Tech Today

Did you miss these January business headlines? We’ve compiled the top global news stories that you need to stay in-the-know on the latest hot topics and insights from our experts. Next-gen AI analytic apps in credit In this Lendit Fintech webinar about the future of AI analytics in credit, Srikanth Geedipalli, SVP of Global analytics and AI, joins a panel of experts to explain how Experian deals with delinquencies and retains customers using a proactive approach. A successful DevOps strategy is more than just technology Dr Mark D. Spiteri writes on the Forbes Technology Council about how Experian has embraced DevOps culture to not only improve internal IT processes, but also to reshape the mindset of product development teams. 7 payments trends for 2022 as innovation climbs David Bernard, SVP Global Decision Analytics, talks to Payments Dive about cross-border services, BNPL and cybersecurity tools, and how there will be no shortage of innovation and competition in the payments industry as businesses and their regulators shape new digital tools. Deepfakes – the good, the Bad, and the ugly In this Forbes article, Eric Haller, VP & General Manager, Identity, Fraud & DataLabs, talks about how the creation of deepfakes can be thought of as the latest development in the ongoing battle between business and counterfeiting. Stay in the know with our latest research and insights:

Interview with Donna DePasquale, EVP and GM of Global Decisioning, on winning a 2021 Bronze Stevie Award for Supporting Women and Employee Resource Groups Donna DePasquale, Executive Vice President and General Manager of Global Decisioning, has been awarded a bronze Stevie® Award in the “Women Helping Women – Business” category for 2021 in honor of her work supporting women in Decision Analytics and overseeing numerous employee resource groups across the company. She spoke about this with the Global Insights Blog. Q: Why did you think your work on helping women was worthy of this award? A: I’m a first-generation American and the first in my family to go to college. I knew since business school that I thought and acted differently from the other students, but that’s how I knew that I could add value, and that’s what I’ve always aimed to impart to other women wherever I’ve worked. I’ve been at Experian for many years and have always advocated for women at all levels of the organization. I have strived to be a mentor and championed women for growth in what is traditionally a male-dominated industry. And I’ve also tried to lead by example and with compassion. I’m a firm believer that the best results come from effective collaboration and open communication. I’ve been very lucky in my career and I’ve always been encouraged to express and share my point of view. At Experian, I try to pay that forward by encouraging all voices, and, in particular, women’s voices. Q: What did the Stevie Awards cite when you won? A: In 2018, we launched the Accelerated Development Program (ADP) to identify and mentor more women business leaders within the company. I worked with Experian’s Global Decision Analytics HR Director Richard Teague to develop this program. ADP welcomes mentees from all functions in the business. Each mentee is paired with a senior mentor who they regularly meet with for practical, on the job guidance and longer term career coaching. The mentees also participate in a variety of activities to develop hard and soft business skills. So far, the ADP has supported 44 mid-career, high-potential women on the Global Decision Analytics team in a leadership training program, and, on average, half of the women who participate are promoted within two years. The ADP complements another initiative which is important for many of our employees. We renewed our focus on DE&I in Global Decision Analytics a few years ago. We now offer five employee resource groups, which are Mental Health, Neurodiversity and Disability, LGBTQ+, Race and Ethnicity, and Gender which is focused on “Women in Experian.” These resource groups have played a valuable role for employees during the pandemic and during personal challenges. Q: Can you tell us more about the Stevie Awards? A: The awards, which are given in a range of different categories for small, medium, and large businesses, have been presented since 2002 for notable achievements in business to organizations and individuals in more than 60 nations. More on working at Experian

Mike Gross, VP of Applied Fraud Research & Analytics, takes a look at the seven top global fraud predictions for 2022. A new wave of deep fake synthetic identity fraud Fraud-as-a-Service is just a click away Real-time payments = faster fraud Fintech growth comes at a cost The two-fold reality of ransomware attacks Supply chain issues expand marketplace scams Digital identity’s convergence of identity verification and fraud detection Digital acceleration is transforming the way financial services providers connect with consumers. The rise of Fintechs, cryptocurrency, and embedded finance options from alternative lenders has changed the face of the financial services industry, and a secure but seamless customer experience has become the gold standard for businesses. Driving this demand is consumers, led firstly by a natural shift towards digital encouraged by disrupter technology providers and their easy-to-use products, and secondly by the pandemic-induced online boom. But with these changes come opportunities. And not always positive ones. As businesses grapple with how to keep up with digital demand from consumers, they are also dealing with an evolving fraud landscape, with online payment fraud losses alone set to exceed $206 billion between 2021 and 