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With billions of delinquent dollars still uncollected around the world, collection centers are searching for new, more productive and profitable ways to pursue overdue accounts. In this quest, many companies have re-evaluated long-held beliefs and have actually found that some of these assumptions are restricting—rather than promoting—their success.

~ by Lois Brown

With billions of delinquent dollars still uncollected around the world, collection centers are searching for new, more productive and profitable ways to pursue overdue accounts. In this quest, many companies have re-evaluated long-held beliefs and have actually found that some of these assumptions are restricting—rather than promoting—their success. As a result, they have made significant changes in their collections process; in some cases, doing the opposite of what they had done before. The payoff for these companies has been measurable improvements in collection results.

Collection calling operations that are not achieving their desired results may be trapped in one or more of today’s top five outdated collection beliefs. Even one of these outda ted habits could add up to several million dollars in losses annually. However, companies do not have to unquestioningly follow these practices. Today there are intelligent best-practices processes that collections centers can adopt to overcome their old beliefs and start collecting more delinquent dollars, retaining valuable customer relationships, and boosting their profitability.

OUTDATED BELIEF #1: Behavior Scores Deliver the Best Customer Targeting.

Behavior scoring is the most commonly used customer analysis process in today’s collection centers. However, it has the disadvantage of lumping customers into broad categories rather than considering each account individually. As a result, behavior scoring is limited in its ability to treat each individual account in a way that will achieve the desired response. When it comes to collecting delinquent dollars, this difference can be worth millions of dollars per year.

Behavior scoring uses a statistical method to predict the likelihood that an account will make a payment, reach a later stage of delinquency, or charge-off within a period of months. This approach classifies delinquent accounts into high-risk, medium-risk, and low-risk categories based on the value of a behavior score. This can lead to non-optimal decisions, such as an excessive focus on high-risk accounts or treating all high-risk accounts with the same level of focus. This approach can also unnecessarily devote resources to accounts that will never pay and it can needlessly annoy customers who would have paid without being hassled. Penalties can include fewer dollars collected, increased attrition, and higher costs.

NEW THINKING: In early-stage portfolios, 20 to 50 percent of delinquent customers will pay even without an agent contact. The question is which 20 to 50 percent? Action-specific modeling answers this critical question by predicting each individual account’s need for contact, so that the contact center’s agent resources can focused their time and resources where they will have the greatest impact.

Given the tremendous bottom-line impact, many larger financial service institutions have already augmented their traditional behavioral scoring process with action-specific modeling solutions. For example, one of today’s largest diversified financial services companies deployed action -specific modeling and found that with its one-cycle delinquent portfolio, about one-third of the accounts were likely to self-cure. Rather than calling these accounts, resources were focused on the fewer than 60 percent who truly needed a call to cure.

By focusing on those accounts, the bank reduced charge-offs by 100 basis points. Because action- specific modeling eliminated self-cures from the calling pool, collectors did not call early-stage delinquent account holders who were likely to self-cure – some of whom may have been offended by a collections call. Consequently, the bank also measured a four-percent reduction in attrition. With the cost to replace an account estimated at $100 to $150, these attrition-reduction savings also added to the bank’s profits.

 

BOTTOM LINE: Treat each account individually, not as a member of a large group.

OUTDATED BELIEF #2: It Takes Trial-and-Error to Find the Best Contact Channel for Each Customer.

To control resource costs, some collections operations are experimenting with alternate contact methods, such as automated call, letter, e-mail, and website communication Using trial-and-error to determine the best method for each customer is both time-consuming and risky. If people who really need agent calls to cure are sent letters instead, roll-rates and cash flow may be adversely affected.

NEW THINKING: New optimization technology allows you to know in advance which contact channel is likely to be the most productive and cost-effective for each delinquent account. Not only can these optimization solutions determine who should be called—in other words, who really needs a call to cure—but they can also predict the best method of contact to maximize dollars collected and minimize costs. The most advanced technology solutions actually optimize the entire day’s delinque nt portfolio so that the most dollars possible are collected using the available resources. This technology uses a sophisticated optimization algorithm that simultaneously considers four critical elements:

(1) the best action for each account,

(2) the needs of an entire account set,

(3) actual resources and business constraints, and

(4) the collection center’s overall business objectives.

Through this optimization process, companies gain several benefits including:

• Improving cure rates, resulting in more dollars collected along with lower roll rates and fewer charge-offs;

• Reducing call volumes, thereby, making better use of collections and call center resources; and

• Improving customer retention by eliminating collection calls to accounts likely to pay without a call.

 

BOTTOM LINE: Sophisticated optimization technology can now be used to quickly and safely determine the best contact channel for all accounts.

