It’s that time of year again – when people all over the U.S. take time away from life’s daily chores and embark upon that much-needed refresh: vacation! But just as fraud activity spikes during the holidays, there are also fraud trends suggesting spikes in fraudster activity during the summer. With consumers on vacation, identity theft becomes easier. Consumers are most likely to break their normal spending trends and break patterns established by fraud analytics; and consumers are less likely to be as attentive to elements that can help minimize fraud while out of town. There has been plenty of research to demonstrate that fraudsters perpetrate account takeover by changing the pin, address, or email address of an account. Now, fraudsters are more likely to add themselves as an authorized user to the account, which may not be considered a high-risk flag in transactional decisioning strategies. By identifying risky behaviors or patterns outside of a consumer’s normal behavior and an engaging in a knowledge based authentication session with the consumer, it is possible to help minimize the risk of fraud. Knowledge based authentication provides strong authentication and can be part of a risk-based approach to on-going account management, protecting both businesses and consumers from being burned, at least by fraudsters, while on vacation.

By: Kari Michel On March 18th 2011 the Federal Reserve Board approved a rule amending Regulation Z (Truth in Lending) to clarify portions of the final rules implementing the Credit CARD Act of 2009. Specific to ability to pay requirements, the new rule states that credit card applications generally cannot request a consumer's "household income" because that term is too vague to allow issuers to properly evaluate the consumer's ability to pay. Instead, issuers must consider the consumer's individual income or salary. The new ruling will be effective October 2011. Given the new direction outlined in the latest rules, we've been hard at work on developing 2 income models to support these regulatory obligations and enhance the underwriting and risk assessment process – Income InsightSM and Income Insight W2SM.  Both income models estimate an individual’s income based on an individual credit report and can be used in acquisition strategies, account management review and collection processes.  Why two models? Income InsightSM estimates the consumer’s total income, including wages, investments, rentals and other income. Income Insight W2SM estimates wages only.  Check them out – and let us know what you think! We want to hear from you.

By: Kennis Wong When we think about fraud prevention, naturally we think about mininizing fraud at application. We want to ensure that the identities used in the application truly belong to the person who applies for credit, and not identity theft. But the reality is that some fraudsters do successfully get through the defense at application. In fact, according to Javelin’s 2011 Identity Fraud Survey Report, 2.5 million accounts were opened fraudulently using stolen identities in 2010, costing lenders and consumers $17 billion. And these numbers do not even include other existing account fraud like account takeover and impersonation (limited misusing of account like credit/debit card and balance transfer, etc.). This type of existing account fraud affected 5.5 million accounts in 2010, costing another $20 billion. So although it may seem like a no brainer, it’s worth emphasizing that we need to have fraud account management system and continue to detect fraud for new and established accounts. Existing account fraud is unlikely to go away any time soon.  Lending activities have changed significantly in the last couple of years. Origination rate in 2010 is still less than half of the volume in 2008, and booked accounts become riskier. In this type of environment, when regular consumers are having hard time getting new credits, fraudsters are also having hard time getting credit. So they will switch their focus to something more profitable like account takeover. In addition to application fraud, does your organization have appropriate tools and decisioning strategy to minimize fraud loss from existing account fraud?