2025*. Fortunately, advancements in fraud detection and prevention methods have also accelerated, with machine learning and AI enabling businesses to keep pace with rapidly evolving fraudsters. But how have such rapid changes in the industry impacted criminal activity in this space? We look at seven key global fraud predictions for 2022. A new wave of deep fake synthetic identity fraud 2021 has seen a surge in deep fake identity fraud, and that looks set to continue. The development of AI to impersonate consumers’ voices and faces is becoming more prevalent, making it challenging for businesses to verify and authenticate identities. With recent advances in deep fake technology, fraudsters can leverage compromised identity data to bypass verification controls, and then either create new synthetic profiles with documents, facial images, and voice cloning to bypass identity authentication requirements for secure exchanges like government benefits sign ups. These deep fake tactics can impact businesses’ ability to recognize consumers across the entire lifecycle, but particularly at the point of enrolment and authentication. Detection and prevention of deep fake identity fraud involves applying a layered strategy of technical defenses along with a vigilant approach. Requiring identity data or documents in isolation is not sufficient. Organizations need to fight fire with fire by capturing digital and behavioral data to complement identity controls, then using AI and machine learning to analyze interactions and spot fraud. Fraud-as-a-Service is just a click away The use of automated bots by fraudsters to impersonate businesses and socially engineer their customers is also growing rapidly. As fraud controls become even more effective at thwarting traditional attacks, fraudsters see an opportunity to evolve their tactics and capitalize on advances in voice bots. In 2022 and beyond, a large portion of fraudulent transactions will be submitted by legitimate consumers who are being socially engineered to not only provide data, but to use their own devices to submit what they believe are legitimate transactions. Banks globally are already witnessing the start of this trend, as fraudsters can now purchase bots to contact consumers, impersonate their banks, retrieve one-time passwords, and forward those codes to fraudsters to complete fraudulent transactions. Historically, fraudsters couldn’t scale this type of attack to manage thousands of calls to consumer victims, but now they can just hire a bot that sounds and acts just like a bank reaching out to their customers. As a result of this success and the cost effectiveness of bots, fraudsters are expanding operations to impersonate every type of business, from retailers to government organizations. Real-time payments = faster fraud Faster money often means faster fraud. Real-time payments (RTP) increased by 41% between 2019 and 2020 and are set to rise again by 23% between 2020 and 2025*. From mobile payments all the way to Buy Now Pay Later, RTPs have provided ample opportunity for fraudsters to quickly monetize and cash-out – converting money to other forms of currency like crypto and then laundering the funds through multiple fraudulently-established accounts. The lack of regulation in cryptocurrency makes it an especially attractive target for fraudulent activity because attackers can more easily remain anonymous and funnel funds across currencies in mere seconds. Crypto exchange platforms have profited from the unregulated environment but are starting to pay the price when it comes to fraud losses. The speed of real-time payments presents unique challenges to businesses because they often can’t be revoked or easily traced, so detection can be more difficult. But the demand for RTP is only increasing, so consistent regulations need to be in place and organizations must be able to accurately verify and authenticate identities and transactions across channels in seconds to detect criminals preying on these faster payment methods. Fintech growth comes at a cost Buy Now Pay Later has exploded over the last year. Alternative lenders now dominate the retail landscape, embedding themselves in customer journeys, offering consumers fast and easy credit, and minimizing fraud liability for merchants. But these disruptive businesses offering tailored financial products based on vast amounts of customer data have the potential to leave the door wide open to criminals. A frictionless customer experience and easy-to-use technology has allowed these nimble businesses to attract millions of customers, and with it, huge volumes of fraud. According to Aite-Novarica Group, Fintechs have an average fraud rate of around 0.30%, which is double that of credit cards that average 0.15-0.20%. 2022 is likely the year that Fintechs put risk at the forefront of strategy. Without the right identity and fraud protections in place across their websites and apps, they not only risk fraud losses, but they could also damage brand reputation. And without quick, comprehensive fraud reporting back to the businesses they serve, they also risk enabling even more downstream fraud attacks. The two-fold reality of ransomware attacks As businesses experience extortion in the form of weaponized malware, the sophisticated nature of AI used in ransomware attacks is rapidly evolving, allowing attackers to be even more successful at extracting data and wreaking havoc. A business’s data is the primary commodity that the fraudsters use to negotiate ransom payments, but the stolen data of that business’s customers is often forgotten, which can be an even greater concern. This growth in ransomware and the availability of sensitive consumer and business data will not