Decision Analytics | Collections

Mike Sutton – Director of Collections Solutions, Experian Decision Analytics

Hello and welcome to our blog! My name is Mike Sutton and I am the Director of Collections Solutions for Experian's Decision Analytics business. I am primarily responsible for packaging and promoting collections products and services based on market trends and client needs. Additionally, I serve as the North American product manager for Tallyman TM, Experian's next-generation collections management system.


Since joining Experian in 1997, I have held many roles supporting and delivering scoring, risk, customer management and consulting products and services. Before I joined Experian, my management experience included roles at several large credit issuers managing credit extension, authorization, fraud and collections operations. I have spent a considerable portion of my career developing and implementing strategies and systems to mitigate risk, create operational efficiencies, increase cash flow and deliver better bottom-line financial results.

I am a graduate of the University of Tennessee and hold a bachelor’s degree in business psychology.


Jeff Bernstein – Executive Strategic Consultant, Experian Decision Analytics

Hello and thanks for visiting our blog! My name is Jeff Bernstein and I am an Executive Strategic Consultant with Experian’s Decision Analytics business. I am primarily responsible for providing strategic insights of clients’ needs for collections products and services to Experian, and ensuring that we are providing best of class solutions and consulting expertise into the market. In that role, I consult with many clients throughout North America and other parts of the globe across the collections lifecycle.  I also have responsibility for supporting Tallyman TM, Experian’s next-generation collections management system, in the North American market.

I’ve only been working for Experian since early 2009, but have been spent the past 29 years involved in all aspects of collections and credit risk management. I’ve spent the past 13 years consulting on a global basis with banking and financial services clients, debt purchasers and collections services providers, and working for technology and analytics solutions providers that serve those markets.

Prior to consulting, I was a senior executive in top tier banking and financial services organizations in the U.S. market, responsible for lending, credit risk management, and collections operations spanning consumer and small business lending, auto finance, sub-prime mortgage, dealer finance, and credit cards.

Throughout my career, I’ve been focused on integrating portfolio risk strategy with collections, optimizing collections treatment strategies, and improving operational performance, all in the quest to mitigate risk, create operational efficiencies, and deliver better overall profitability.

I am a graduate of Utica College of Syracuse University and hold a bachelor’s degree in Business Administration – Management.


Dan Buell -- Vice President of Marketing, Experian Consumer Information Solutions Marketing

Hi and thanks for visiting our blog !  I’m the Vice President of Marketing for Experian’s Consumer Information Solutions Marketing group where I am responsible for the development, management and marketing for Experian’s Collections Products and Solutions.

I began my career in the credit and collections industry with software developer Ontario Systems. I have also served as the Director of Information Services for OSI, Chief Operating Officer for Machol & Johannes, P.C. and President of Americall Group, Inc.

An active speaker, I present at numerous collections industry events. My most recent appearances include the 2008 Akcelerant Credit Union Conference, 2008 Platts Utility Collection Conference, 2007 Debt Buyers Association Conference, 2005 and 2006 Collection Technology Summit, the 2006 Telecommunication Risk Management Association Interactive Learning Lab, the National Association of Retail Collection Attorneys Fall 2006 Conference and the 2007 Collection and Recovery Solutions conference.

I graduated from Ball State University and hold a Masters in Business Administration with honors.



Paul J. Konkel -- Senior Director of Collections Strategy

With eighteen years of startup experience and ten years of account receivables management experience, Paul joined Experian in July 2009 to focus on early stage collections programs.  Prior to joining Experian Paul served as the President for TrueLogic Corporation, a leading account receivables management organization that Paul founded in 2002.  Paul was also a leader at analytics and modeling organization NAREX (now a part of FICO) where he led information technology and operations.  He also has served as President of AUB, Inc. and the IVY Group.  Paul holds a B.A. in Economics and International Relations from the University of Pennsylvania and is Six Sigma Certified. 






 

--by Jeff Bernstein

In my last blog, I discussed the basic concept of a maturation curve, as illustrated below:

Exhibit 1

In Exhibit 1, we examine different vintages beginning with those loans originated by year during Q2 2002 through Q2 2008. The purpose of the vintage analysis is to identify those vintages that have a steeper slope towards delinquency, which is also known as delinquency maturation curve.

The X-axis represents a timeline in months, from month of origination.  Furthermore, the Y-axis represents the 90+ delinquency rate expressed as a percentage of balances in the portfolio.  Those vintage analyses that have a steeper slope have reached a normalized level of delinquency sooner, and could in fact, have a trend line suggesting that they overshoot the expected delinquency rate for the portfolio based upon credit quality standards.

So how can you use a maturation curve as a useful portfolio management tool?

As a consultant, I spend a lot of time with clients trying to understand issues, such as why their charge-offs are higher than plan (budget).  I also investigate whether the reason for the excess credit costs are related to collections effectiveness, collections strategy, collections efficiency, credit quality or a poorly conceived budget.

I recall one such engagement, where different functional teams within the client’s organization were pointing fingers at each other because their budget evaporated. One look at their maturation curves and I had the answers I needed. I noticed that two vintages per year had maturation curves that were pointed due north, with a much steeper curve than all other months of the year. Why would only two months or vintages of originations each year be so different than all other vintage analyses in terms of performance?

I went back to my career experiences in banking, where I worked for a large regional bank that ran marketing solicitations several times yearly. Each of these programs was targeted to prospects that, in most instances, were out-of-market, or in other words, outside of the bank’s branch footprint.

Bingo! I got it! The client was soliciting new customers out of his
market, and was likely getting adverse selection. While he targeted the “right” customers – those with credit scores and credit attributes within an acceptable range, the best of that targeted group was not interested in accepting their offer, because they did not do business with my client, and would prefer to do business with an in-market player.

Meanwhile, the lower grade prospects were accepting the offers, because it was a better deal than they could get in-market. The result was adverse selection...and what I was staring at was the "smoking gun" I’d been looking for with these two-a-year vintages (vintage analysis) that reached the moon in terms of delinquency.

That’s the value of building a maturation curve analysis – to identify
specific vintages that have characteristics that are more adverse than others.  I also use the information to target those adverse populations and track the performance of specific treatment strategies aimed at containing losses on those segments. You might use this to identify which originations vintages of your home equity portfolio are most likely to migrate to higher levels of delinquency; then use credit bureau attributes to identify specific borrowers for an early lifecycle treatment strategy.

As that beer commercial says – “brilliant!”

 

--by Jeff Bernstein

In the current economic environment, many lenders and issuers across the globe are struggling to manage the volume of caseloads coming into collections. The challenge is that as these new collection cases come into collections in early phases of delinquency, the borrower is already in distress, and the opportunity to have a good outcome is diminished.

One of the real “hot” items on the list of emerging best practices and innovating changes in collections is the concept of early lifecycle treatment strategy. Essentially, what we are referring to is the treatment of current and non-delinquent borrowers who are exhibiting higher risk characteristics.  There are also those who are at-risk of future default at higher levels than average. The challenge is how to identify these customers for early intervention and triage in the collections strategy process.

One often-overlooked tool is the use of maturation curves to identify vintages within a portfolio that is performing worse than average. A maturation curve identifies how long from origination until a vintage or segment of the portfolio reaches a normalized rate of delinquency.

Let’s assume that you are launching a new credit product into the marketplace. You begin to book new loans under the program in the current month. Beyond that month, you monitor all new loans that were originated/booked during that initial time frame which we can identify as a “vintage” of the portfolio. Each month’s originations are a separate vintage or vintage analysis, and we can track the performance of each vintage over time.

How many months will it take before the “portfolio” of loans booked in that initial month reach a normal level of delinquency based on these criteria: the credit quality of the portfolio and its borrowers, typical collections servicing, delinquency reporting standards, and factor of time?  The answer would certainly depend upon the aforementioned factors, and could be graphed as follows:

Exhibit 1

 
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-- by Dan Buell

Towards the end of 2007, the management of Bay Area Credit Service embarked on an agressive strategy to dramatically enhance the company's market position and increase its collection revenues.  These goals could be achieved only through superior performance at competitive rates.  At the same time, though, the company needed to drastically reduce internal operating expenses while facing significant competition.  The company's major goals for 208 included:

*  Earn a much larger share of business from one of the nation's top five cellular phone service providers;

*  Become a major collections partner for one of the nation's largest banking institutions;

*  Earn more than 50 percent of the market in the pre-charge-off, early-out segment for the nation's largest landline communications provider;

*  Enhance the company's position in the secondary collections tier.

It's an interesting case study.  Navigate to the link to learn more: 

http://www.experian.com/whitepapers/index.html

--by Mike Sutton

In today’s collections environment, the challenges of meeting an organization’s financial objectives are more difficult than ever.  Case volumes are higher, accounts are more difficult to collect and changing customer behaviors are rendering existing business models less effective.

When responding to recent events, it is not uncommon for organizations to take what may seem to be the easiest path to success — simply hiring more staff. Perhaps in the short-term there may appear to be cash flow improvements, but in most cases, this is not the most effective way to cope with long-term business needs. As incremental staff is added to compensate for additional workloads, there is a point of diminishing return on investment and that can be difficult to define until after the expenditures have been made. Additionally, there are almost always significant operational improvements that can be realized by introducing new technology.  Furthermore, the relevant return on investment models often forecast very accurately.

So, where should a collections department consider investing to improve financial results? The best option may not be the obvious choice, and the mere thought can make the most seasoned collections professionals shutter at the thought of replacing the core collections system with modern technology. That said, let’s consider what has changed in recent years and explore why the replacement proposition is not nearly as difficult or costly as in the past.

Collection Management Software
The collections system software industry is on the brink of a technology evolution to modern and next-generation offerings. Legacy systems are typically inflexible and do not allow for an effective change management program. This handicap leaves collections departments unable to keep up with rapidly changing business objectives that are a critical requirement in surviving these tough economic times. Today’s collections managers need to reduce operational costs while improving these objectives: reducing losses, improving cash flow and promoting customer satisfaction (particularly with those who pose a greater lifetime profit opportunity).  The next generation collections software squarely addresses these business problems and provides significant improvement over legacy systems. Not only is this modern technology now available, but the return on investment models are extremely compelling and have been proven in markets where successful implementations have already occurred.

As an example of modern collections technologies that can help streamline operations, check out the overview and brief demonstration that is on this link:

www.experian.com/decision-analytics/tallyman-demo.html.
 

--by Mike Sutton

I recently interviewed a number of Experian clients to determine how they believe their organizations and industry peers will prioritize collections process improvement over the next 24 months. Additional contributions were collected by written surveys. Here are several interesting observations:

All of the categories mentioned above were considered important by every respondent, but the most urgent priorities were not consistent across industries.

Put yourself in the shoes of your collections team. The year ahead is challenging. Workloads are increasing as consumer debt escalates, and collectors are working tiring, stressful shifts talking to people who don't want to talk about their debts.

What kind of incentives can improve your collections performance and at the same time as create a well motivated and productive team?

Introduction

Financial incentives have long been a popular method to help boost staff performance. These rewards usually relate to the achievement of certain goals -- either personal, team, organizational or a combination of all three. A well-constructed incentive plan will increase staff morale and loyalty, as well as making a valuable difference to the bottom line. It can help ensure you are managing a team who are running at full speed and capability during these busy, turbulent times.

However, collections managers can also implement alternative non-monetary incentive programs that can boost staff commitment and effectiveness.

This series of postings identifies cash and non-cash alternatives that can help build and maintain a motivated team.

Getting Started

Before introducing a new incentive plan, clearly explain your objectives to the team. If your main goal is to maximize profitability, boost morale by letting your team know they are a major source of profit. Their understanding of how individual performance relates to the business will deepen their commitment to the program once it begins.

To help you decide what to include in the incentive plan, you must first understand what drives your team. This should be ascertained by conducting regular performance appraisals, call monitoring, attitude surveys and informal conversations. Your staff will likely tell you that increased status and recognition, higher pay, better working conditions and improved benefits would increase both morale and performance. We can look into incentives that address these requirements individually, but let's begin with the most obvious: money.

Money is a powerful motivator

The current economic climate guarantees that money is more important to your team members than ever; they want to be financially rewarded for their efforts. In this industry, collectors work individually so it is wise to target them in this way when using financial incentives.

Comparing individuals can also achieve higher performance levels because the cachet of being 'top dog' is a real motivator for some people.

Our advice is to begin by targeting staff in three familiar areas and ensure from the start that your collections system delivers the depth and granularity of management information to support your incentive program.

