Collections & Debt Recovery
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?IntroductionFinancial 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 StartedBefore 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 motivatorThe 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: Tracy Bremmer Preheat the oven to 350 degrees. Grease the bottom of your pan. Mix all of your ingredients until combined. Pour mixture into pan and bake for 35 minutes. Cool before serving. Model development, whether it is a custom or generic model, is much like baking. You need to conduct your preparatory stages (project design), collect all of your ingredients (data), mix appropriately (analysis), bake (development), prepare for consumption (implementation and documentation) and enjoy (monitor)! This blog will cover the first three steps in creating your model! Project design involves meetings with the business users and model developers to thoroughly investigate what kind of scoring system is needed for enhanced decision strategies. Is it a credit risk score, bankruptcy score, response score, etc.? Will the model be used for front-end acquisition, account management, collections or fraud? Data collection and preparation evaluates what data sources are available and how best to incorporate these data elements within the model build process. Dependent variables (what you are trying to predict) and the type of independent variables (predictive attributes) to incorporate must be defined. Attribute standardization (leveling) and attribute auditing occur at this point. The final step before a model can be built is to define your sample selection. Segmentation analysis provides the analytical basis to determine the optimal population splits for a suite of models to maximize the predictive power of the overall scoring system. Segmentation helps determine the degree to which multiple scores built on an individual population can provide lift over building just one single score. Join us for our next blog where we will cover the next three stages of model development: scorecard development; implementation/documentation; and scorecard monitoring.
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 effectiveUse 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.
Champion/Challenger strategy testing is performed using … This allows strategies to be tested before rolling them out across the entire portfolio. The purpo
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.
Have you ever wondered how your current collections workflow process evolved to its current state? To start at the beginning, let’s rewind to medieval England … The Tallyman The earliest known collections system was essentially a door-to-door program, as there were no modern day devices to make the process more efficient. The system of record at that time was typically a hardwood stick with carved notches representing loans and payments between a lender and borrower. This door-to-door collector was known as the Tallyman, which referred to the collection of tally sticks he carried to document financial transactions. The beginning of modern times As technology evolved, telephones and letters became the collections management tools of choice, with a personal visit being a last resort action. The process where a collector managed the repayment strategy and relationships for his assigned customers was still in practice. Collections operations were typically in decentralized branches and small teams of skilled collectors were able to effectively manage this “cradle-to-grave” approach. Yesterday When expense management became a priority, the migration to larger, centralized operations became an industry trend. Many companies found it difficult to hire large teams of highly-skilled collectors in their geographic regions and the bucket system was born. The concept was simple and effective -- let the less experienced staff work the accounts that are the easiest to collect and focus the experienced collectors on the more difficult cases. Advanced collections tools such as automatic dialers arrived on the market to increase efficiency and were shortly followed by decision engines used to support behavioral scoring and segmentation strategies. Today Current trends in collections include the migration towards a risk-based segmentation and strategy approach. Cutting edge tools and collection management software, designed to address today’s collections business objectives, are hitting the market and challenging the traditional bucket approach most of us are used to. As the economic conditions of the past few years deteriorated, many organizations began shifting their spending focus towards the collections department and this, in turn, has inspired investment and innovation from software, analytics and data vendors. New collections scores were recently unveiled that yield predictiveness that has never been seen and collections data products have become significantly more sophisticated. Modern technology is also empowering collections managers to control the destiny of their business units by freeing them from the constraints of over-burdened IT departments and inflexible systems. There is also an emerging trend to consider the collective power of multiple products working in tandem. Collections experts are finding that the benefit of the complete solution equals much more than just the sum of the parts. Tomorrow Once we all migrate to the next level and employ today’s modern marvels to make our businesses more productive and efficient, what’s next? It’s highly probable that tomorrow’s collections workflow will consider the entire relationship and profit potential of a customer before a collections action is executed. Additionally, the value in considering the entire credit and risk picture associated with a customer will be better understood and we will learn when each of the holistic view options is most appropriate. There are a number of roadblocks in the way today, including disparate systems and databases and siloed business units with goals and objectives that are not aligned. Will we eventually get there? The business leaders with long-range vision certainly will … just as some unknown visionary had the initiative to embrace emerging technology and abandon his tally sticks. For more information and to read the Decision Analytics newsletter that features one of my previous blogs, "Next generation collections systems", click here.