only drive attacks in 2022. It will likely change the nature and depth of those frauds using newly-available data such as business financials or consumer medical conditions or employment details in more pervasive attacks. Organizations falling victim to ransomware must understand all of the data that has been compromised and should notify its customers so they can take steps to prevent future identity or other fraud attacks. Supply chain issues expand marketplace scams We expect to see more issues with marketplace fraud as supply chain issues and inflation persist through 2022. Where there are supply gaps, fraudsters will meet the pent-up demand with products that don’t exist, scamming customers to part with money for nothing in return. In the current marketplace environment, it’s easy to set up a fake business with positive reviews. And because consumers have no way to verify the authenticity of a business, they roll the dice on what seems too-good-to-be-true, lose money, and then try to recoup funds from their financial provider. This is another area where BNPL providers will end up bearing responsibility for a lot of retail fraud in 2022, as they take on liability for the fraud and credit losses that fueled their rapid growth. Digital identity’s convergence of identity verification and fraud detection Password-free experiences led by the ubiquitous smartphone and the ability to make real-time payments has resulted in a demand for a seamless, uninterrupted customer journey. But central to all of this is identity authentication. As identity verification and fraud detection continue to converge, the big question is, how can a secure, consumer-friendly approach to digital identity be adopted and regulated, and by whom? The announcement of the European Digital Identity scheme shows that governments are beginning to move in this direction, but there is still a long way to go. As authentication and onboarding systems continue to be targeted by fraudsters, the bid to create secure, reusable digital identities to enable more seamless commerce and to mitigate fraud and criminal activity becomes more critical. This is a concept that is dominating the conversation and one that we expect to play a big role in fraud prevention in 2022 and beyond. *Juniper Research Stay in the know with our latest research and insights:

Did you miss these December business headlines? We’ve compiled the top global news stories that you need to stay in-the-know on the latest hot topics and insights from our experts. How are companies responding to consumer behavior? Nasdaq Trade Talk's Jill Maladrino talks to Steve Wagner, Global Managing Director of Decision Analytics, about the increase in online activity over the course of the pandemic, how inflation can impact brand loyalty, and why businesses need to respond to consumer demand with better customer experience and fraud prevention. Q&A: Why the increased use of digital transactions is here to stay David Bernard, SVP of Strategy, Marketing and Digital, talks to Digital Journal about how businesses should be approaching the increase in digital transactions using advanced analytics and decisioning technologies to improve the digital customer experience and grow their businesses. How criminals are using synthetic identities for fraud Dark Reading's The Edge talks to David Britton, VP of Industry Solutions, about why businesses must improve their fraud detection and prevention protocols to detect synthetic identities and ensure that they are protecting their consumers' personal information. Latest retail trends: AI is on the up, consumer loyalty is heading down Digital Journal looks at Experian's latest research that uncovers how businesses are incorporating machine learning and artificial intelligence into everyday operations and investments in response to an upward trend in online activity and a downward trend in customer loyalty. Stay in the know with our latest research and insights:

Transaction data is some of the most valuable data a financial institution holds. By understanding how and where customers are spending money, businesses can leverage that insight to provide exactly the right next service or cross-sell product that a customer will most likely use. With open banking, this data is becoming democratized. It allows customers to give other institutions and businesses permission to access the data, which helps mid-market lenders and fintechs compete on the same playing field as the larger banks. In addition to spurring competition and innovation, it offers the potential for greater financial inclusion to people who struggle to gain access to credit due to a lack of information on their financial track record. The impact of open banking can’t be understated. According to Accenture, it will account for roughly $416 billion in revenue across the top 20 economies once open banking is fully online. And that day is closer than you might think; a survey by Know-It revealed that 55% of UK credit providers said they plan to adopt open banking in 2021, while 93% of businesses expect to adopt the data-sharing initiative within the next 12 months. While open banking was created to give customers more control over their data, the ability for institutions to leverage shared data creates the potential for data-rich services that the industry is only starting to explore. The more that banks integrate data into their services, and the more that technology firms use data to offer financial services, the more the lines between the two will blur. The role of decision analytics in open banking The key to incorporating a successful open banking approach will be leveraging the right analytics tools for better decisions. Using real-time