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Updated November 17th Related Posts Link to automotive form, business form
As Valentine’s Day approaches, hearts will melt, but some will inevitably be broken by romance scams. This season of love creates an opportune moment for scammers to prey on individuals feeling lonely or seeking connection. Financial institutions should take this time to warn customers about the heightened risks and encourage vigilance against fraud. In a tale as heart-wrenching as it is cautionary, a French woman named Anne was conned out of nearly $855,000 in a romance scam that lasted over a year. Believing she was communicating with Hollywood star Brad Pitt; Anne was manipulated by scammers who leveraged AI technology to impersonate the actor convincingly. Personalized messages, fabricated photos, and elaborate lies about financial needs made the scam seem credible. Anne’s story, though extreme, highlights the alarming prevalence and sophistication of romance scams in today’s digital age. According to the Federal Trade Commission (FTC), nearly 70,000 Americans reported romance scams in 2022, with losses totaling $1.3 billion—an average of $4,400 per victim. These scams, which play on victims’ emotions, are becoming increasingly common and devastating, targeting individuals of all ages and backgrounds. Financial institutions have a crucial role in protecting their customers from these schemes. The lifecycle of a romance scam Romance scams follow a consistent pattern: Feigned connection: Scammers create fake profiles on social media or dating platforms using attractive photos and minimal personal details. Building trust: Through lavish compliments, romantic conversations, and fabricated sob stories, scammers forge emotional bonds with their targets. Initial financial request: Once trust is established, the scammer asks for small financial favors, often citing emergencies. Escalation: Requests grow larger, with claims of dire situations such as medical emergencies or legal troubles. Disappearance: After draining the victim’s funds, the scammer vanishes, leaving emotional and financial devastation in their wake. Lloyds Banking Group reports that men made up 52% of romance scam victims in 2023, though women lost more on average (£9,083 vs. £5,145). Individuals aged 55-64 were the most susceptible, while those aged 65-74 faced the largest losses, averaging £13,123 per person. Techniques scammers use Romance scammers are experts in manipulation. Common tactics include: Fabricated sob stories: Claims of illness, injury, or imprisonment. Investment opportunities: Offers to “teach” victims about investing. Military or overseas scenarios: Excuses for avoiding in-person meetings. Gift and delivery scams: Requests for money to cover fake customs fees. How financial institutions can help Banks and financial institutions are on the frontlines of combating romance scams. By leveraging technology and adopting proactive measures, they can intercept fraud before it causes irreparable harm. 1. Customer education and awareness Conduct awareness campaigns to educate clients about common scam tactics. Provide tips on recognizing fake profiles and unsolicited requests. Share real-life stories, like Anne’s, to highlight the risks. 2. Advanced data capture solutions Implement systems that gather and analyze real-time customer data, such as IP addresses, browsing history, and device usage patterns. Use behavioral analytics to detect anomalies in customer actions, such as hesitation or rushed transactions, which may indicate stress or coercion. 3. AI and machine learning Utilize AI-driven tools to analyze vast datasets and identify suspicious patterns. Deploy daily adaptive models to keep up with emerging fraud trends. 4. Real-time fraud interception Establish rules and alerts to flag unusual transactions. Intervene with personalized messages before transfers occur, asking “Do you know and trust this person?” Block transactions if fraud is suspected, ensuring customers’ funds are secure. Collaborating for greater impact Financial institutions cannot combat romance scams alone. Partnerships with social media platforms, AI companies, and law enforcement are essential. Social media companies must shut down fake profiles proactively, while regulatory frameworks should enable banks to share information about at-risk customers. Conclusion Romance scams exploit the most vulnerable aspects of human nature: the desire for love and connection. Stories like Anne’s underscore the emotional and financial toll these scams take on victims. However, with robust technological solutions and proactive measures, financial institutions can play a pivotal role in protecting their customers. By staying ahead of fraud trends and educating clients, banks can ensure that the pursuit of love remains a source of joy, not heartbreak. Learn more
As data breaches become an ever-growing threat to businesses, the role of employees in maintaining cybersecurity has never been more critical. Did you know that 82% of data breaches involve the human element1 , such as phishing, stolen credentials, or social engineering tactics? These statistics reveal a direct connection between employee identity theft and business vulnerabilities. In this blog, we’ll explore why protecting your employees’ identities is essential to reducing data breach risk, how employee-focused identity protection programs, and specifically employee identity protection, improve both cybersecurity and employee engagement, and how businesses can implement comprehensive solutions to safeguard sensitive data and enhance overall workforce well-being. The Rising Challenge: Data Breaches and Employee Identity Theft The past few years have seen an exponential rise in data breaches. According to the Identity Theft Resource Center, there were 1,571 data compromises in the first half of 2024, impacting more than 1.1 billion individuals – a 490% increase year over year2. A staggering proportion of these breaches originated from compromised employee credentials or phishing attacks. Explore Experian's Employee Benefits Solutions The Link Between Employee Identity Theft and Cybersecurity Risks Phishing and Social EngineeringPhishing attacks remain one of the top strategies used by cybercriminals. These attacks often target employees by exploiting personal information stolen through identity theft. For example, a cybercriminal who gains access to an employee's compromised email or social accounts can use this information to craft realistic phishing messages, tricking them into divulging sensitive company credentials. Compromised Credentials as Entry PointsCompromised employee credentials were responsible for 16% of breaches and were the costliest attack vector, averaging $4.5 million per breach3. When an employee’s identity is stolen, it can give hackers a direct line to your company’s network, jeopardizing sensitive data and infrastructure. The Cost of DowntimeBeyond the financial impact, data breaches disrupt operations, erode customer trust, and harm your brand. For businesses, the average downtime from a breach can last several weeks – time that could otherwise be spent growing revenue and serving clients. Why Businesses Need to Prioritize Employee Identity Protection Protecting employee identities isn’t just a personal benefit – it’s a strategic business decision. Here are three reasons why identity protection for employees is essential to your cybersecurity strategy: 1. Mitigate Human Risk in Cybersecurity Employee mistakes, often resulting from phishing scams or misuse of credentials, are a leading cause of breaches. By equipping employees with identity protection services, businesses can significantly reduce the likelihood of stolen information being exploited by fraudsters and cybercriminals. 2. Boost Employee Engagement and Financial Wellness Providing identity protection as part of an employee benefits package signals that you value your workforce’s security and well-being. Beyond cybersecurity, offering such protections can enhance employee loyalty, reduce stress, and improve productivity. Employers who pair identity protection with financial wellness tools can empower employees to monitor their credit, secure their finances, and protect against fraud, all of which contribute to a more engaged workforce. 3. Enhance Your Brand Reputation A company’s cybersecurity practices are increasingly scrutinized by customers, stakeholders, and regulators. When you demonstrate that you prioritize not just protecting your business, but also safeguarding your employees’ identities, you position your brand as a leader in security and trustworthiness. Practical Strategies to Protect Employee Identities and Reduce Data Breach Risk How can businesses take actionable steps to mitigate risks and protect their employees? Here are some best practices: Offer Comprehensive Identity Protection Solutions A robust identity protection program should include: Real-time monitoring for identity theft Alerts for suspicious activity on personal accounts Data and device protection to protect personal information and devices from identity theft, hacking and other online threats Fraud resolution services for affected employees Credit monitoring and financial wellness tools Leading providers like Experian offer customizable employee benefits packages that provide proactive identity protection, empowering employees to detect and resolve potential risks before they escalate. Invest in Employee Education and Training Cybersecurity is only as strong as your least-informed employee. Provide regular training sessions and provide resources to help employees recognize phishing scams, understand the importance of password hygiene, and learn how to avoid oversharing personal data online. Implement Multi-Factor Authentication (MFA) MFA adds an extra layer of security, requiring employees to verify their identity using multiple credentials before accessing sensitive systems. This can drastically reduce the risk of compromised credentials being misused. Partner with a Trusted Identity Protection Provider Experian’s suite of employee benefits solutions combines identity protection with financial wellness tools, helping your employees stay secure while also boosting their financial confidence. Only Experian can offer these integrated solutions with unparalleled expertise in both identity protection and credit monitoring. Conclusion: Identity Protection is the Cornerstone of Cybersecurity The rising tide of data breaches means that businesses can no longer afford to overlook the role of employee identity in cybersecurity. By prioritizing identity protection for employees, organizations can reduce the risk of costly breaches and also create a safer, more engaged, and financially secure workforce. Ready to protect your employees and your business? Take the next step toward safeguarding your company’s future. Learn more about Experian’s employee benefits solutions to see how identity protection and financial wellness tools can transform your workplace security and employee engagement. Learn more 1 2024 Experian Data Breach Response Guide 2 Identity Theft Resource Center. H1 2024 Data Breach Analysis 3 2023 IBM Cost of a Data Breach Report
As I mentioned in my previous blog, model validation is an essential step in evaluating a recently developed predictive model’s performance before finalizing and proceeding with implementation. An in-time validation sample is created to set aside a portion of the total model development sample so the predictive accuracy can be measured on a data sample not used to develop the model. However, if few records in the target performance group are available, splitting the total model development sample into the development and in-time validation samples will leave too few records in the target group for use during model development. An alternative approach to generating a validation sample is to use a resampling technique. There are many different types and variations of resampling methods. This blog will address a few common techniques. Jackknife technique — An iterative process whereby an observation is removed from each subsequent sample generation. So if there are N number of observations in the data, jackknifing calculates the model estimates on N – 1 different samples, with each sample having N – 1 observations. The model then is applied to each sample, and an average of the model predictions across all samples is derived to generate an overall measure of model performance and prediction accuracy. The jackknife technique can be broadened to a group of observations removed from each subsequent sample generation while giving equal opportunity for inclusion and exclusion to each observation in the data set. K-fold cross-validation — Generates multiple validation data sets from the holdout sample created for the model validation exercise, i.e., the holdout data is split into K subsets. The model then is applied to the K validation subsets, with each subset held out during the iterative process as the validation set while the model scores the remaining K-1 subsets. Again, an average of the predictions across the multiple validation samples is used to create an overall measure of model performance and prediction accuracy. Bootstrap technique — Generates subsets from the full model development data sample, with replacement, producing multiple samples generally of equal size. Thus, with a total sample size of N, this technique generates N random samples such that a single observation can be present in multiple subsets while another observation may not be present in any of the generated subsets. The generated samples are combined into a simulated larger data sample that then can be split into a development and an in-time, or holdout, validation sample. Before selecting a resampling technique, it’s important to check and verify data assumptions for each technique against the data sample selected for your model development, as some resampling techniques are more sensitive than others to violations of data assumptions. Learn more about how Experian Decision Analytics can help you with your custom model development.