I would like to thank the Experian collections experts who contributed to this four-part series. The rest of the series will be posted soon!

-- by Jeff Bernstein

So, here I am with my first contribution to Experian Decision Analytics’ collections blog, and what I am discussing has practically nothing to do with analytics. But, it has everything to do with managing the opportunities to positively impact collections results and leveraging your investment in analytics and strategies, beginning with the most important weapon in your arsenal – collectors.

Yes, I know it’s a bit unconventional for a solutions and analytics company to talk about something other than models; but the difference between mediocre results and optimization rests with your collectors and your organization’s ability to manage customer interactions.

Let’s take a trip down memory lane and reminisce about one of the true landscape changing paradigm shifts in collections in recent memory – the use of skill models to become payment of choice.

AT&T Universal Card was one of the first early adopters of a radical new approach towards managing an emerging Gen X debtor population during the early 1990s. Armed with fresh research into what influenced delinquent debtors into paying certain collectors while dogging others, they adopted what we called a “management systems” approach towards collections.

They taught their entire collections team a new set of skills models that stressed bridging skills between the collector and the customer, thus allowing the collector to interact in a more collaborative, non-aggressive manner. The new approach enabled collectors to more favorably influence customer behavior, creating payment solutions collaboratively that allowed AT&T to become “payment of choice” when competing with other creditors competing for share of wallet.

A new of set of skill metrics, which we now affectionately call our “dashboard,” were created to measure the effective use of the newly taught skill models, and collectors were empowered to own their own performance – and to leverage their team leader for coaching and skills development. Team developers, the new name for front line collection managers, were tasked with spending 40-50% or more of their time on developmental activities, using leadership skills in their coaching and development activities.  

The game plan was simple.

• Engage collectors with customer focused skills that influenced behavior and get paid sooner.
• Empower collectors to take on the responsibility for their own development.
• Make performance results visible top-to-bottom in the organization to stimulate competitiveness, leveraging our innate desire for recognition.
• Make leaders accountable for continuous performance improvement of individuals and teams.

It worked. AT&T Universal won the Malcom Baldrige National Quality Award in 1992 for its efforts in “delighting the customer” while driving their delinquencies and charge-offs to superior levels. A new paradigm shift was unleashed and spread like wildfire across the industry, including many of the major credit card issuers and top tier U.S. banks, and large retailers.

Why do I bring this little slice of history up in my first blog?

I see many banking and financial services companies across the globe struggle with more complex customer situations and harder collections cases -- with their attention naturally focused on tools, models, and technologies. As an industry, we are focused on early lifecycle treatment strategy, identifying current, non-delinquent customers who may be at-risk for future default, and triaging them before they become delinquent. Risk-based collections and segmentation is now a hot topic. Outsourcing and leveraging multiple, non-agent based contact channels to reduce the pressures on collection resources is more important than ever. Optimization is getting top billing as the next “thing.”

What I don’t hear enough of is how organizations are engaged in improving the skills of collectors, and executing the right management systems approach to the process to extract the best performance possible from our existing resources. In some ways, this may be lost in the chaos of our current economic climate. With all the focus on analytics, segmentation, strategy and technology, the opportunity to improve operational performance through skill building and leadership may have taken a back seat.

I’ve seen plenty of examples of organizations who have spent millions on analytical tools and technologies, improving portfolio risk strategy and targeting of the right customers for treatment. I’ve seen the most advanced dialer, IVR, and other contact channel strategies used successfully to obtain the highest right party contact rates and the lowest possible cost. Yet, with all of that focus and investment, I’ve seen these right party contacts mismanaged by collectors who were not provided with the optimal coaching and skills.

With the enriched data available for decisioning, coupled with the amazing capabilities we have for real time segmentation, strategy scripting, context-sensitive screens, and rules-based workflow management in our next generation collections systems, we are at a crossroads in the evolution of collections.

Let’s not forget some of the “nuts and bolts” that drive operational performance and ensure success.

Something old can be something new. Examine your internal processes aimed at producing the best possible skills at all collector levels and ensure that you are not missing the easiest opportunity to improve your results.