analytics and advanced decisioning logic so lenders can effectively leverage the data available through open banking initiatives. Here are five ways that decision analytics will enable open banking to create new credit opportunities for customers. Better risk models. Analytical models and scorecards are the lifeblood of risk analysis. Open banking makes it possible to gather far more transactional data to add to credit risk models to better understand the true risk of each customer. More accurate predictions. Transactional insight powered by open banking and decision analytics creates a deeper, fuller view into a customer’s financial profile at origination. By using advanced analytics to determine credit scoring, affordability, income verification and other factors, institutions can make more accurate predictions about how much a customer can reasonably afford to borrow and pay back when issuing credit. Fewer risky customers. By leveraging data from across institutions, lenders can also look beyond common metrics like credit scoring and income verification to dig deeper into a borrower’s background. Sophisticated decision analytics can uncover unseen red flags for a specific borrower that may require the lender to take action. Increased revenue. Looking beyond origination, open banking can help organizations leverage decisioning analytics on an ongoing basis to better understand the needs of their customers. By continuing to analyze their data, institutions can then identify more relevant cross-sell and upsell opportunities, increasing the lifetime value of the customer. They can also create customer cohorts that allow them to identify which segments will be more likely to accept specific promotional offers across the customer journey. Better customer experience. Open banking can use decision analytics to power automation so customers can get credit decisions faster. For example, an institution can leverage this ability to automatically approve credit upgrade requests from an app instead of requiring a customer to call or come into a branch. By making it faster and easier to make these types of decisions, customers will feel better about your brand and more likely to continue giving you their business. In addition, this automation reduces time-consuming tasks, allowing service staff to focus on more complex customer requests. What does it take to leverage open banking? By its nature, open banking requires large volumes of data from multiple sources so that businesses can make real-time decisions about creditworthiness and risk. Breaking down traditional data silos is central to powering analytics and increasing credit opportunities. For traditional banks relying on legacy, on-premises infrastructure to manage data, internal data silos may be a problem, limiting the use of the data available. Many of these institutions are turning to cloud solutions to reap the benefits of open banking. Cloud integrations enable automatic, daily updates and upgrades to maintain compliance. Data security is provided by the cloud vendor, not internal IT staff, so most importantly, the cloud makes it easy to reduce operational silos by connecting data through integrations, allowing businesses to maximize the potential of open banking. The future is open Open banking has the potential to revolutionize the way financial institutions and customers think about financial services. A modern decisioning solution can leverage data across the cloud to give you the power and flexibility to incorporate open banking into operations, turning complex data into actionable insight. Download the 2021 Open Banking Survey (EMEA) Stay in the know with our latest research and insights:

Historically, identity graphs were used to drive marketing for businesses, allowing marketers to understand and target their audience with relevant content. But in recent years, identity graphs have emerged as a useful tactic to help businesses detect and prevent fraud due to the magnitude of data they collate and analyse. As fraud continues to evolve, businesses need to get creative and resourceful when it comes to fighting online fraud to keep pace with the fraudsters. Identity graphs allow businesses to map multiple data points to create individual customer profiles while highlighting connections across all customer profiles in their current portfolio. Download our latest Global Identity and Fraud Report How do identity graphs work? Identity graphs are databases that create a consolidated unique customer profile. Information is collected from different platforms, both online and offline, and merged into a single view. This process of gathering and merging information is known as identity resolution. The primary goal of identity resolution is to create a real-time, holistic view of an individual. How identity graphs can be used across different types of fraud Account Takeover: Identity graphs make it simple to tell when the same individual is logging into multiple accounts or when all data associated with a particular user account suddenly changes. Identity graphs can screen customer accounts that are suspected of having been compromised by takeover attacks. Credit Card Fraud: Identity graphs collate data from both online and offline means. Having access to this data can be hugely beneficial in preventing counterfeit credit card transactions. Identity graphs will map common links between cardholders and data such as point of sale locations or historic transactional behaviour. Understanding these behaviours means identity graphs can uncover suspicious transactions, helping to expose compromised credit cards and prevent fraud. Referral Fraud: Many businesses offer reward incentives to their customers