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Gone are the days when validating scoring models was a thing you did when you got around to it. Besides that fact that the OCC wants models validated at least once a year, it’s just good business sense to make sure your tools are working as expected. At a minimum, the OCC wants back testing, stress testing, benchmarking and sensitivity analysis, but there is another aspect to validations that needs to be taken into consideration. Most lenders do not rely exclusively on a scoring model of their decisioning (or at least they shouldn’t). Whether it’s a dual score strategy or attribute overlay, additional underwriting criteria is often used to help refine and optimize decision strategies. However, those same overlays need to be incorporated into the model validation process so that the results are not misleading. VantageScore® Solutions, LLC has just published a concise white paper offering excellent examples of how to make sure your overlay criteria are an integral part of the overall validation process, ensuring your effort here are yielding the right results. And while on the topic of model validation, next time I’ll review what to do when you have no idea what to test for. Stay tuned!

It comes as no surprise to anyone that cell phone usage continues to rise, while at the same time the usage of wire lines, or what used to be affectionately known as POTS (Plain Old Telephone Service), continues to decline. Some recent statistics, supplied by the CDC show that: 34% of all households are now wireless only 25 states have rates of primary wireless exceeding 50% Landline only households is now down to only 10.2% When you couple that with churn rates for cell phones that can exceed 40% a year, it becomes paramount to find a good source for cell numbers if you are trying to contact an existing customer or collect on an overdue bill. But where can debt collectors go to find reliable cell phone numbers? The cell phone providers won’t sell you a database, there is no such thing as 411 for cell phones, nor is it likely there will be one in the near future with the aforementioned 40%+ churn rates. Each cell phone service provider will continue to protect their customer base. There are a few large compilers of cell phone numbers; they mostly harvest these numbers from surveys and sources that capture the numbers as a part of an online service—think ringtones here! These numbers can be good, at least initially, if they came with an address which enables you to search for them. The challenge is that these numbers can grow stale relatively quickly. Companies that maintain recurring transactions with consumers have a better shot at having current cell numbers. Utilities and credit bureaus offer an opportunity to capture these self-reported numbers. At our company, over 40% of self-reported phones are cell phones. However, in most cases, you must have a defined purpose as governed by Gramm Leach Bliley (GLB) in order to access them. Of course, the defined purpose also goes hand in hand with the Telephone Consumer Protection Act (TCPA), which restricts use of automatic dialers and prohibits unsolicited calls via a cell phone. Conclusion? If you are trying to find someone’s cell number for debt collection purposes, I recommend using a resource more likely to receive updates on the owner of a cell over that of compilers who are working with one time event data. In today’s world, obtaining an accurate good cell number is a challenge and will continue to be. What cell phone number resources have been most effective for you?

Contributed by: David Daukus As the economy recovers from the recession, consumers are becoming more responsible with their credit card usage; credit card debts have not increased and delinquency rates have declined. Delinquency rates as a percentage of balances continue to decline with the short term 30-59 DPD period, now at 0.9%. With mixed results, where is the profit opportunity? Further studies from Experian-Oliver Wyman state that the average bankcard balance per consumer remained relatively flat at $4,170, but the highest credit tiers (using VantageScore® credit score A and B segments) saw average balances increase to $2,422 and $3,208, respectively. It's time to focus on what you have—your current portfolio—and specifically how to: Increase credit card usage in the prime segments Assign the right lines to your cardholders Understand who has the ‘right’ spend Risk score alone doesn't provide the most accurate insight into consumer accounts. You need to dig deeper into individual accounts to uncover behavioral trends to get the critical information needed to grow your portfolio:  Leading financial institutions are looking at consumer payment history, such as balance and utilization changes. These capture a consumer’s credit situation more accurately than a point in time view. When basic principles are applied to credit data, different consumer behaviors become evident and can be integrated into client strategies. For example, if two consumers have the same VantageScore® credit score, credit card balances, and payment status, does that mean they have the same current credit status? Not necessarily so. By looking at their payment history, you can determine which direction each is heading. Are they increasing their debt or are they paying down their debt? These differences reveal their riskiness and credit needs. Therefore, with payment history added to the mix, you can more accurately allocate credit lines between consumers and simultaneously reduce risk exposure. Spend is another important metric to evaluate to help grow your portfolio. How do you know if a consumer uses primary a credit card when making purchases? Wouldn’t you want to know the right amount of credit to provide based on the consumer’s need? Insight into consumer spending levels provides a unique understanding of a consumer’s credit needs. Knowing spend allows lenders to provide necessary high lines to the limited population of very high spenders, while reducing overall exposure by providing lower lines to low spenders. Spend data also reveals wallet share—knowing the total spend of your cardholder allows you to calculate their external spend. With wallet share data, you can capture more spend by adjusting credit lines or rewards that will entice consumers to spend more using your card. Once you have a more complete picture of a consumer, adjusting lines of credit and making the right offer is much easier. Take some of the risk out of managing your existing customers and finding new ones. What behavioral data have you found most beneficial in making lending decisions?   Source: Experian-Oliver Wyman Market Intelligence Reports

I'm here in Vegas at the Mobile2020 conference and I am fascinated by my room key. This is not the usual “insert in to the slot, wait for it turn green or hear it chime” key cards, these are “tap and hold to a door scanner till the door opens” RFID key card. It is befitting the event I am about to attend – Money2020 – the largest of its kind bringing together over 2000 mobile money aficionados, strategists and technologists from world over for a couple of days to talk about how payment modalities are shifting and the impact of these shifts to existing and emerging players. Away from all the excitement of product launches, I hope some will be talking about one of the major barriers for consumer adoption towards alternate payment modalities such as mobile – security and fraud.  I was in Costa Mesa last week and in the process of buying something for my wife with my credit card, triggered the card fraud alert. My card was declined and I had to use a different card to complete my transaction. As I was walking out, my smartphone registers a text alert from the card issuer – asking me to confirm that it was actually I who attempted the transaction. And If so, Respond by texting 1 – if Yes Or 2 – if No. All good and proper up till this point. If someone had stolen my card or my identity, this would have been enough to stop fraud from re-occurring. In this scenario the payment instrument and the communication device were separate – my plastic credit card and my Verizon smartphone. In the next couple of years, these two will converge, as my payment instrument and my smartphone will become one. At that point, will the card issuer continue to send me text alerts asking for confirmation? If instead of my wallet, my phone was stolen – what good will a text alert to that phone be of any use to prevent the re-occurrence of fraud? Further if one card was shut down, the thief could move to other cards with in the wallet – if, just as today, there are no frameworks for fraud warnings to permeate across other cards with in the wallet. Further, fraud liability is about to shift to the merchant with the 2013 EMV Mandate. In the recent years, there has been significant innovation in payments – to the extent that we have a number of OTT (Over the Top) players, unencumbered by regulation, who has been able to sidestep existing players – issuers and card networks, in positioning mobile as the next stage in the evolution of payments. Google, PayPal, Square, Isis (a Carrier consortium formed by Verizon, T-Mobile and AT&T), and a number of others have competing solutions vying for customer mind share in this emerging space. But when it comes to security, they all revert to a 4 digit PIN – what I call as the proverbial fig leaf in security. Here we have a device that offers a real-time context – whether it be temporal, social or geo-spatial – all inherently valuable in determining customer intent and fraud, and yet we feel its adequate to stay with the PIN, a relic as old as the payment rails these newer solutions are attempting to displace. Imagine what could have been – in the previous scenario where instead of reaching for my card, I reach for my mobile wallet. Upon launching it, the wallet, leveraging the device context, determines that it is thousands of miles away from the customer’s home and should score the fraud risk and appropriately ask the customer to answer one or more “out-of-wallet” questions that must be correctly answered. If the customer fails, or prefers not to, the wallet can suggest alternate ways to authenticate – including IVR. Based on the likelihood of fraud, the challenge/response scenario could include questions about open trade lines or simply the color of her car. Will the customer appreciate this level of pro-activeness on the issuer’s part to verify the legality of the transaction? Absolutely. Merchants, who so far has been on the sidelines of the mobile payment euphoria, but for whom fraud is a real issue affecting their bottom-line, will also see the value. The race to mobile payments has been all about quickly shifting spend from plastic to mobile, and incenting that by enabling smartphones to store and deliver loyalty cards and coupons. The focus need to shift, or to include, how smartphones can be leveraged to address and reduce fraud at the point-of-sale – by bringing together context of the device and a real-time channel for multi-factor authentication. It’s relevant to talk about Google Wallet (in its revised form) and Fraud in this context. Issuers have been up in arms privately and publicly, in how Google displaces the issuer from the transaction by inserting itself in the middle and settles with the merchant prior to firing off an authorization request to the issuer on the merchant’s behalf. Issuers are worried that this could wreak havoc with their inbuilt fraud measures as the authorization request will be masked by Google and could potentially result in issuer failing to catch fraudulent transactions. Google has been assuaging issuer’s fears on this front, but has yet to offer something substantial – as it clearly does not intent to revert to where it was prior – having no visibility in to the payment transaction (read my post here). This is clearly shaping up to be an interesting showdown – would issuers start declining transactions where Google is the merchant of record? And how much more risk is Google willing to take, to become the entity in the middle? This content is a re-post from Cherian's personal blog: http://www.droplabs.co/?p=625

Part 2:  Common myths about credit risk scores and how to educate consumers In light of what I've heard in the marketplace through the years, I wanted to provide some information to help 'debunk' some common myths about credit scores. Myth: There is only one credit score Reality: There are multiple credit scores that lenders can use to evaluate consumer credit worthiness. As noted in a recent New York Times article, there are 49 FICO score models. Make sure your customers know that an underwriting decision is based on more than just a credit score—multiple factors are evaluated to make a lending decision. The most important thing a consumer can do is ensure their credit report is accurate. Myth:  The probability of default remains constant for a credit score over time Reality:  The probability of default can shift dramatically based on macro-economic conditions. In 2005, a score of 700 in any given model, may have had a probability of default of 2 percent, while in 2009, the same score could have had a probability of default of 8 percent. This underscores the value of conducting an annual validation of the credit model you are using to ensure your institution is making the most accurate lending decisions based on your risk tolerance. One of the benefits of utilizing the VantageScore® model, is that VantageScore® Solutions, LLC, produces an annual validation so you can ensure your institution is adjusting your strategies to meet changing economic conditions. Myth:  If the underlying credit report is the same at each credit reporting company, I will have the same score at each company Reality:  Traditional credit scoring models are completely different at each credit reporting company, which leads to vastly different scores or probabilities of default based on the same information. As a risk manager, this is very frustrating, as I may not understand which score most accurately assess the consumer’s probability of default. The only model that is the same across all credit reporting agencies is the VantageScore® model, where this is a patented feature that ensures the lender receives a consistent score (probability of default) across all bureau platforms. I hope these brief examples help clear up some confusion about credit scores. In Part 3 of this series, I will outline how to evaluate the risk of traditionally unscoreable consumers. If you have any thoughts or experiences from a lending perspective, please feel free to share them below.   Courtesy Why You Have 49 Different FICO Scores in the August 27, 2012 issue of the New York Times

By: Kyle Aiman Let’s face it, debt collectors often get a bad rap.  Sure, some of it is deserved, but the majority of the nation’s estimated 157,000 collectors strive to do their job in a way that will satisfy both their employer and the debtor.  One way to improve collector/debtor interaction is for the collector to be trained in consumer credit and counseling. In a recent article published on Collectionsandcreditrisk.com, Trevor Carone, Vice President of Portfolio and Collection Solutions at Experian, explored the concept of using credit education to help debt collectors function more like advisors instead of accusers.  If collectors gain a better understanding of consumer credit – how to read a credit report, how items may affect a credit score, how a credit score is compiled and what factors influence the score – perhaps they can offer suggestions for improvement. Will providing past-due consumers with a plan to help improve their credit increase payments?  Read the article and let us know what you think!

By: Mike Horrocks It has been over a year that in Zuccotti Park the Occupy Wall Street crowd made their voices heard.  At the anniversary point of that movement, there has been a lot of debate on if the protest has fizzled away or is still alive and planning its next step.  Either way, it cannot be ignored that it did raise a voice in how consumers view their financial institutions and what actions they are willing to take i.e. “Bank Transfer Day”. In today’s market customer risk management must be balanced with retention strategies.  For example, here at Experian we value the voice of our clients and prospects and I personally lead our win/loss analysis efforts.  The feedback we get from our customers is priceless.   In a recent American Banker article, some great examples were given on how tuning into the voice of the consumer can turn into new business and an expanded market footprint. Some consumers however will do their talking by looking at other financial institutions or by slowly (or maybe rapidly) using your institution’s services less and less.   Technology Credit Union saw great results when they utilized retention triggers off of the credit data to get back out in front of their members with meaningful offers.     Maximizing the impact of internal data and spotting the customer-focused trends that can help with retention is even a better approach, since that data is taken at the “account on-us” level and can help stop risks before the customer starts to walk out the door. Phillip Knight, the founder of Nike once said, “My job is to listen to ideas”.  Your customers have some of the best ideas on how they can be retained and not lost to the competitors.  So, think how you can listen to the voice and the actions of your customers better, before they leave and take a walk in the park.

By: Maria Moynihan State and local governments responsible for growth may be missing out on an immediate and sizeable revenue opportunity if their data and processes for collections are not up to par. The Experian Public Sector team recently partnered with Governing Magazine to conduct a nationwide survey with state and local government professionals to better understand how their debt collections efforts are helping to address current revenue gaps. Interestingly enough, 81% stated that the economic climate has negatively impacted their collections efforts, either through reduced staff or reduced budgets, while 30% of respondents are actively looking for new technologies to aid in their debt collections processes. New technologies are always a worthwhile investment. Operational efficiencies will ultimately ensue, but those government organizations who are coupling this investment with improved data and analytics are even better positioned to optimize collections processes and benefit from growth in revenue streams. No longer does the public sector need to lag behind the private sector in debt recovery. With the total outstanding debt among the 50 states reaching an astounding size of approximately $631 billion dollars, why delay? Check out Experian's guide to improving debt collections efforts in the public sector. What is your agency doing to capitalize on revenue from overdue obligations?

By: Teri Tassara Negative liquidity, or owing more on your home than its value, has become a much too common theme in the past few years.  According to CoreLogic, 11 million consumers are underwater, representing 1 out of 4 homeowners in the nation.  The irony is with mortgage rates remaining at historic lows, consumers who can benefit the most from refinancing can’t qualify due to their negative liquidity situation. Mortgage Banker’s Association recently reported that approximately 74% of home loan volumes were mortgage re-finances in 2Q 2012.  Consumers who have been able to refinance to take advantage of the low interest rates already have, some even several times over.  But there is a segment of underwater consumers who are paying more than their scheduled amount in order to qualify for refinancing – which translates to growth opportunity in mortgage loan volume. Based on an Experian analysis of actual payment amount on mortgages, actual payment amount was reported on about 65% of open mortgages (actual payment amount is the amount the consumer paid the prior month).  And when the actual payment is reported, the study found that 82% of the consumers pay within their $100 of scheduled payment and 18% pay more than their scheduled amount. Actual payment amount information as reported on the credit file, used in combination with other analytics, can be a powerful tool to identify viable candidates for a mortgage refinance, versus those who may benefit from a loan modification offer.  Consumers methodically paying more than the scheduled payment amount may indicate that the consumer is trying to qualify for refinancing.  Conversely, if the consumer is not able to pay the scheduled payment about, that consumer may be an ideal candidate for a loan modification program.   Either way, actual payment amount can provide insight that can create a favorable situation for both the consumer and the lender, mitigating additional and unnecessary risk while providing growth opportunity. Find other related blog posts on credit and housing market trends.

What does the mortgage interest rate, currently at an all time low of 3.55% (for 30 yr. fixed), mean for financial institutions? According to the latest Experian-Oliver Wyman Market Intelligence Report, 75% of the mortgage originations are refinancing vs. purchasing loans. As mortgage rates decrease, financial institutions face losing mortgage loans to other lenders in the refinance climate. Consumers are looking to save money and mortgage payments are generally the largest monthly expense.  Economic indicators, such as decreasing credit card and mortgage delinquency rates, reveal that consumers are more watchful of their spending and more closely managing their debt. Overall consumer debt has come down 11% from the peak in 2008, with a majority coming from the lowest VantageScore® model credit populations. Consumer confidence continues to drop, indicating consumer pessimism due to increasing gas prices and declining job growth. Given the mixed trends in the economic landscape, we can conclude that some consumers are still doubtful on economic recovery and will seek ways to save more and pay down their debt. Consumers with existing mortgages will most likely take advantage of the lower mortgage rates and refinance. So how can financial institutions help prevent attrition? With the current economic situation, managing retention efforts on a daily basis is imperative to retaining consumers. By monitoring their portfolio and receiving information daily, financial institutions are quickly informed if an existing mortgage client is shopping for a new mortgage with another lender, enabling them to act swiftly to retain the business. Information obtained from daily monitoring of accounts helps financial institutions speak with customers more intelligently about their needs. Because of this competitive environment, and often irrelevance of brand loyalty, financial institutions need to build relationships and increase customer loyalty by quickly meeting the financial needs of their most profitable customers. To demonstrate how taking daily actions can help boost loyalty, reduce attrition, and increase profitability, the Technology Credit Union recently revealed how they obtained a 788% ROI. Access the case study here. What efforts has your institution taken to reduce attrition over the past year?   VantageScore is a registered trademark of VantageScore Solutions, LLC.

By: Kyle Aiman For more than 20 years, creditors have been using scores in their lending operations.  They use risk models such as the VantageScore® credit score, FICO or others to predict what kind of risk to expect before making credit-granting decisions. Risk models like these do a great job of separating the “goods” from the “bads.” Debt recovery models are built differently-their job is to predict who is likely to pay once they have already become delinquent. While recovery models have not been around as long as risk models, recent improvements in analytics are producing great results.  In fact, the latest generation of recovery models can even predict who will pay the most. Hopefully, you are not using a risk model in your debt collection operations.  If you are, or if you are not using a model at all, here are five reasons to start using a recovery model: Increase debt recovery rates – Segmenting and prioritizing your portfolios will help increase recovery rates by allowing you to place emphasis on those accounts most likely to pay. Manage and reduce debt recovery costs – Develop treatment strategies of varying costs and apply appropriately. Do not waste time and money on uncollectible accounts. Outsource accounts to third party collection agencies – If you use outside agencies, use recovery scoring to identify accounts best suited for assignment; take the cream off the top to keep in house. Send accounts to legal – Identify accounts that would be better served using a legal strategy versus spending time and money using traditional treatments. Price accounts appropriately for sale – If you are in a position to sell accounts, recovery scoring can help you develop a pricing strategy based on expected collectibility. What recovery scoring tools are you using to optimize your company's debt collection efforts? Feel free to ask questions or share your thoughts below.   VantageScore® is a registered trademark of VantageScore Solutions, LLC.

By: Uzma Aziz They say, “a bird in the hand is better than two in the bush” …and the same can be said about customers in a portfolio. Studies have shown time and again that the cost of acquiring a new financial services customer is many times higher than the cost of keeping an existing one. Retention has always been an integral part of portfolio management, and with the market finally on an upward trajectory, there is all the more need to hold on to profitable customers. Experts at CEB TowerGroup are forecasting a combined annual growth rate of over 12% for new credit cards alone through 2015. Combine that with a growing market with better-informed and savvy customers, and you have a very good reason to be diligent about retaining your best ones. Also, different sized institutions have varying degrees of success. According to a study by J.D. Power & Associates, in 2011 overall, 9.6% of customers indicated they switched their primary bank account during the past year, up from 8.7% a year ago. Smaller banks and credit unions did see drastically lower attrition than they did in prior years: just 0.9% on average, down from 8.8% a year earlier. For large, mid-sized and regional banks unfortunately, it was a different story with attrition rates at 10 to 11.3%. It gets even more complex when you drill down to a specific type of financial product such as a credit card. Experian’s own analysis of credit card customer retention shows that while the majority of customers are loyal, a good percentage attrite actively—that is, close their accounts and open new ones—while a bigger percent are silent attriters, those that do not close accounts but pay down balances and move their spend to others. Obviously, attrition is a continual topic that needs to be addressed, but to minimize it you first need to understand the root cause. Poor service seems to be the leading factor and one study* showed that 31% of consumers who switched banks did so because of poor service, followed by product features and finding a better offer elsewhere. So what are financial institutions doing to retain their profitable customers? There are lots of tools ranging from easy to more complex e.g., fee and interest waiver, line increases, rewards, and call center priority to name a few. But the key to successful customer retention is to look within the portfolio combining both internal and external information. This encompasses both proactive and reactive strategies. Proactive strategies include identifying customer behaviors which lead to balance or account attrition and taking action before a customer does. This includes monitoring changes over time and identifying thresholds for action as well as segmentation and modeling to identify problem. Reactive strategies, as the name suggests, is reacting to when a customer has already taken action which will lead to attrition; these include monitoring portfolios for new inquiries and account openings or response to customer complaints. In some cases, this maybe too little too late, but in others reactive response may be what saves a customer relationship. Whichever strategy or combination of these you choose, the key points to remember to retain customers and keep them happy are: Understand your current customers’ perceptions about credit, as they many have changed—customers are likely to be more educated, and the most profitable ones expect only the best customer service experience Be approachable and personal – meet customer needs—or better yet, anticipate those needs, focusing on loyalty and customer experience You don’t need to “give away the farm” – sometimes a partial fee waiver works * Global Consumer Banking Survey 2011, by Ernst & Young  

By: Ken Pruett The great thing about being in front of customers is that you learn something from every meeting.  Over the years I have figured out that there is typically no “right” or “wrong” way to do something.  Even in the world of fraud and compliance I find that each client's approach varies greatly.  It typically comes down to what the business need is in combination with meeting some sort of compliance obligation like the Red Flag Rules or the Patriot Act.  For example, the trend we see in the prepaid space is that basic verification of common identity elements is really the only need.   The one exception might be the use of a few key fraud indicators like a deceased SSN.  The thought process here is that the fraud risk is relatively low vs. someone opening up a credit card account.  So in this space, pass rates drive the business objective of getting customers through the application process as quickly and easily as possible….while meeting basic compliance obligations. In the world of credit, fraud prevention is front and center and plays a key role in the application process.  Our most conservative customers often use the traditional bureau alerts to drive fraud prevention.  This typically creates high manual review rates but they feel that they want to be very customer focused. Therefore, they are willing to take on the costs of these reviews to maintain that focus.  The feedback we often get is that these alerts often lead to a high number of false positives. Examples of messages they may key off of are things like the SSN not being issued or the On-File Inquiry address not matching.  The trend is this space is typically focused on fraud scoring. Review rates are what drive score cut-offs leading to review rates that are typically 5% or less.  Compliance issues are often resolved by using some combination of the score and data matching. For example, if there is a name and address mismatch that does not necessarily mean the application will kick out for review.  If the Name, SSN, and DOB match…and the score shows very little chance of fraud, the application can be passed through in an automated fashion.  This risk based approach is typically what we feel is a best practice.  This moves them away from looking at the binary results from individual messages like the SSN alerts mentioned above. The bottom line is that everyone seems to do things differently, but the key is that each company takes compliance and fraud prevention seriously.  That is why meeting with our customers is such an enjoyable part of my job.

Join us Sept 12-13 in New York City for the Finovate conference to check out the best new innovations in financial and banking technology from a mixture of leading established companies and startups. As part of Finovate's signature demo-only format for this event, Steve Wagner, President, Consumer Information Services and Michele Pearson, Vice President of Marketing, Consumer Information Services, from Experian will demonstrate how providers and lead generators can access a powerful new marketing tool to: Drive new traffic Lower online customer acquisition costs Generate high-quality, credit-qualified leads Proactively utilize individual consumer credit data online in real time Networking sessions will follow company demos each day, giving attendees the chance to speak directly with the Experian innovators they saw on stage. Finovate 2011 had more than 1,000 financial institution executives, venture capitalists, members of the press and entrepreneurs in attendance, and they expecting an even larger audience at the 2012 event. We look forward to seeing you at Finovate! 

  In this three-part series, Everything you wanted to know about credit risk scores, but were afraid to ask, I will provide a high level overview of: What a credit risk score predicts; Common myths about credit risk scores and how to educate consumers; and finally, Scoring traditionally unscoreable consumers Part I: So what exactly does a credit risk score predict? A credit risk score predicts the probability that a consumer will become 90 days past due or greater on any given account over the next 24 months. A three digit risk score relates to probability; or in some circles, probability of default. An example of the probability of default: For a consumer who has a VantageScore® credit score of 900, there is a 0.21% chance they will have a 90 day or greater past due occurrence in the next 24 months or odds of 2 out of 1,000 consumers A consumer with a VantageScore® credit score of 560 will have a 35% chance they will have a 90 day or greater past due occurrence in the next 24 months or odds of 350 out of 1,000 consumers This concept comes to life in light of changes being made on the regulatory front from the FDIC in the new proposed large bank pricing rule, which will change the way large lenders define and calculate risk for their FDIC Deposit Insurance Assessment. One of the key changes is that the traditional three-digit credit score used to set its risk threshold will be replaced with “probability of default” (PD) metric.  Based on the proposed rule, the new definition for a higher risk loan is one that has a 20% or higher probability of defaulting in two years. The new rule has a number of wide-ranging implications. It will impact a lender’s FDIC assessment and will allow them to uniformly and easily assess risk regardless of their use of proprietary or generic credit risk scoring modes. In part 2, I will dispel some common consumer myths about credit scores and how lenders can provide credit education to their customers.