Tag: credit risk
This is the introduction to a series of blog posts highlighting key focus areas for your response to the COVID-19 health crisis: Risk, Operations, Consumer Behavior, and Reporting and Compliance. For more information and the latest resources, please visit Look Ahead 2020, Experian\'s COVID-19 resource center with the latest news and tools for our business partners as well as links to consumer resources and a risk simulator. Responding to COVID-19 The response to COVID-19 is rolling out across the global financial system and here in North America. Together, we’re adapting to working remotely and adjusting to our “new normal.” It seems the long forecasted economic recession is finally and abruptly on our doorstep. Recession planning has been a focus for many organizations, and it’s now time to act on these contingency plans and respond to the downturn. The immediate effects and those that quickly follow the pandemic will widely impact the economy, affecting businesses of all sizes, employment and consumer confidence. We learned from the housing crisis and Great Recession how to identify and adapt to emerging risks. We can apply those skills while rebuilding the economy and focusing on the consumer. How should you respond? What strategies should you deploy? How can you balance emerging risks, changing consumer expectations and regulatory impacts? First, let\'s draw upon the best knowledge we gained from the last recession and apply those learnings. Second, we need to understand the current environment including the impact of major changes in technology and consumer behavior over the last few years. This approach will allow us to identify key themes to help build-out strategies to focus resources, respond successfully and deliver for stakeholders. Anticipate the pervasive and highly impactful market dynamics and trends The impact of this downturn on the consumer, on businesses and on financial institutions will be very different to that of the Great Recession. There will be a complete loss of income for many workers and small businesses. In a survey conducted by the Center for Financial Services Innovation (CFSI), more than 112 million Americans said that they don’t have enough savings to cover three months of living expenses*. These volatile market conditions and consumer insecurity will cause changes to your business models. You must prepare to manage increased fraud attacks, continue to push toward digital banking and understand regulatory changes. Learn More *U.S. Financial Health Pulse, 2018 Baseline Survey Results. https://s3.amazonaws.com/cfsi-innovation-files-2018/ wp-content/uploads/2018/11/20213012/Pulse-2018- Baseline-Survey-Results-11-16.18.pdf
A few months ago, I got a letter from the DMV reminding me that it was finally time to replace my driver’s license. I’ve had it since I was 21 and I’ve been dreading having to get a new one. I was especially apprehensive because this time around I’m not just getting a regular old driver’s license, I’m getting a REAL ID. For those of you who haven’t had this wonderful experience yet, a REAL ID is the new form of driver’s license (or state ID) that you’ll need to board a domestic flight starting October 1, 2020. Some states already offered compliant IDs, but others—like California, where I’m from—didn’t. This means that if I want to fly within the U.S. using my driver’s license next year, I can’t renew by mail. It’s Easier Than It Looks Imagine my surprise when I started the process to schedule my appointment, and the California DMV website made things really easy! There’s an online application you can fill out before you get to the DMV and they walk you through the documents to bring to the appointment (which I was able to schedule online). Despite common thought that the DMV and agencies like it are slow to adopt technology, the ease of this process may indicate a shift toward a digital-first mindset. As financial institutions embrace a similar shift, they’ll be better positioned to meet the needs of customers. Case in point, the electronic checklist the DMV provided to prepare me for my appointment. I sailed through the first two parts of the checklist, confirming that I’ll bring my proof of identity and social security number, but I paused when I got to the “Two Proofs of Residency” screen. Like many people my age—read: 85% of the millennial population, according to a recent Experian study—I don’t have a mortgage or any other documents relating to property ownership. I also don’t have my name on my utilities (thanks, roomie) or my cell phone bill (thanks Mom). I do however have a signed lease with my name on it, plus my renter’s insurance, both of which are acceptable as proof of residency. And just like that, I’m all set to get my REAL ID, even though I don’t have some of the basic adulting documents you might expect, because the DMV took into account the fact that not all REAL ID applicants are alike. Imagine if lenders could adopt that same flexibility and create opportunities for the more than 45 million U.S. consumers1 who lack a credit report or have too little information to generate a credit score. The Bigger Picture By removing some of the usual barriers to entry, the DMV made the process of getting my REAL ID much easier than it might have been and corrected my assumptions about how difficult the process would be. Experian has the same line of thought when it comes to helping you determine whether a borrower is credit-worthy. Just because someone doesn’t have a credit card, auto loan or other traditional credit score contributor doesn’t mean they should be written off. That’s why we created Experian BoostTM, a product that lets consumers give read-only access to their bank accounts and add in positive utility and telecommunications bill payments to their credit file to change their scores in real time and demonstrate their stability, ability and willingness to repay. It’s a win-win for lenders and consumers. 2 out of 3 users of Experian Boost see an increase in their FICO Score and of those who saw an increase, 13% moved up a credit tier. This gives lenders a wider pool to market to, and thanks to their improved credit scores, those borrowers are eligible for more attractive rates. Increasing your flexibility and removing barriers to entry can greatly expand your potential pool of borrowers without increasing your exposure to risk. Learn more about how Experian can help you leverage alternative credit data and expand your customer base in our 2019 State of Alternative Data Whitepaper. Read Full Report 1Kenneth P. Brevoort, Philipp Grimm, Michelle Kambara. “Data Point: Credit Invisibles.” The Consumer Financial Protection Bureau Office of Research. May 2015.
Alex Lintner, Group President at Experian, recently had the chance to sit down with Peter Renton, creator of the Lend Academy Podcast, to discuss alternative credit data,1 UltraFICO, Experian Boost and expanding the credit universe. Lintner spoke about why Experian is determined to be the leader in bringing alternative credit data to the forefront of the lending marketplace to drive greater access to credit for consumers. “To move the tens of millions of “invisible” or “thin file” consumers into the financial mainstream will take innovation, and alternative data is one of the ways which we can do that,” said Lintner. Many U.S. consumers do not have a credit history or enough record of borrowing to establish a credit score, making it difficult for them to obtain credit from mainstream financial institutions. To ease access to credit for these consumers, financial institutions have sought ways to both extend and improve the methods by which they evaluate borrowers’ risk. By leveraging machine learning and alternative data products, like Experian BoostTM, lenders can get a more complete view into a consumer’s creditworthiness, allowing them to make better decisions and consumers to more easily access financial opportunities. Highlights include: The impact of Experian Boost on consumers’ credit scores Experian’s take on the state of the American consumer today Leveraging machine learning in the development of credit scores Expanding the marketable universe Listen now Learn more about alternative credit data 1When we refer to \"Alternative Credit Data,\" this refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term \"Expanded FCRA Data\" may also apply in this instance and both can be used interchangeably.
What if you had an opportunity to boost your credit score with a snap of your fingers? With the announcement of Experian BoostTM, this will soon be the new reality. As part of an increasingly customizable and instant consumer reality in the marketplace, Experian is innovating in the space of credit to allow consumers to contribute information to their credit profiles via access to their online bank accounts. For decades, Experian has been a leader in educating consumers on credit: what goes into a credit score, how to raise it and how to maintain it. Now, as part of our mission to be the consumer’s bureau, Experian is ushering in a new age of consumer empowerment with Boost. Through an already established and full-fledged suite of consumer products, Experian Boost is the next generation offering a free online platform that places the control in the consumers’ hands to influence their credit scores. The platform will feature a sign-in verification, during which consumers grant read-only permission for Experian Boost to connect to their online bank accounts to identify utility and telecommunications payments. After they verify their data and confirm that they want the account information added to their credit file, consumers will receive an instant updated FICO® Score. The history behind credit information spans several centuries from a group of London tailors swapping information on customers to keeping credit files on index cards being read out to subscribers over the telephone. Even with the evolution of the credit industry being very much in the digital age today, Experian Boost is a significant step forward for a credit bureau. This new capability educates the consumer on what types of payment behavior impacts their credit score while also empowering them to add information to change it. This is a big win-win for consumers and lenders alike. As Experian is taking the next big step as a traditional credit bureau, adding these data sources is a new and innovative way to help consumers gain access to the quality credit they deserve as well as promoting fair and responsible lending to the industry. Early analysis of Experian’s Boost impact on the U.S. consumer credit scores showed promising results. Here’s a snapshot of some of those findings: These statistics provide an encouraging vision into the future for all consumers, especially for those who have a limited credit history. The benefit to lenders in adding these new data points will be a more complete view on the consumer to make more informed lending decisions. Only positive payment histories will be collected through the platform and consumers can elect to remove the new data at any time. Experian Boost will be available to all credit active adults in early 2019, but consumers can visit www.experian.com/boost now to register for early access. By signing up for a free Experian membership, consumers will receive a free credit report immediately, and will be one of the first to experience the new platform. Experian Boost will apply to most leading consumer credit scores used by lenders. To learn more about the platform visit www.experian.com/boost.
Every morning, I wake up and walk bleary eyed to the bathroom, pop in my contacts and start my usual routine. Did I always have contacts? No. But putting on my contacts and seeing clearly has become part of my routine. After getting used to contacts, wearing glasses pales in comparison. This is how I view alternative credit data in lending. Are you having qualms about using this new data set? I get it, it’s like sticking a contact into your eye for the first time: painful and frustrating because you’re not sure what to do. To relieve you of the guesswork, we’ve compiled the top four myths related to this new data set to provide an in-depth view as to why this data is an essential supplement to your traditional credit file. Myth 1: Alternative credit data is not relevant. As consumers are shifting to new ways of gaining credit, it’s important for the industry to keep up. These data types are being captured by specialty credit bureaus. Gone are the days when alternative financing only included the payday store on the street corner. Alternative financing now expands to loans such as online installment, rent-to-own, point-of-sale financing, and auto-title loans. Consumers automatically default to the financing source familiar to them – which doesn’t necessarily mean traditional financial institutions. For example, some consumers may not walk into a bank branch anymore to get a loan, instead they may search online for the best rates, find a completely digital experience and get approved without ever leaving their couches. Alternative credit data gives you a lens into this activity. Myth 2: Borrowers with little to no traditional credit history are high risk. A common misconception of a thin-file borrower is that they may be high risk. According to the CFPB, roughly 45 million Americans have little to no credit history and this group may contain minority consumers or those from low income neighborhoods. However, they also may contain recent immigrants or young consumers who haven’t had exposure to traditional credit products. According to recent findings, one in five U.S. consumers has an alternative financial services data hit– some of these are even in the exceptional or very good credit segments. Myth 3: Alternative credit data is inaccurate and has poor data quality. On the contrary, this data set is collected, aggregated and verified in the same way as traditional credit data. Some sources of data, such as rental payments, are monthly and create a consistent look at a consumer’s financial behaviors. Experian’s Clarity Services, the leading source of alternative finance data, reports their consumer information, which includes application information and bank account data, as 99.9% accurate. Myth 4: Using alternative credit data might be harmful to the consumer. This data enables a more complete view of a consumer’s credit behavior for lenders, and provides consumers the opportunity to establish and maintain a credit profile. As with all information, consumers will be assessed appropriately based on what the data shows about their credit worthiness. Alternative credit data provides a better risk lens to the lender and consumers may get more access and approval for products that they want and deserve. In fact, a recent Experian survey found 71% of lenders believe alternative credit data will help consumers who would have previously been declined. Like putting in a new pair of contact lenses the first time, it may be uncomfortable to figure out the best use for alternative credit data in your daily rhythm. But once it’s added, it’s undeniable the difference it makes in your day-to-day decisions and suddenly you wonder how you’ve survived without it so long. See your consumers clearly today with alternative credit data. Learn More About Alternative Credit Data
Understanding and managing first party fraud Background/Definitions Wherever merchants, lenders, service providers, government agencies or other organizations offer goods, services or anything of value to the public, they incur risk. These risks include: Credit risk — Loosely defined, credit risk arises when an individual receives goods/services in exchange for a promise of future repayment. If the individual’s circumstances change in a way that prevents him or her from paying as agreed, the provider may not receive full payment and will incur a loss. Fraud risk — Fraud risk arises when the recipient uses deception to obtain goods/services. The type of deception can involve a wide range of tactics. Many involve receiving the goods/services while attributing the responsibility for repayment to someone else. The biggest difference between credit risk and fraud risk is intent. Credit risk usually involves customers who received the goods/services with intent to repay but simply lack the resources to meet their obligation. Fraud risk starts with the intent to receive the goods/services without the intent to repay. Between credit risk and fraud risk lies a hybrid type of risk we refer to as first-party fraud risk. We call this a hybrid form of risk because it includes elements of both credit and fraud risk. Specifically, first party fraud involves an individual who makes a promise of future repayment in exchange for goods/services without the intent to repay. Challenges of first party fraud First party fraud is particularly troublesome for both administrative and operational reasons. It is important for organizations to separate these two sets of challenges and address them independently. The most common administrative challenge is to align first-party fraud within the organization. This can be harder than it sounds. Depending on the type of organization, fraud and credit risk may be subject to different accounting rules, limitations that govern the data used to address risk, different rules for rejecting a customer or a transaction, and a host of other differences. A critical first step for any organization confronting first-party fraud is to understand the options that govern fraud management versus credit risk management within the business. Once the administrative options are understood, an organization can turn its attention to the operational challenges of first-party fraud. There are two common choices for the operational handling of first-party fraud, and both can be problematic. First party fraud is included with credit risk. Credit risk management tends to emphasize a binary decision where a recipient is either qualified or not qualified to receive the goods/services. This type of decision overlooks the recipient’s intent. Some recipients of goods/services will be qualified with the intent to pay. Qualified individuals with bad intentions will be attracted to the offers extended by these providers. Losses will accelerate, and to make matters worse it will be difficult to later isolate, analyze and manage the first party fraud cases if the only decision criteria captured pertained to credit risk decisions. The end result is high credit losses compounded by the additional first party fraud that is indistinguishable from credit risk. First party fraud is included with other fraud types. Just as it’s not advisable to include first party fraud with credit risk, it’s also not a good idea to include it with other types of fraud. Other types of fraud typically are analyzed, detected and investigated based on the identification of a fraud victim. Finding a person whose identity or credentials were misused is central to managing these other types of fraud. The types of investigation used to detect other fraud types simply don’t work for first-party fraud. First party fraudsters always will provide complete and accurate information, and, upon contact, they’ll confirm that the transaction/purchase is legitimate. The result for the organization will be a distorted view of their fraud losses and misconceptions about the effectiveness of their investigative process. Evaluating the operational challenges within the context of the administrative challenges will help organizations better plan to handle first party fraud. Recommendations Best practices for data and analytics suggest that more granular data and details are better. The same holds true with respect to managing first party fraud. First party fraud is best handled (operationally) by a dedicated team that can be laser-focused on this particular issue and the development of best practices to address it. This approach allows organizations to develop their own (administrative) framework with clear rules to govern the management of the risk and its prevention. This approach also brings more transparency to reporting and management functions. Most important, it helps insulate good customers from the impact of the fraud review process. First-party fraudsters are most successful when they are able to blend in with good customers and perpetrate long-running scams undetected. Separating this risk from existing credit risk and fraud processes is critical. Organizations have to understand that even when credit risk is low, there’s an element of intent that can mean the difference between good customers and severe losses. Read here for more around managing first party fraud risk.
Customer experience strategies for success Sometimes it’s easier to describe something as the opposite of something else. Being “anti-” something can communicate something meaningful. Cultural movements in the past have taken on these monikers: consider the “anti-establishment” or “anti-war” movements. We all need effective anti-virus protection. And there are loads of skin products marketed as “anti-aging”, “anti-wrinkle”, or “anti-blemish.” But when you think about a vision for the customer experience that your company aspires to deliver, this approach of the “anti-X” falls flat. Would you want to aspire to basically “not stink?” Would that inspire you and your team to run through walls to deliver on that grand aspiration? Would it motivate customers to stick with you, buy more of what you sell, and tell others about you? I think not…But it sure seems like many out there indeed do aspire to “not stink.” Sure, there are great companies out there who have a set a high standard for customer experience, placing it at the center of their strategies and their success. Some, like Zappos, started that way from the beginning. Others, like The Ritz-Carlton, realized that they had lost their way and made the commitment to do the hard work of reaching and sustaining excellence. On the other hand, there are hundreds of firms who have a weak commitment to or even understanding of the importance of customer experience to their strategy and performance. Their leaders may give lip service or just pay attention for a few days or hours following the release of reports from leading analysts and firms. They may have posters and slogans that talk about putting the customer first or similar platitudes. These companies probably even have talented and passionate professionals working tirelessly to improve the customer experience in spite of the fact that nobody seems to care much. What these firms lack is a clear customer experience strategy. As nature abhors a vacuum, customers and employees are free to infer or just guess at it. Focusing on customer experience only when a report comes out – and paying special attention only when weak results put the firm near the bottom of the ranking leads people to conclude that all that really matters is to “not stink.” In other words, don’t stand out for being bad…but don’t worry much about being good as it is not important to the company’s strategy or results. I think that this “don’t stink” implicit strategy helps explain a fascinating insight from a Forrester survey in 2013: “80% of executives believe their company is delivering a superior customer experience, yet in 2013 only 8% of companies surveyed received a top grade from their customers.” Many leaders simply have not invested the energy and commitment necessary to define a real customer experience vision that reflects a deep understanding of the role that it plays in the company’s strategy. Beyond setting that vision, there is a big and sustained commitment required to deliver on the vision, measure results, and continuously adjust as customer needs evolve. Like all journeys, a great customer experience starts with one step. Establishing a customer experience strategy is the first one – and “don’t stink” simply stinks as a strategy. Download our recent perspective paper to learn how exceptional customer experience can give companies the competitive edge they need in a market where price, products and services can no longer be a differentiator.
Using a risk model based on older data can result in reduced predictive power.
By: Staci Baker It seems like every time I turn on the TV there is another natural disaster. Tsunami in Japan, tornadoes and flooding in the Mid-West United States, earthquakes and forest fires – everywhere; and these disasters are happening worldwide. They are not confined to one location. If a disaster were to happen near any of your offices, would you be prepared? Living in Southern California, this is something I think of often. Especially, since we are supposed to have had “the big one” for the past several years now. When developing a preparedness plan for a company, there are several things to take into consideration. Some are obvious, such as how to keep employees safe, developing steps for IT to take to ensure data is protected , including an identity theft prevention program, and establishing contingency business plans in case a disaster directly hits your business and doors need to remain closed for several days, weeks, or …. But, what about the non-obvious items that should be included in a disaster preparedness plan? When a natural disaster hits, there is an increase in fraud. So much so, that after Hurricane Katrina battered the Gulf, the Hurricane Katrina Fraud Task Force, now known as the National Center for Disaster Fraud, was created. In addition to the items listed above, I recommend including the following. Create a plan that will put fraud alerts in place to minimize fraud. Fraud alerts are not just to notify your clients when there is fraudulent activity on their accounts. Alerts should also be put in place to let you know when there is fraudulent activity within your own business as well. Depending on the type of disaster, delinquency rates may increase, since borrower funds may be diverted to other needs. Implement a disaster collections strategy, which may include modifying credit terms, managing credit risk, and loan loss provisioning. Although these are only a few things to be considered when developing a disaster preparedness plan, I hope it gets you thinking about what your company needs to do to be prepared. What are some things you have already done, or that are on your to do list to prepare your company for the next big event that may affect you?
I love a good analogy, and living in Southern California, lately I’ve been thinking a lot about earthquakes, and how lenders might want to start thinking like seismologists when considering the risk levels in their portfolios. Currently, scientists that study earthquakes review mountains of data around fault movement, tidal forces, even animal behavior, all in an attempt to find a concrete predictor of ‘the big one’. Small tremors are inputs, but the focus is on predicting and preparing for the large shock and impact of large earthquakes. Credit risk modeling, conversely, seems to focus on predicting the tremors, (risk scores that predict the risk of individual default) and less so the large-shock risk to the portfolio. So what are lenders doing to forecast ‘the big one’? Lenders are building sophisticated models that contemplate the likelihood of the big event – developing risk models and econometric models that look at loan repayment, house prices, unemployment rates – all in an attempt to be ahead of the credit version of ‘the big one’. This type of model and perspective is at a nascent stage for many lenders, but like the issues facing the people of Southern California, preparing for the big-one is an essential part of every lender’s planning in today’s economy.
By: Staci Baker On September 12, 2010, the new Basel III rules were passed in Basel, Switzerland. These new rules aim to increase the liquidity of banks over the next decade, thereby mitigating the risk of bank failures and mergers that transpired during the recent financial crisis. Currently, banks must maintain capital reserves of 4% on their balance sheet to account for enterprise risk. Starting January 1, 2013, banks will be required to progressively increase their capital reserves, known as tier 1 capital, to 4.5%. By the end of 2019, this reserve will need to be 6%. Banks will also be required to keep an emergency reserve, or “conservation buffer,” of 2.5%. What does this mean for banks? And, what are some tools that banks can use in assessing credit risk? By increasing capital reserves, banks will be more stable in times of economic hardship. The conservation buffer is meant to help absorb losses during times of economic stress, which means banks will be in a better position to maintain economic progress in the most challenging economic circumstances. The capital reserve designated by the Group of Governors and Heads of Supervision is the minimum requirement each bank will be held to. Each bank will need to assess their current risk levels, and run stress tests to ensure they are in a good financial position, and are able to sustain strong financial health during a failing economy. Stress tests should be run for different time intervals, which will allow lenders to assess future losses and to plan capital satisfactoriness accordingly. This type of credit risk analysis is possible through applications such as Moody’s CreditCycle Plus, powered by Experian, that allow for stress testing, and profit and loss forecasting. These applications will measure future performance of consumer credit portfolios under various economic scenarios, measured against industry benchmarks. ______________ Bank for International Settlements, 9/12/10, http://bis.org/press/p100912.htm
With the news from the Federal Reserve that joblessness is not declining, and in fact is growing, a number of consumers are going to face newly difficult times and be further challenged to meet their credit obligations. Thinking about how this might impact the already struggling mortgage market, I’ve been considering what the impact of joblessness is on the incidence of strategic default and the resulting risk management issues for lenders. Using the definitions from our previous studies on strategic default, I think it’s quite clear that increased joblessness will definitely increase the number of ‘cash-flow managers’ and ‘distressed borrowers’, as newly jobless consumers face reduced income and struggle to pay their bills. But, will a loss of income also mean that people become more likely to strategically default? By definition, the answer is no – a strategic defaulter has the capacity to pay, but chooses not to, mostly due to their equity position in the home. But, I can’t help but consider a consumer who is 20% underwater, but making payments when employed, deciding that the same 20% that used to be acceptable to bear, is now illogical and will simply choose to stop payment? Although only a short-term fix, since they can use far less of their savings by simply ceasing to pay their mortgage, this would free up significant cash (or savings) for paying car loans, credit cards, college loans, etc; and yet, this practice would maintain the profile of a strategic defaulter. While it’s impossible to predict the true impact of joblessness, I would submit that beyond assessing credit risk, lenders need to consider that the definition of strategic default may contain a number of unique, and certainly evolving consumer risk segments. __________________________ http://money.cnn.com/2010/08/19/news/economy/initial_claims/index.htm
Recently, a number of media articles have discussed the task facing financial institutions today – find opportunities growth in a challenging and flat economy. The majority of perspectives discuss the fact that lenders will soon have no choice but to look to the ‘fringe’, by lowering score cut-offs, adjusting acquisition strategies and introducing greater risk into their portfolios in order to grow. Risk and marketing departments are sure to be creating and analyzing credit risk models and assessing credit risk in new, untapped markets in order to achieve these objectives. While it may appear to be oversimplifying the task, many lenders have the opportunity to grow simply by understanding more about two groups of consumers that are already sitting in their offices (or application queues) today: applicants who are approved, but book elsewhere, and applicants that are declined. There are a number of analytic techniques that can be utilized to understand these populations further. Lenders can study the characteristics of other loans originated by these lost consumers, and can also perform analyses of how these consumers performed after booking competitive offers. By understanding the credit characteristics and account delinquency trends of its current applicants, lenders can uncover a wealth of information and insight about the growth opportunities sitting right before them.
By: Kari Michel Credit risk models are used by almost every lender, and there are many choices to choose from including custom or generic models. With so many choices how do you know what is best for your portfolio? Custom models provide the strongest risk prediction and are developed using an organization’s own data. For many organizations, custom models may not be an option due to the size of the portfolio (may be too small), lack of data including not enough bads, time constraints, and/or lack of resources. If a custom model is not an option for your organization, generic bureau scoring models are a very powerful alternative for predicting risk. But how can you understand if your current scoring model is the best option for you? You may be using a generic model today and you hear about a new generic model, for example VantageScore. How do you determine if the new model is more predictive than your current model for your portfolio? The best way to understand if the new model is more predictive is to do a head-to-head comparison – a validation. A validation requires a sample of accounts from your portfolio including performance flags. An archive is pulled from the credit reporting agency and both scores are calculated from the same time period and a performance chart is created to show the comparison. There are two key performance metrics that are used to determine the strength of the model. The KS (Komogorov-Smirnov) is a statistical term that measures the maximum difference between the bad and good cumulative score distribution. The KS range is from 0% to 100%, with the higher the KS the stronger the model. The second measurement uses the bad capture rate in the bottom 5%, 10% or 15% of the score range. A stronger model will provide better risk prediction and allow an organization to make better risk decisions. Overall, when stronger scoring models are used, organizations will be best prepared to decrease their bad rates and have a more profitable portfolio.
A recent January 29, 2010 article in the Wall Street Journal * discussing the repurchasing of loans by banks from Freddie Mae and Fannie Mac included a simple, yet compelling statement that I feel is worth further analysis. The article stated that \"while growth in subprime defaults is slowing, defaults on prime loans are accelerating.\" I think this statement might come as a surprise to some who feel that there is some amount of credit risk and economic immunity for prime and super-prime consumers – many of whom are highly sought-after in today’s credit market. To support this statement, I reference a few statistics from the Experian-Oliver Wyman Market Intelligence Reports: • From Q1 2007 to Q1 2008, 30+ DPD mortgage delinquency rates for VantageScore A and B consumers remained flat (actually down 2%); while near-prime, subprime, and deep-subprime consumers experienced an increase of over 36% in 30+ rates. • From Q4 2008 to Q4 2009, 30+ DPD mortgage delinquency rates for VantageScore A and B consumers increased by 42%; whereas consumers in the lower VantageScore tiers saw their 30+ DPD rate increase by only 23% in the same period Clearly, whether through economic or some other form of impact, repayment practices of prime and super-prime, consumers have been changing as of late, and this is translating to higher delinquency rates. The call-to-action for lenders, in their financial risk management and credit risk modeling efforts, is increased attentiveness in assessing credit risk beyond just a credit score...whether this be using a combination of scores, or adding Premier Attributes into lending models – in order to fully assess each consumer’s risk profile. * http://online.wsj.com/article/SB10001424052748704343104575033543886200942.html
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