to help drive engagement. While good intended, businesses that offer referral rewards may expose vulnerabilities to referral fraud. In referral fraud attacks, fraudsters will take advantage of the offered rewards without ever meeting the conditional requirements. Identity graphs make it possible to uncover referral fraud, for example, highlighting multiple referrals from one household. Gaming Fraud: Fraudsters will make multiple online gambling accounts to take advantage of any sign-up offers the vendor may offer. Likewise, fraudsters will often use multiple accounts to bet against themselves, ensuring they always win. Identity graphs can help track and highlight these instances flagging relationships between the multiple accounts. Synthetic ID Theft: Recently fraudsters have been turning to synthetic IDs to commit fraud, as opposed to sourcing legitimate IDs as per traditional identity theft. Fraudsters will combine personal data from multiple victims to create a new, non-existent identity that they can then use during online transactions. These new personas, and the inconsistencies they contain, can be easier spotted when identity graphs are applied. Anti-Money Laundering (AML): When fraudsters illegally obtain funds, they will recruit individuals to pass these funds from one source to another, making their origin hard to trace. Identity graphs can help organisations track financial transactions, providing a clear image of the journey the funds have taken, all the way from origin to destination. Innovative ways identity graphs are helping to detect and prevent fraud Cross-device Identification: Identifying customers through PII and digital data, through both deterministic and probabilistic matching, allows organisations to better identify the same user across multiple devices. This allows them to be treated as a single entity, highlighting suspicious anomalies in behaviours. Real-time: Our digital world is notoriously fast paced, and not known for standing still. Identity graphs operate by collating data and updating the associated customer profiles in real-time. Ensuring we always make decisions on accurate and up-to-date customer information is crucial for both regulatory and risk reasons. Fraud Rings: Identity graphs collect and link a vast magnitude of data. Examining each data point in tabular form can be a laborious task for investigators and spotting suspicious connections can prove difficult. When connections are presented within a graph, they can easily present powerful insights that can uncover fraud rings that could otherwise be missed. Stay in the know with our latest research and insights:

Did you miss these November business headlines? We’ve compiled the top global news stories that you need to stay in-the-know on the latest hot topics and insights from our experts. Online retailers work to turn pandemic buyers into loyal customers Digital Commerce 360 cites that only 73% of U.S. consumers say they're loyal to the brands they shopped with before the pandemic, down from 79% last year, according to Experian's latest wave of Global Insights research. So what does this mean for businesses? Donna DePasquale on Using Tech to Modernize Financial Services In this podcast, Donna DePasquale, EVP Global Decisioning Software, talks to eWeek about how the use of data analytics has evolved in the financial sector, the challenges involved, where we are at now, and what the future might look like. Was that for real? Delving into the deepfake reality Digital Journal spoke to David Britton, VP of Industry Solutions, on deepfake learning benefits and risks, focusing on how bad actors can deceive or manipulate consumers and businesses - and what they can both do to mitigate the dangers. Experian Finds 25 Percent Increase in Online Activity Since Covid-19 Business Information Industry Association looks at Experian's latest research and why the pandemic-accelerated increase in digital transactions is here to stay and how businesses must continue to transform their operations as they head into 2022. Stay in the know with our latest research and insights:

Did you miss these October business headlines? We’ve compiled the top global news stories that you need to stay in-the-know on the latest hot topics and insights from our experts. Best practices to detect and mitigate deepfake attacks David Britton, VP of Industry Solutions, writes for Search Security on how deepfake technology enables fraudsters to distort reality and commit financial crimes. Learn about how the technology works and what best practices to deploy to mitigate deepfake attacks. View deepfake infographic Consumers prefer biometrics to passwords, think less of brands with bad authentication Biometric Update looks at recent research from the CMO Council which found that a far greater number of consumers would choose to use biometrics for authentication ahead of passwords. This supports findings from the Global Identity and Fraud report from earlier this year. This article features an overview of authentication education resources for businesses to better understand where the industry is headed. Managing the Impact of Disinformation Via Deepfakes The Business Information Industry Association looks at why rapidly evolving technology platforms pave the way for even more creative approaches to fraudulent activity. With a focus on deepfakes, this piece looks at what businesses should do to minimise the impact by identifying areas of infiltration and creating a layered strategy of defence. Stories from around the world TDavivienda responde tras robo a cuentas que afectó a Jessica de La Peña CyberArk, Cybersecurity Awareness Month Stay in the know with our latest insights:

One of the most exciting things about financial services innovation is our growing ability to deliver personalized customer experiences. For example, consider a customer who enters a shopping center during the holiday season. By leveraging decisioning software, lenders can proactively offer that customer more credit—in real-time. The person has the financial ability to get what they need and doesn't have to experience a rejected transaction based on previous credit availability. What's behind such personalized offers? They are powered by the latest data—information that goes far beyond traditional credit ratings and references. For the holiday shopper, that may include geolocalization and behavior data that project a customer's likelihood of reaching a credit limit while shopping. The information empowers lenders to provide that personalized experience at the exact right time. But to make that possible, the data must be interoperable across systems, analytical and operational environments, and third-party data providers. Looking ahead, the financial service companies that enable this interoperability will be able to innovate faster, compete better, and scale their personalization to ultimately win more business. Why interoperability matters Our most recent Global Decisioning Research Report denotes consumers' evolving expectations and the increasingly vital role data and analytics play in meeting their needs. Financial service companies must leverage data to understand customer circumstances better, changing risk profiles and emerging credit needs, especially as we move out of the pandemic. Indeed the right data can help lenders support customers across their entire journey. But utilizing data to improve the customer experience is not as straightforward as it seems. The amount and diversity of the data available are huge. And the data required to power personalized products and experiences are not always readily accessible, well-formed, or high quality. As a result, data integration projects often take longer and cost more than many financial service companies anticipate. Legacy systems add to the complexity and expense. The evolving open standards for data interoperability are helping alleviate some of these challenges. But companies still need to determine which standards and platforms to use. Selecting the right ones can accelerate innovation and prevent expensive stops, starts, and detours down the road. Cultivating a healthy ecosystem The good news is that these challenges are surmountable. The first step is to understand where your organization is in its data interoperability journey. Then you can create a strategy that makes data-based innovation easier, faster, and more cost-effective. For example, consider: Prioritizing industry-leading open standards for interoperability. Requiring CSV and JSON data formats is smart; both are currently ubiquitous across the industry. Using standard APIs to share data. For example, Rest APIs using Swagger provide a description of the API, the data and facilitate the discoverability and use of the API. Exploring API aggregation services and marketplace platforms. These make it easy for developers to add services and for your organization to put them to use. Leveraging low-code data integration tooling. This helps you remove data silos and empower staff to navigate older, traditional data integration methods until they evolve to use open standards. These actions can make a significant impact on your company's ability to take advantage of various data sources now, as well as set your organization up for the future. Data meets decisioning Selecting the right decisioning software is a crucial way to facilitate the steps noted above. As you consider decisioning solutions, look for products that allow you to publish and consume data using open APIs and simple visual drag and drop approaches. In addition, evaluate the core data management capabilities of potential solutions, and prioritize those that can natively also support semi-structured data. For instance, applications that allow you to leverage frequently changing data sources ensure that when a source evolves, only the specific areas loading the data are impacted—not the wider solution. Lastly, as mentioned above, solutions that provide lightweight, low-code middleware allow you to leverage third-party data no matter where you’re at in your interoperability journey. Those new sources of data will inform and enhance your customer's experience.   Stay in the know with our latest research and insights:

Did you miss these September business headlines? We’ve compiled the top global news stories that you need to stay in-the-know on the latest hot topics and insights from our experts. Lending in a Two-Lane Economy Harry Singh, Senior VP, Global Decisioning, features on this CU Management podcast, discussing ways in which Credit Unions can best serve their customers with loans and other products within what Experian's latest research refers to as the two-lane economy. The deepfake-scape: How to fight fraud in the digital age This Biometric Update article by David Britton, VP of Industry Solutions, looks at why deepfakes are a big risk to businesses and consumers, and how fighting fire with fire in the form of artificial intelligence and machine learning can be the best form of defence for organizations. Focus on Data, Advanced Analytics and Decisioning Creates a Winning Strategy for Experian Global Banking and Finance announce that Experian has been ranked number 11 in the IDC FinTech Rankings Top 100 which highlights the top 100 global providers of financial technology, with the piece referring to Experian as a “rising star.” The Rise Of Voice Cloning And DeepFakes In The Disinformation Wars Forbes's Jennifer Kite-Powell uncovers that although deepfake fraud is dominant in social media, it is quickly moving into business sectors. Kite-Powell talks to David Britton, VP of Industry Solutions, about what businesses can do to counteract deepfake fraud tactics like voice-cloning. Shri Santhanam talks AI in lending On this Fintech One to One podcast from Lendit FinTech News, Shri Santhanam, Global Head of Advanced Analytics and AI, talks about how lenders in the FinTech space should be using AI and machine learning, and what key trends he has encountered through the years, and what we might expect to see in the future. Stay in the know with our latest insights:

