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This article was updated on August 24, 2023. The continuous shift to digital has made a tremendous impact on consumer preferences and behaviors, with 81% thinking more highly of brands that offer multiple digital touchpoints. As a result, major credit card issuers are making creative pivots to their credit marketing strategies, from amplifying digital features in their card positioning to promoting partnerships and incentives on digital channels. But as effective as it is to reach consumers where they most frequent, credit card marketing will need to be more customer-centric to truly captivate and motivate audiences to engage.  So, what does this innovative period of credit marketing mean for financial institutions? How can these institutions stand out in a competitive, ever-changing market?  To target and acquire the right consumers, here are three credit card marketing strategies financial institutions should consider:  Maximize share of voice through targeted approaches  About half of consumers say personalization is the most important aspect of their online experience. Because today’s consumers are now expecting to engage digitally with brands, it’s important for financial institutions to not only be seen and mentioned on the right digital channels, but to deliver content that will resonate with their specific audiences. To do this, lenders must leverage fresh, comprehensive data sets to gain a more holistic view of consumers. This way, they can create targeted, customer-centric prescreen campaigns, allowing for enhanced personalization and increased response rates.  Seek new opportunities to provide value to customers  77% of Gen Zers believe having an established credit history is important to being less financially dependent on their parents. Changes in consumer needs and lifestyles provide great opportunities to deliver value to customers. For example, younger consumers starting their credit journeys may look for brands that offer financial education or tools to help them build credit. Financial institutions that are open to pivoting their strategies to adapt to these needs and behaviors are those that will succeed in attracting new customers and maintaining long-lasting relationships with existing ones.  Amplify points of differentiation in their products and marketing  Before buying a product, consumers likely want to know more about the items they are purchasing and how they compare to different players in the market. To help set their products apart from other offerings, financial institutions should clearly define their product’s key differentiators and convey them in a personalized and compelling manner.  Enhance your credit card marketing campaigns  From identifying the right prospects to saturating your targeting criteria with data-rich insights, Experian offers credit marketing solutions to help you level up your campaigns and stand out from the competition. Learn more

"Grandma, it’s me, Mike.” Imagine hearing the voice of a loved one (or what sounds like it) informing you they were arrested and in need of bail money. Panicked, a desperate family member may follow instructions to withdraw a large sum of money to provide to a courier. Suspicious, they even make a video call to which they see a blurry image on the other end, but the same voice. When the fight or flight feeling settles, reality hits. Sadly, this is not the scenario of an upcoming Netflix movie. This is fraud – an example of a new grandparent scam/family emergency scam happening at scale across the U.S. While generative AI is driving efficiencies, personalization and improvements in multiple areas, it’s also a technology being adopted by fraudsters. Generative AI can be used to create highly personalized and convincing messages that are tailored to a specific victim. By analyzing publicly available social media profiles and other personal information, scammers can use generative AI to create fake accounts, emails, or phone calls that mimic the voice and mannerisms of a grandchild or family member in distress. The use of this technology can make it particularly difficult to distinguish between real and fake communication, leading to increased vulnerability and susceptibility to fraud. Furthermore, generative AI can also be used to create deepfake videos or audio recordings that show the supposed family member in distress or reinforce the scammer's story. These deepfakes can be incredibly realistic, making it even harder for victims to identify fraudulent activity. What is Generative AI? Generative artificial intelligence (GenAI) describes algorithms that can be used to create new content, including audio, code, images, text, simulations, and videos. Generative AI has the potential to revolutionize many industries by creating new and innovative content, but it also presents a significant risk for financial institutions. Cyber attackers can use generative AI to produce sophisticated malware, phishing schemes, and other fraudulent activities that can cause data breaches, financial losses, and reputational damage. This poses a challenge for financial organizations, as human error remains one of the weakest links in cybersecurity. Fraudsters capitalizing on emotions such as fear, stress, desperation, or inattention can make it difficult to protect against malicious content generated by generative AI, which could be used as a tactic to defraud financial institutions. Four types of Generative AI used for Fraud: Fraud automation at scale Fraudulent activities often involve multiple steps which can be complex and time-consuming. However, GenAI may enable fraudsters to automate each of these steps, thereby establishing a comprehensive framework for fraudulent attacks. The modus operandi of GenAI involves the generation of scripts or code that facilitates the creation of programs capable of autonomously pilfering personal data and breaching accounts. Previously, the development of such codes and programs necessitated the expertise of seasoned programmers, with each stage of the process requiring separate and fragmented development. Nevertheless, with the advent of GenAI, any fraudster can now access an all-encompassing program without the need for specialized knowledge, amplifying the inherent danger it poses. It can be used to accelerate fraudsters techniques such as credential stuffing, card testing and brute force attacks. Text content generation In the past, one could often rely on spotting typos or errors as a means of detecting such fraudulent schemes. However, the emergence of GenAI has introduced a new challenge, as it generates impeccably written scripts that possess an uncanny authenticity, rendering the identification of deceit activities considerably more difficult. But now, GenAI can produce realistic text that sounds as if it were from a familiar person, organization, or business by simply feeding GenAI prompts or content to replicate. Furthermore, the utilization of innovative Language Learning Model (LLM) tools enables scammers to engage in text-based conversations with multiple victims, skillfully manipulating them into carrying out actions that ultimately serve the perpetrators' interests. Image and video manipulation In a matter of seconds, fraudsters, regardless of their level of expertise, are now capable of producing highly authentic videos or images powered by GenAI. This innovative technology leverages deep learning techniques, using vast amounts of collected datasets to train artificial intelligence models. Once these models are trained, they possess the ability to generate visuals that closely resemble the desired target. By seamlessly blending or superimposing these generated images onto specific frames, the original content can be replaced with manipulated visuals. Furthermore, the utilization of AI text-to-image generators, powered by artificial neural networks, allows fraudsters to input prompts in the form of words. These prompts are then processed by the system, resulting in the generation of corresponding images, further enhancing the deceptive capabilities at their disposal. Human voice generation The emergence of AI-generated voices that mimic real people has created new vulnerabilities in voice verification systems. Firms that rely heavily on these systems, such as investment firms, must take extra precautions to ensure the security of their clients' assets. Criminals can also use AI chatbots to build relationships with victims and exploit their emotions to convince them to invest money or share personal information. Pig butchering scams and romance scams are examples of these types of frauds where AI chatbots can be highly effective, as they are friendly, convincing, and can easily follow a script. In particular, synthetic identity fraud has become an increasingly common tactic among cybercriminals. By creating fake personas with plausible social profiles, hackers can avoid detection while conducting financial crimes. It is essential for organizations to remain vigilant and verify the identities of any new contacts or suppliers before engaging with them. Failure to do so could result in significant monetary loss and reputational damage. Leverage AI to fight bad actors In today's digital landscape, businesses face increased fraud risks from advanced chatbots and generative technology. To combat this, businesses must use the same weapons than criminals, and train AI-based tools to detect and prevent fraudulent activities. Fraud prediction: Generative AI can analyze historical data to predict future fraudulent activities. By analyzing patterns in data and identifying potential risk factors, generative AI can help fraud examiners anticipate and prevent fraudulent behavior. Machine learning algorithms can analyze patterns in data to identify suspicious behavior and flag it for further investigation. Fraud Investigation: In addition to preventing fraud, generative AI can assist fraud examiners in investigating suspicious activities by generating scenarios and identifying potential suspects. By analyzing email communications and social media activity, generative AI can uncover hidden connections between suspects and identify potential fraudsters. To confirm the authenticity of users, financial institutions should adopt sophisticated identity verification methods that include liveness detection algorithms and document-centric identity proofing, and predictive analytics models. These measures can help prevent bots from infiltrating their systems and spreading disinformation, while also protecting against scams and cyberattacks. In conclusion, financial institutions must stay vigilant and deploy new tools and technologies to protect against the evolving threat landscape. By adopting advanced identity verification solutions, organizations can safeguard themselves and their customers from potential risks. To learn more about how Experian can help you leverage fraud prevention solutions, visit us online or request a call

This article was updated on August 24, 2023. While the principle of “trust but verify” might work for personal relationships, “verifying before trusting” is a more appropriate approach for businesses. With consumers and companies leading more of their lives online, the use of online identity verification methods is becoming increasingly important.  According to Experian’s 2023 U.S. Identity and Fraud Report, 92 percent of businesses have a strategy in place for online identify verification. But more than half of consumers are either “somewhat confident” or “not very confident” in businesses’ ability to accurately identify them online.1 A streamlined initial verification process and continual authentication can help you build consumer trust and loyalty, as well as protect your business.  What is online identity verification?  Online identity verification is the process of digitally confirming the identity of a user. Whether you’re reviewing an account application or approving an online transaction, you need to know that the person you’re dealing with is who they claim to be.  Technology can help bring traditional identification verification methods online, such as checking a photo ID. Additionally, people and organizations have more digital “fingerprints” than ever before, which digital identity solutions can use to authenticate users with increased accuracy and less friction.  What problems do digital identity verification help solve?  A well-designed and implemented online identity verification process can help address fraud, compliance and customer demands all at once.  Verifying someone’s identity when they first create an account could be an important part of the know your customer (KYC) and customer identification program (CIP) requirements. From that moment on, continuous authentication can help detect and prevent fraud.  A proactive approach can also appeal to your customers, who may have an increasing awareness of and desire for security. Experian’s 2023 U.S. Identity and Fraud Report found that identity theft, stolen credit card information and privacy are top concerns when conducting activities online.1  Balancing the need for identity verification with a smooth online experience can be challenging. Customers may abandon a cart if identification requirements aren’t easy and fast, and may look for new services altogether if they’re repeatedly asked to authenticate themselves. But the challenge also presents an opportunity for companies that can leverage online identity verification services and methods to verify users’ identities accurately and discreetly.  Online identity verification methods  There are multiple ways to verify someone’s identity, but some of the most popular online identity verification methods include:  Personally identifiable information. Including their name, address, email address and phone number that can be checked against existing databases.  Mobile network operator data. A service that verifies a person’s mobile phone identity. For instance, this can help verify the name, address, device details and other information associated with a phone number.  Document verification. There are services that ask consumers to snap and upload a picture of the required document, like a driver’s license, passport, visa or national ID card. These may be verified with 2D or 3D facial recognition with liveness detection (e.g., verifying the user is human) or validating whether the document is real by verifying things like magnetic ink, the machine-readable zone and the barcode are genuine. One-time passwords. A one-time password is sent to a user’s phone or email during an application process to verify that they can access the account or device. Multifactor authentication. A service for existing users who can verify their identity with a combination of different factors, such as a password or biometrics (a method that measures unique physiological characteristics using fingerprints and face recognition). Knowledge-based association questions. These are questions that users answer to verify their identity. The questions may be based on their previous answers to “secret questions” or information from a credit bureau. Behavioral analysis. A service that verifies identity by comparing how a user interacts with a website or app to their previous behavior or an average user’s behavior. Environmental attributes, such as time and location, may also be considered. This technique requires no effort from the consumer. To keep up with increasing consumer and business demand, online identity verification processes may use artificial intelligence and machine learning techniques to complement the digital and manual processes. Some methods, such as consistency checks on a device and behavioral biometric assessments, can also help offer an “invisible” approach to verification. Even small behavioral traits, such as a user’s scrolling style or finger pressure, could be important data points. These invisible methods may be welcomed as a low-friction approach by consumers, who are increasingly aware of the lack of security that comes from only using passwords as an identity verification method. In Experian’s 2023 U.S. Identity and Fraud Report, 85 percent of consumers said they felt most secure using physical biometrics, followed by behavioral biometrics (81 percent) and payment or identity data from mobile wallets (80 percent), respectively.1 How Experian can help Experian is a global leader in identity verification and fraud detection services. We offer a layered approach that draws on different verification methods, including credit, device, non-traditional and user-provided data. Step-up authentication can add additional verification requirements based on how risky a user appears or the action they’re trying to take. The approach gives your trusted users a lower-friction experience while helping you detect multiple types of fraud and address CIP discrepancies. At the same time, your customers are assigned a unique and persistent identity, which can give you a single, consolidated view of your customers based on data from different platforms. Using these insights from identity resolution, you can deliver a personalized experience that surprises and delights. Given that 70% percent of consumers say it’s extremely or very important for businesses to accurately identify them online, doubling down on the use of online identity verification methods is a smart business practice.1 Learn more about Experian’s identity verification solutions and Experian VerifyTM. 1 (Experian). 2023 U.S. Identity and Fraud Report.