OUTDATED BELIEF #3: Heavy List Penetration is the Best Way to Collect.

For those accounts who do need an agent call to cure, many call centers believe that maximizing penetration is essential. The rational is that the more times they penetrate their lists, the quicker they will achieve the goal of collecting the most dollars. But heavy list penetration can be unnecessarily costly and yield disappointing promises-to-pay and roll-rate reductions.

NEW THINKING: A better way to improve productivity, reduce expenses, and increase dollars collected is to make calls at the best time of day to reach each responsible party. Today a growing number of companies are aiming for accuracy over brute force by adding intelligent predictive technologies to identify the best time of day to call each account. Even in cases where more than one pass is required, making all calls at the best times of day will result in more promises-to-pay and fewer overall calls, because more right parties will have been reached on the first pass. One of the nation’s largest banks has achieved enormous gains by installing a sophisticated call targeting technology that increased the rate of right- party contacts per collector hour and increased the ratio of right-to-wrong party contacts.

The solution creates an optimized call schedule each day, based on the value and “contact-ability” of each account at various times of the day. The bank gained several benefits including:

• Increasing collector productivity by increasing right-party contact rate (15%+) and decreasing wrong-party contacts,

• Reducing roll-rates, and

• Decreasing agent resources required for daily campaign management.

 

BOTTOM LINE: Call targeting improves results with or without heavy list penetration.

OUTDATED BELIEF #4: Your Best Agents Should Call Your Toughest Customers.

Theoretically it seems logical to assign your best agents to call the toughest accounts, whether for collections or cross-sell. But, if this assumption is wrong, it means your best agents are being wasted on accounts where higher skills (and their associated higher salaries) have little impact.

NEW THINKING: Research with sales agents has shown that agents’ skill levels, indeed, have a great impact when talking to receptive customers. Skilled agents can, in these cases, sell more in less time. But the research also showed that highly skilled agents delivered no advantage when selling to the most difficult prospects. The company’s counterintuitive finding showed that the hardest prospects were difficult to approach under any conditions. If the call center had followed its intuition without testing the theory, it would have degraded its overall agent performance. This finding translates to your skilled collection agents and delinquent customers and means that your general agent pool will be equally as effective with your toughest accounts as your skilled agents.

BOTTOM LINE: If you are putting skilled agents against your most difficult accounts, you should conduct an unbiased test to find out if this strategy is really paying off.

OUTDATED BELIEF #5: Local Strategy Control is Best.

With multiple call centers, strategy is often left up to each center because there is a belief that each local floor operation and download list is somehow unique. What’s more, you may allow strategy to be handled locally because a group of call records is downloaded to one specific dialer and called only from that dialer. There are many problems with this outdated approach: Agents across multiple sites may not be fully utilized, campaigns may not be implemented consistently, and the individual customers are vulnerable to severe weather and other downtime risks.

NEW THINKING: New-generation list management technologies remove these limitations by holding a centralized global campaign and dynamically directing call records from any download to any networked dialer. The result is increased productivity as the workload is leveled across agent resources and as strategies are executed consistently and without interruption.

 

BOTTOM LINE: The collections operation is more productive with a centralized list management technology keeping all call strategies on track in a single or multiple centers.

Conclusion

Mounting consumer debt around the world is a challenge for every company. In today’s complex and increasingly risky business world, it is necessary to make every step of the collections process as effective and efficient as possible. Often this requires updating long-held beliefs with the addition of new solutions that solve today’s biggest collection problems. Today these five outdated practices are being overcome by companies who’ve found that intelligent predictive technologies can measurably elevate their collections efforts to a new, significantly higher level of productivity.

” Lois Brown is Vice President of Marketing at Austin Logistics Incorporated, headquartered in Austin,
Texas. She oversees brand positioning, marketing communications, and new product definition for the
companies’ expanding line of predictive analytic and optimization solutions. “

About Kollect Systems

Kollect Systems is an innovative tech platform provider in Collections, Debt Recovery, Agency, Legal and Repossession management. In the areas of Banking, Credit Cards and Lending operations, Kollect provides KollectApps (BankTech) software solutions which leverage AI based decisioning and workflow technologies to help perform Collections & Debt Recovery processes automation better. For Hire Purchase and Leasing companies, Kollect provides KollectRepo  (BankTech) to enable the ecosystem for lenders, repo agents, store yards and auctioning advance process automation. And for mid-size to large scale enterprise companies, KollectValley (FinTech) is used to automate Receivables Collections, Notifications, Reminders, Segmentation & Risk Scoring, e-Invoicing, Customer Portal & Online Payments better.  Kollect’s solutions in summary are as follows  :

• KollectApps (BankTech),

• KollectRepo (BankTech) and

• KollectValley (FinTech)