Fraud threats continue to rise across the globe as consumers are spending record amounts of time online due to the pandemic. At the same time, emerging threats of fraud are growing, as fraudsters are taking advantage of the globally shifting economic conditions. Fraud prevention remains a top concern for both consumers and businesses alike. Anticipating future fraud risk is critical and companies are adopting more complex technology systems to ensure consumers’ financial safety. To provide a safe and convenient experience, businesses need to take a customer-first approach when evaluating the latest technology and solutions available to them. To ensure they are providing secure online experiences, businesses are turning to verification strategies using data technology and other detection methods. In fact, according to this year’s Global Identity and Fraud Report, customer recognition security strategies have become the new norm for businesses with 82 percent of companies saying they now have one in place, a 26 percent increase since the start of the pandemic. An independent research firm headquartered in Germany, KuppingerCole Analysts, released a report, Leadership Compass: Fraud Reduction Intelligence Platforms, that provides an overview of the market segment, vendor service functionality, prevention measures and innovative solutions to fraud. The report cites Experian as an overall leader, product leader, innovation leader, market leader and technology leader in fraud reduction intelligence platforms. Experian is also credited for taking a client-oriented upgrade approach and delivering other cutting-edge features while maintaining compatibility with our older platform releases. We also scored a strong positive for interoperability, usability, deployment, innovativeness, market position, financial strength and ecosystem; and a positive in security and functionality. We pride ourselves in our digital identity protection services and consumer safety, taking proactive approaches to fraud prevention and providing businesses with the necessary tools to identify risks of fraud. The report discusses fraud prevention measures and innovative solutions to fraud. According to the report, cybercrime costs will reach $10.5 trillion by 2025. The report evaluated 15 different data security and fraud prevention platforms and ranked their products, innovation, market positioning and technology in their report. All of Experian’s fraud detection and prevention services are available through our CrossCore® partner ecosystem. By combining advanced analytics, rich data assets, identity insights and fraud prevention capabilities, businesses can connect any new or existing tools and systems in one place, whether it be Experian’s, Experian’s partners or its own. With its built-in strategy design and enhanced workflow, fraud and compliance teams have more control to quickly adjust strategies based on evolving threats and business needs, which helps to improve efficiency and reduce operational costs. Learn more about the CrossCore platform.   Stay in the know with our latest research and insights:

Did you miss these August business headlines? We’ve compiled the top global news stories that you need to stay in-the-know on the latest hot topics and insights from our experts. Categorizing Fraud Types is the Key to Addressing Risk Security Magazine's Chris Ryan uses Experian research to break down why businesses need to first identify and understand the individual types of fraud before being in the position to address risk, especially when operating in an increasingly digital age. How To Protect Yourself Against Scammers and Deepfakes In this video, Philip Michael of Bold TV talks to David Britton, VP of Industry Solutions, about what fraud looks like in an AI-driven world, what exactly Deepfakes are, how they can be used in financial scams, and how Experian is using tools like AI and ML to fight back. Today’s Credit Decisioning: Navigating the Current Complexities The science of consumer credit decisioning is complex, writes Harry Singh, SVP of Global Decisioning, for Credit Union Times, but what has the pandemic done to further these complexities? This piece explains why lenders need to rethink existing models and processes to succeed in changing times. Experian Named Top Fraud Prevention Leader in International Analyst Report Research from KuppingerCole lists Experian as an overall leader in fraud reduction intelligence platforms. The research also recognized leadership in product, market and innovation, and across all other categories. Read about why this is important as fraud risks rise. How To Combat Fraudsters As The Digital World Grows In this piece for CEO World, David Britton, VP of Industry Solutions, writes about the relentless nature of fraud and why the goal of fraudsters never changes, and what businesses and individuals must to in the face of an ever-evolving fraud landscape in an increasingly digital world. Stay in the know with our latest research and insights: