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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
A vintage analysis comparing 60 or more days past due (DPD) delinquency performance at the one-year mark for mortgages originated between 2002 and 2010 shows that 2010 outperformed previous years, with a delinquency rate of 0.37 percent. The worst- performing vintage was 2006, with a 60 or more DPD delinquency rate of 3.84 percent – more than 10 times the delinquency rate of 2010. Listen to our recorded Webinar for a detailed look at the current state of strategic default in mortgage and an update on consumer credit trends. Source: Experian-Oliver Wyman Market Intelligence Reports
After increasing for the first time in nearly two years, the 30 and 60 days past due (DPD) mortgage delinquencies as a percentage of balances returned to their downward trend, with Q4 delinquency rates of 2.18 percent and 1.06 percent, respectively. This represents a decline of 3.5 percent for the 30 DPD category and a 2.8 percent decline for 60 DPD. Listen to our recorded Webinar for a detailed look at the current state of mortgage strategic default and an update on consumer credit trends from the Q4 2011 Experian-Oliver Wyman Market Intelligence Reports. Source: Experian-Oliver Wyman Market Intelligence Reports.
One of the most successful best practices for improving agency performance is the use of scorecards for assessing and rank ordering performance of agencies in competition with each other. Much like people, agencies thrive when they understand how they are evaluated, how to influence those factors that contribute to success, and the recognition and reward for top tier performance. Rather than a simple view of performance based upon a recovery rate as a percentage of total inventory, best practice suggests that performance is more accurately reflected in vintage batch liquidation and peer group comparisons to the liquidation curve. Why? In a nutshell, differences in inventory aging and the liquidation curve. Let’s explain this in greater detail. Historically, collection agencies would provide their clients with better performance reporting than their clients had available to them. Clients would know how much business was placed in aggregate, but not by specific vintage relating to the month or year of placement. Thus, when a monthly remittance was received, the client would be incapable of understanding whether this month’s recoveries were from accounts placed last month, this year, or three years ago. This made forecasting of future cash flows from recoveries difficult, in that you would have no insight into where the funds were coming from. We know that as a charged off debt ages, its future liquidation rate generally downward sloping (the exception is auto finance debt, as there is a delay between the time of charge-off and rehabilitation of the debtor, thus future flows are higher beyond the 12-24 month timeframe). How would you know how to predict future cash flows and liquidation rates without understanding the different vintages in the overall charged off population available for recovery? This lack of visibility into liquidation performance created another issue. How do you compare the performance of two different agencies without understanding the age of the inventory and how it is liquidating? An as example, let’s assume that Agency A has been handling your recovery placements for a few years, and has an inventory of $10,000,000 that spans 3+ years, of which $1,500,000 has been placed this year. We know from experience that placements from 3 years ago experienced their highest liquidation rate earlier in their lifecycle, and the remaining inventory from those early vintages are uncollectible or almost full liquidated. Agency A remits $130,000 this month, for a recovery rate of 1.3%. Agency B is a new agency just signed on this year, and has an inventory of $2,000,000 assigned to them. Agency B remits $150,000 this month, for a recovery rate of 7.5%. So, you might assume that Agency B outperformed Agency A by a whopping 6.2%. Right? Er … no. Here’s why. If we had better visibility of Agency A’s inventory, and from where their remittance of $130,000 was derived, we would have known that only a couple of small insignificant payments came from the older vintages of the $10,000,000 inventory, and that of the $130,000 remitted, over $120,000 came from current year inventory (the $1,500,000 in current year placements). Thus, when analyzed in context with a vintage batch liquidation basis, Agency A collected $120,000 against inventory placed in the current year, for a liquidation rate of 8.0%. The remaining remittance of $10,000 was derived from prior years’ inventory. So, when we compare Agency A with current year placements inventory of $1,500,000 and a recovery rate against those placements of 8.0% ($120,000) versus Agency B, with current year placements inventory of $2,000,000 and a recovery rate of 7.5% ($150,000), it’s clear that Agency A outperformed Agency B. This is why the vintage batch liquidation model is the clear-cut best practice for analysis and MI. By using a vintage batch liquidation model and analyzing performance against monthly batches, you can begin to interpret and define the liquidation curve. A liquidation curve plots monthly liquidation rates against a specific vintage, usually by month, and typically looks like this: Exhibit 1: Liquidation Curve Analysis Note that in Exhibit 1, the monthly liquidation rate as a percentage of the total vintage batch inventory appears on the y-axis, and the month of funds received appears on the x-axis. Thus, for each of the three vintage batches, we can track the monthly liquidation rates for each batch from its initial placement throughout the recovery lifecycle. Future monthly cash flow for each discrete vintage can be forecasted based upon past performance, and then aggregated to create a future recovery projection. The most sophisticated and up to date collections technology platforms, including Experian’s Tallyman™ and Tallyman Agency Management™ solutions provide vintage batch or laddered reporting. These reports can then be used to create scorecards for comparing and weighing performance results of competing agencies for market share competition and performance management. Scorecards As we develop an understanding of liquidation rates using the vintage batch liquidation curve example, we see the obvious opportunity to reward performance based upon targeted liquidation performance in time series from initial placement batch. Agencies have different strategies for managing client placements and balancing clients’ liquidation goals with agency profitability. The more aggressive the collections process aimed at creating cash flow, the greater the costs. Agencies understand the concept of unit yield and profitability; they seek to maximize the collection result at the lowest possible cost to create profitability. Thus, agencies will “job slope” clients’ projects to ensure that as the collectability of the placement is lower (driven by balance size, customer credit score, date of last payment, phone number availability, type of receivable, etc.) For utility companies and other credit grantors with smaller balance receivables, this presents a greater problem, as smaller balances create smaller unit yield. Job sloping involves reducing the frequency of collection efforts, employing lower cost collectors to perform some of the collection efforts, and where applicable, engaging offshore resources at lower cost to perform collection efforts. You can often see the impact of various collection strategies by comparing agency performance in monthly intervals from batch placement. Again, using a vintage batch placement analysis, we track performance of monthly batch placements assigned to competing agencies. We compare the liquidation results on these specific batches in monthly intervals, up until the receivables are recalled. Typical patterns emerge from this analysis that inform you of the collection strategy differences. Let’s look at an example of differences across agencies and how these strategy differences can have an impact on liquidation: As we examine the results across both the first and second 30-day phases, we are likely to find that Agency Y performed the highest of the three agencies, with the highest collection costs and its impact on profitability. Their collection effort was the most uniform over the two 30-day segments, using the dialer at 3-day intervals in the first 30-day segment, and then using a balance segmentation scheme to differentiate treatment at 2-day or 4-day intervals throughout the second 30-day phase. Their liquidation results would be the strongest in that liquidation rates would be sustained into the second 30-day interval. Agency X would likely come in third place in the first 30-day phase, due to a 14-day delay strategy followed by two outbound dialer calls at 5-day intervals. They would have a better performance in the second 30-day phase due to the tighter 4-day intervals for dialing, likely moving into second place in that phase, albeit at higher collection costs for them. Agency Z would come out of the gates in the first 30-day phase in first place, due to an aggressive daily dialing strategy, and their takeoff and early liquidation rate would seem to suggest top tier performance. However, in the second 30-day phase, their liquidation rate would fall off significantly due to the use of a less expensive IVR strategy, negating the gains from the first phase, and potentially reducing their over position over the two 30-day segments versus their peers. The point is that with a vintage batch liquidation analysis, we can isolate performance of a specific placement across multiple phases / months of collection efforts, without having that performance insight obscured by new business blended into the analysis. Had we used the more traditional current month remittance over inventory value, Agency Z might be put into a more favorable light, as each month, they collect new paper aggressively and generate strong liquidation results competitively, but then virtually stop collecting against non-responders, thus “creaming” the paper in the first phase and leaving a lot on the table. That said, how do we ensure that an Agency Z is not rewarded with market share? Using the vintage batch liquidation analysis, we develop a scorecard that weights the placement across the entire placement batch lifecycle, and summarizes points in each 30-day phase. To read Jeff's related posts on the topic of agency management, check out: Vendor auditing best practices that will help your organization succeed Agency managment, vendor scorecards, auditing and quality monitoring