Back during World War I, the concept of “triage” was first introduced to the battlefield.  Faced with massive casualties and limited medical resources, a system was developed to identify and select those who most needed treatment and who would best respond to treatment.  Some casualties were tagged as terminal and received no aid; others with minimal injuries were also passed over.  Instead, medical staff focused their attentions on those who required their services in order to be saved.  These were the ones who needed and would respond to appropriate treatment. 

Our clients realize that the collections battlefield of today requires a similar approach.  They have limited resources to face this mounting wave of delinquencies and charge offs.  They also realize that they can’t throw bodies at this problem. They need to work smarter and use data and decisioning more effectively to help them survive this collections efficiency battle.

Some accounts will never “cure” no matter what you do.  Others will self-cure with minimal or no active effort. Taking the right actions on the right accounts, with the right resources, at the right time is best accomplished with advanced segmentation that employs behavioral scoring, bureau-based scores and other relevant account data. The actual data and scores that should be used depend on the situation and account status, and there is no one-size-fits-all approach.

 

How is your financial institution/organization working to improve your collections work stream?

What are some of your keys for collections efficiency?

What tools do you use to manage your collections workflow?

In addition to behavioral models, collections and account management groups need the ability to implement collections workflow strategies in order to effectively handle and process accounts, particularly when the optimization of resources is a priority. While the behavioral models will effectively evaluate and measure the likelihood that an account will become delinquent or result in a loss, strategies are the specific actions taken, based on the score prediction, as well as other key information that is available when those actions are appropriate.

Identifying high-risk accounts, for example, may result in strategies designed to accelerate collections management activity and execute more aggressive actions. On the other hand, identifying low-risk accounts can help determine when to take advantage of cost-saving actions and focus on customer retention programs.  Effective strategies also address how to handle accounts that fall between the high- and low-risk extremes, as well as accounts that fall into special categories such as first payment defaults, recently delinquent accounts and unique customer or product segments.

To accommodate lenders with systems that cannot support either behavioral scorecards or strategies, Experian developed the powerful service bureau solution, Portfolio Management Package, which is also referred to as PMP. To use this service, lenders send Experian customer master file data on a daily basis. Experian processes the data through the Portfolio Management Package system which includes calculating Fast Start behavior scores and identifying special handling accounts and electronically delivers the recommended strategies and actions codes within hours. Scoring and strategy parameters can be easily changed, as well as portfolio segmentation, special handling options and scorecard selections.

PMP also supports Champion Challenger testing to enable users to learn which strategies are most effective. Comprehensive reports suites provide the critical information needed for lenders to design strategies and evaluate and compare the performance of those strategies.
 

Optimization is a very broad and commonly used term today and the exact interpretation is typically driven by one's industry experience and exposure to modern analytical tools. Webster defines optimize as: "to make as perfect, effective or functional as possible". In the risk/collections world, when we want to optimize our strategies as perfect as technology will allow us, we need to turn to advanced mathematical engineering. More than just scoring and behavioral trending, the most powerful optimization tools leverage all available data and consider business constraints in addition to behavioral propensities for collections efficiency and collections management.

A good example of how this can be leveraged in collections is with letter strategies. The cost of mailing letters is often a significant portion of the collections operational budget. After the initial letter required by the Fair Debt Collection Practice Act (FDCPA) has been sent, the question immediately becomes: “What is the best use of lettering dollars to maximize return?” With optimization technology we can leverage historical response data while also considering factors such as the cost of each letter, performance of each letter variation and departmental budget constraints, while weighing the alternatives to determine the best possible action to take for each individual customer.

n short, cutting edge mathematical optimization technology answers the question:

"Where is the point of diminishing return between collections treatment effectiveness and efficiency / cost?"

 

Currently, financial institutions focus on the existing customer base and prioritize collections to recover more cash, and do it faster. There is also a need to invest in strategic projects with limited budgets in order to generate benefits in a very short term, to rationalize existing strategies and processes while ensuring that optimal decisions are made at each client contact point.
To meet the present challenging conditions, financial institutions increasingly are performing business reviews with the goal of evaluating needs and opportunities to maximize the value created in their portfolios.  Business reviews assess an organization’s capacity to leverage on existing opportunities as well as identifying any additional capability that might be necessary to realize the increased benefits.

An effective business review covers the following four phases:

• Problem definition: Establish and qualify what the key objectives of the organization are, the most relevant issues to address, the constraints of the solution, the criteria for success and to summarize how value management fits into the company’s corporate and business unit strategies.
• Benchmark against leading practice: Strategies, processes, tools, knowledge, and people have to be measured using a review toolset tailored to the organization’s strategic objectives.
• Define the opportunities and create the roadmap: The elements required to implement the opportunities and migrating to the best practice should be scheduled in a phased strategic roadmap that includes the implementation plan of the proposed actions.
• Achieve the benefits: An ROI-focused approach, founded on experience in peer organizations, will allow analysis of the cost-benefits of the recommended investments and quantify the potential savings and additional revenue generated. A continuous fine-tuning (i.e. impact of market changes, looking for the next competitive edge and proactively challenge solution boundaries) will ensure the benefits are fully achieved.

Today’s blog is an extract of an article written by Burak Kilicoglu, an Experian Global Consultant

To read the entire article in the April edition of Experian Decision Analytics’ global newsletter e-news, please follow the link below:

http://www.experian-da.com/news/enews_0903/Story2.html
 

The way in which you communicate with your customers really does impact the effectiveness of your collections operation.

At the heart of any collections management operation is the quality of the correspondence and, in particular, the tone of voice adopted with the debtor. In short, what you say is important, but how you say it has a critical impact on its effectiveness.

To help guide best practice in this area and provide areas for consideration when designing and implementing customer letters within a collections strategy, Experian commissioned a study to explore how consumers react to the words used to communicate with them about their debt.

Key findings:

• An appropriate tone, clear detail of the consequences and a conciliatory approach are effective in the early phases of collection 
• Fees and charges and negative impacts on credit ratings were key motivators to pay
•  Charges applied to an account for issuing a letter is disliked and likely to encourage many to contact the organisation to express their frustration 
• After 3 months a strong emphasis on serious action is appropriate, including reference to legal action or debt collection agency involvement 
• Support should be offered, wherever possible, to aid those in difficulty 
• Letters should avoid an informal and patronising tone 
• Lengthy letters have a low impact and are often not fully read, resulting in important messages being missed 
• Use of red to highlight and focus on a specific point is effective
• Use of red to highlight more than one point is counter-effective 

To download the entire paper* and view other best practice briefings, follow the link below to the global Experian Decision Analytics collections briefing papers page:

http://www.experian-da.com/resources/briefingpapers.html

* Secure download account required. You can sign up for one today - FREE.

2007 and 2008 saw a rapid change of consumer behaviors and it is no surprise to most collections professionals that the existing collections scoring models and strategies are not working as well as they used to. These tools and collections workflow practices were mostly built from historical behavioral and credit data and assume that consumers will continue to behave as they had in the past. We all know that this is not the case, with an example being prioritization of debt and repayment patterns.

Its been assumed and validated for decades that consumers will let their credit card lines go before an auto loan and that the mortgage obligations would be the last trade to remain standing before bankruptcy. Today, that is certainly not the case and there are other significant behavior shifts that are contributing to today's weak business models.

There are at least three compelling reasons to believe now is the right time for updates:

• It appears that most of the consumer behavioral shift is over for collections. While economic recovery will take many years, more radical changes in the economy are unlikely. Most experts are calling for a housing bottom sometime in 2009 and there are already signs of hope on Wall Street.
   
• What is built now shouldn't be obsolete next year. A slow economic recovery probably means that the life of new models will be fairly long and most consumers won't be able to improve their credit and collections scores anytime soon. Even after financial recovery (which at this point is not likely over the short term for many that are already in trouble), it can take two to seven years of responsible payment history before a risk assessment is improved.
   
• We now have the data with which to make the updates. It takes six to12 months of stability to accumulate sufficient data for proper analysis and so far 2009 hasn't seen much behavioral volatility. Whether you build or buy, the process takes awhile, so if you still need a few more months of history in will be in hand when needed if the projects are kicked off soon.

Due to the recent economic events, increased collections workloads are straining client infrastructures and resources. Most clients in North America operate their delinquent accounts on legacy collections systems that are inflexible and expensive to manage and maintain. A recent and abrupt spending shift has drifted toward collections tools, data, operational, efficient workflow and decisioning systems.

On the information technology front, the collections workflow software industry is on the brink of a technology shift from legacy systems to modern next generation offerings that are typically coded in Java. Very few collections software vendors have actually released and implemented their next generation products and are preparing to do so over the next six to 12 months. Clients are aware of this technology shift and the interest of many end users has been heightened and many are actively researching and shopping.

Reducing operational costs is an urgent priority for most financial institutions and utilities. Legacy systems do not allow management to change strategies or flows quickly or in a cost effective manner, which leaves most collections departments unable to keep up with rapidly changing environments and business objectives. Clients also have critical business needs to reduce losses, improve cash flow and promote customer satisfaction. 

Many clients maintain multiple systems and it is common that these disparate systems do not communicate with each other. Consolidating collections operations and databases into one central system is strongly desired and presents an opportunity for significant financial gain.

 

Our current collections management landscape is seeing unprecedented consumer debt burdens:

• Total consumer debt o/s is at $14 trillion as of Jan ’09
• Revolving debt o/s has reached $1 trillion
• The unemployment rate is at 7.6% and is expected to continue to rise
• Credit card and Home Equity Line Of Credit issuers reduced available credit by approximately $2 Trillion last year and more reductions are expected in 2009

There is a continuing rise in delinquencies and chargeoffs.  Here are some examples from our recent research:

• 8.5% of Prime Adjustable Rate Mortgages are now delinquent which shows an increase of 491% over this time last year
• 25% of all sub prime mortgages are now 60+ days delinquent
• Delinquencies for prime bankcard customers have increased 286% over the last 2 years
• 34% of all scoreable consumers (those who have sufficient trade information to calculate a score) now have a collection account.

Compound these by a decline in the relative collectability of these accounts and you see:

• 9 million households now have negative equity
• 20% of 401(k) accounts have been tapped for loans (usually at a cost of 45% in penalties and fees to the account holder)
• According to the Federal Reserve, in late 2006 – at the height of the sub prime mortgage boom - the U.S. experienced a negative savings rate for the first time since the Great Depression.

In addition to behavioral models, collections management and account management groups need the ability to implement strategies in order to effectively handle and process accounts, particularly when the optimization of resources is a priority. While the behavioral models will effectively evaluate and measure the likelihood that an account will become delinquent or result in a loss, strategies are the specific actions taken, based on the score prediction, as well as other key information that is available when those actions are appropriate.

Identifying high-risk accounts, for example, may result in collections strategies designed to accelerate collections activity and execute more aggressive actions and increase collections efficiency. On the other hand, identifying low-risk accounts can help determine when to take advantage of cost-saving actions and focus on customer retention programs. Effective strategies also address how to handle accounts that fall between the high- and low-risk extremes, as well as accounts that fall into special categories such as first-payment defaults, recently delinquent accounts and unique customer or product segments.

To accommodate lenders with systems that cannot support either behavioral scorecards or automated strategy assignments a hosted collections software decisioning system can close the gap. To use these services master file data needs to be transmitted (securely) on a regular basis. The remote decision engine then calculates behavioral scores, identifies special handling accounts and electronically delivers the recommended strategy code or string of actions to drive treatments.
 

Behavioral scoring is one of the most important tools that allow collections management and account management groups to evaluate accounts in an efficient and cost-effective manner. Although behavioral models are developed in a similar manner as new applicant models, there are several key differences that make behavioral models a better choice for many account management applications and collections workflow systems:

By using only internal master file data as opposed to external credit bureau data, for example, accounts can be regularly evaluated without incremental cost. The most common practices are to score accounts on a weekly or monthly basis, which allows for quick strategic responses to a customer’s change in behavior. Frequent evaluations can result in automated or manual actions such as the acceleration or deceleration of collections efforts, adjusting credit limits and changing terms and conditions.

The performance definitions of behavioral scores are very specific to each strategy and task, and it is typically not advised to use models in applications for which they were not designed. For example, a new applicant model definition of “bad” may be a high probability of charge off during the initial term of a line of credit. For collections strategy, a more appropriate bad definition might be the likelihood of an account rolling to the next delinquency bucket, regardless of the age of the account. 

Behavioral models also have a much shorter outcome period of three to four months versus new applicant models that forecast over one to two years. Since behaviors with one creditor can typically be recognized more quickly than with all lending institutions associated with a particular debtor, behavioral models provide a unique and timely evaluation of the ongoing risk once the account is already on the books.