There’s no question today’s consumers have high expectations. As financial services companies wrestle with the laws and consumer demands, here are a few points to consider: While digital delivery channels may be new, the underlying credit product remains the same. With digital delivery, adhere to credit regulations, but build in enhanced policies and technological protocols. Consult your legal, risk and compliance teams regularly. Embrace the multitude of delivery methods, including email, text, digital display and beyond. When using the latest technology, you need to work with the right partners. They can help you respect the data and consumer privacy laws, which is the foundation on which strategies should be built. Learn more
There are many factors attributing to the success of dealerships. When it comes to dealers, empirical guidance is a great way to study effective advertising. Experian brought Auto, Targeting, and the Dealer Positioning System capabilities together in a nationwide study to answer the ultimate question: what drives sales? The answers can be found in Experian’s 2018 Attribution Study. This is a wide-ranging, dealer-focused sales-driven attribution study that analyzed a few key variables. We deployed 187,701 tracking pixels to devices in 41,012 distinct households, focused on 15 digital metrics to learn about shopper behavior, and tied that digital shopping data to 2,436 vehicle sales. An industry first, Experian’s ability to combine automotive registration data, sales data, and website analytics and online behavior data puts us in a position to do something that very few companies can do. We use the household identifiers to not only see who bought a car and who bought specifically from a participating dealer, but also how they shopped the dealer’s site. Our ability to accurately identify a household’s digital behavior is based on the fact that we are a source compiler of the data and have it sitting under one roof. Others that attempt to provide this type of insight need to contract out for registrations, sales data imports from the dealership, website analytics, household identifiers, or all the above, which generally adds time to the insights. Using our sales-based approach, we can deliver unbiased attribution. Sales-based attribution is attributing credit to different advertising sources/campaigns based on actual vehicle sales – including those targeted consumers that may have purchased outside of the dealership. This is the Holy Grail of attribution for car dealers since it ties an offline activity such as buying a car back to the online advertising that’s taking up most their budgets every month. Because of that offline-online disconnect, sales-based attribution is difficult. Other automotive attribution models are typically focused on website conversions or website behavior – “what advertising can I attribute website leads to” (conversions) or “what advertising is driving users who follow the behavior that I think shows they’re likely to buy from my dealership” (website behavior.) What are the takeaways? We found three takeaways from our study. First off, we look at shopper behavior instead of isolating KPIs. Later we will discuss how traditional website metrics do not tie-in to sales. Second, we look at optimizing your paid advertising. Finally, we look at third-party investments. Although third parties drive sales, they may not be your sales. Looking at shopper behavior, not isolated KPI’s Traditional website metrics don’t tell the sales story for dealers. Traditional conversion stats are equal for buyers vs. all traffic such as VDPs or page views What this means is on average, buyers converted at a lower rate than overall website traffic. Looking solely at form submissions, hours and directions pageviews, and mobile clicks-to-call, don’t give the best view of what advertising is driving sales. With that, 98% of buyer traffic never submitted a form or went to the hours and directions page. This is a typical website conversion that dealers, vendors, and advertising agencies focus on. Since traditional web metrics don’t tell the story, there is another way. These are called High-Value Users, or HVU. They purchase at a 34% higher rate than overall traffic although they make up 11% of all traffic. High-Value Users are an Experian derived KPI. What makes someone an HVU are four different measurements. They must visit a website at least three times Spend at least six minutes on the site in total View at least eight pages in total View at least one VDP High-Value Users correlates to sales better than Vehicle Detail Page or VDP metrics. In this study, the correlation for VDP was measured at .595 which is rated a medium correlation. Meanwhile, HVU scored a .698 which is rated a high correlation. Looking at many different behavioral KPIs, like we do with our High-Value User (HVU) metric, correlates better to sales than just looking at how many VDPs you had. Driving more VDPs won’t necessarily help sales. But driving more HVUs is more likely to correlate with more sales. This also gets back to the attribution discussion above: Experian sales-based attribution is the best, and Experian’s HVUs are a good method for web-based attribution. From this attribution study, High-Value Users are a vital group for dealers to utilize. In our next post, we will go over the second and third takeaways from the attribution study: optimizing paid advertising and evaluating third-party investments.