties, you are typically covered under the overarching insurance plan that you have. But oftentimes with our pets, we go to one provider for a variety of different services and have to pay for each one separately—which can really start to add up. This is especially expensive in the time of an accident or sudden illness, which many insurance companies shy away from coverage for pets.

Some pet insurance companies are starting to make changes for the better however, and cutting edge businesses in the industry are working to patch these disparities. In fact, the European Pet Insurance Market is estimated at 830 million USD in 2021 and is expected to grow at a CAGR of 12.8% to reach approximately 1710 million USD by 2026. With pet healthcare a somewhat new, yet growing space, the question of what should be expected comes to mind. One company, Barkibu, is setting the precedent for pet insurance in Europe and Latin America, and trailblazing new parameters for pet care in 2022. 

Artificial Intelligence for Pet Diagnosis

Barkibu’s mission is founded on the belief that most pet-health-related problems can be solved by automated consumer experiences built on top of structured pet-health data. They aim to build that future by combining several innovations to help better inform owners about caring for their pets—expanding the tools for maintaining pets’ wellbeing.

The first cutting-edge health solution by Barkibu is what they have termed as the AI Vet, which uses AI capacities to gather data and make highly informed conclusions about a pet’s health conditions. The AI Vet intelligent bot uses insight from veterinarians, as well as from pet owners, to understand what possible problems could be. Using Natural Language Processing (NLP) to glean keywords and understand symptoms, the AI is able to determine common ailments and diseases. Then the AI’s machine learning is used to match the symptoms to the most plausible root cause, drawing highly intelligent conclusions, and covering more than 90% of diseases found in dogs and cats. 

Before launching their AI Vet, Barkibu started by gathering consensual data from thousands of pet consultations completed by veterinarians. Using this insight, they then test drove the intelligent bot to see how its accuracy fared in actual pet diagnosis online. It was found that in these theoretical tests, comparing the proposed AI answer to the professional veterinarian answer, that the AI Vet was accurate 92% of the time. Through this investigative analysis, the case study testing proved that the AI Vet was ready for the real world. 

One example of a relevant use case for this technology is when you are taking care of a family or friend’s pet that you’re not familiar with. With AI Vet, people are given quick and accurate advice without having to try and call a vet and wait for precious minutes to talk to the correct person for the pet’s needs. Rather than trying to replace clinics, Barkibu is working to commence a new era of pet healthcare that is led by more precise, attainable, and immediate knowledge on pets and their medical needs. 

Combining Care Coverage With Needed Technological Innovations

Other common problems with pets’ insurance is the fact that the format offered is bundled services, with some specialists and surgeons peppered in—typically with coverage only in a very specific set of circumstances. But in the end, if the time arises when your furry friend needs help, pet owners often have no understanding of what needs to happen, or how much it might cost before they get there. This makes for a bunch of disparate costs and no comprehension of what was wrong with their companion in the first place.

This is where Barkibu is different. In addition to providing the extremely valuable resource of the AI Vet, Barkibu also offers telehealth with their pet insurance—working in collaboration with experienced operators, engineers, and product builders to make it a feasible virtual avenue for pet healthcare. This helps to even further expand pet owners’ ability to assist their dog or cat’s care, right from home, and helps to close the existing gaps of understanding with their pet’s wellbeing.

Barkibu doesn’t see itself as an insurance company, because they don’t move on the same metrics as an insurance company. With an end goal to help as many pet owners as they can, they use deep engagement with their customers through these technological capacities and are available 24/7 to answer any questions. 

This symbiotic relationship between Barkibu and their customers is a win, win—because the more they are able to answer pet health questions, the more they are able to feed their AI Vet and Telehealth platform databases. Generating valuable insight, the data creates a positive cycle that circles back to help more pets with more accurate diagnoses. 

The app uses all of these learning digital innovations to customize suggestions and healthcare for each pet and pet owner, helping pet owners to always be informed. With easy day-to-day interactions to help prevent problems, immediate attention 24/7 with the AI Vet when owners have concerning health questions, and the capacity to have a vet look at their pet via the telehealth app if need be—Barkibu is truly transforming the way we can care for our furry companions.

With Knowledge Comes Power

Changing the way that pet insurance companies are viewed, Barkibu is a business not just there in the time of accidents, but rather all of the time—for both pet and pet owners alike. This prompts pet owners to naturally trust and use their app, helping them to help you. 

The pet healthcare sector will be radically transformed with more approachable and accurate solutions for pets’ wellbeing. With knowledge comes power, and Barkibu is working to build a brighter future of care for cats and dogs through automated data consumer products—manifesting a platform to which pet owners can rest assured that their companions are covered. 

Disclaimer: This article mentions a client of an Espacio portfolio company

Why Biometric Onboarding Is a Must for AML/KYC

Digital-first businesses were better equipped to take advantage of new market opportunities unleashed during the pandemic. In the past year, 92% of consumers made an online purchase, while 85% performed banking activities online, according to PYMNTS research. In this rapidly evolving digital environment, banks are pressed to adopt technology with a digital-first and consumer-centric mindset. They need to meet customer expectations for secure access to basic services such as making money transfers via multiple digital and mobile channels.

In the December edition of the AML/KYC Tracker®, PYMNTS explores how anti-money laundering (AML)/know your customer (KYC) compliance requirements are changing with consumers growing use of digital banking services and how adopting biometrics, artificial intelligence (AI) and machine learning (ML) technologies are helping banks to remain AML/KYC compliant and keep customers secure.

Around the AML/KYC Space

Hong Kong’s banking regulator has levied a total of $5.7 million in fines on four banks — including local branches of Industrial and Commercial Bank of China and UBS — for non-compliance to AML rules. According to a statement from the Hong Kong Monetary Authority (HKMA), they failed to use appropriate AML measures for customer due diligence.

The Financial Crimes Enforcement Network (FinCEN) has released a list of its top priorities in fighting money laundering and the financing of terrorism. These priorities highlight the most prominent threats to the United States, including corruption, cybercrime, domestic and international terrorist financing, fraud, transnational criminal organizations, drug trafficking organizations and proliferation financing.

As the number of consumers onboarded remotely grows, so does financial crime, making digital identity verification crucial. Fraudsters are adopting more sophisticated scams, such as impersonating a business, which requires an upgrade in digital AML and KYC solutions. Financial institutions (FIs) are also scrambling to keep up with current AML/KYC requirements, a mandate made more urgent by the European Union’s sixth AML directive combined with stricter regulations in the U.S.

For more on these stories and other AML/KYC headlines, check out the Tracker’s News and Trends section.

Upgrade on How FIs and FinTechs Can Leverage Data-Centric AML/KYC Compliance to Secure Digital Banking

New security concerns include greater risks for identity theft and online fraud, as in-person onboarding procedures and account access give way to digital transactions.

In this month’s Feature Story, Upgrade Chief Risk and Compliance Officer Tom Curran explains how FIs and FinTechs can comply with AML/KYC regulatory requirements while ensuring customers have a frictionless digital banking experience.

Deep Dive: How AML/KYC Measures Are Evolving With Digital Banking’s Growth

FIs are pressed to provide digitally-savvy consumers with convenient, streamlined and interactive digital banking experiences while keeping personal information secure.

This month’s Deep Dive explores the challenges FIs face in meeting AML/KYC regulatory requirements as digital banking becomes more popular and how investing in AI and ML technologies can help banks remain AML/KYC compliant and keep their customers safe from online threats.

About the Tracker

The AML/KYC Tracker®, a PYMNTS and Trulioo collaboration, provides an in-depth examination of current efforts to stop money laundering, fight fraud and improve customer identity authentication in the financial services space.

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