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- Test
- Yes

By: Tom Hannagan Part 4 Let’s dig a bit deeper into why Peer Group 1’s margins didn’t improve. We see two possible reasons: Total deposit balances declined from 72 percent of average assets to 70 percent. This means that a larger amount had to be borrowed to fund their assets. Secondly, non-interest bearing demand deposits declined from 4.85 percent of average assets to 4.24 percent. So, fewer deposit balances relative to total asset size, along with a lower proportion of interest-cost-free deposits, appear to have made the difference. Fee income Non-interest income, again as a percent of average total assets, was down to 1.12 percent from 1.23 percent in 2007. This was a decline of 9 percent. For Peer Group 1 (PG1), fees have also been steadily declining relative to asset size, down from 1.49 percent of assets in 2005. A lot of fee income is deposit based and largely based on non-interest bearing deposits. So, the declining interest-free balances, as a percent of total assets, are a source of pressure on fee income and have a negative impact on net interest margins. Operating expenses Operating expenses constituted more bad news as they increased from 2.63 percent to 2.77 percent of average assets. Most of the large scale cost-cutting didn’t get started early enough to favorably impact this number for last year. Historically, this metric has moved down, irregularly, as the size of the largest banks has grown. This number stood at 2.54 percent in 2006, for instance. We saw increase in both 2007 and again in 2008. As a result of the decline in margins and the larger percentage decline in fee income, while operating costs increased, the Peer Group 1 efficiency ratio lost ground from 57.71 percent in 2007 up to 63.70 percent in 2008. This 10 percent increase is a move to the bad. It means every dollar in gross revenue [net interest income + fee income] cost them almost 64 cents in administrative expenses in 2008. This metric averaged 55 cents in 2005/2006. The total impact of changes in margin performance, fee income, operating expenses and the 2008 increase in provision expense of 87 basis points, we arrive at a total decline in pre-tax operating income of 1.23 percent on total assets. That is a total decline of 80 percent from the pre-tax performance in 2007 of 1.53 percent pre-tax ROA to the 2008 result for the group of only .30 percent pre-tax ROA. It would appear that banks have not been utilizing pricing enough credit risk into their loan rates. This would be further confirmed if you compared bank loan rates to the historic risk spreads and absolute rates that the market currently has priced into both investment grade and below-investment-grade corporate bonds. These spreads have decreased some very recently, but it is predicted that more credit risk is present than bank lending rates would indicate.

Part 3 Reducing operational and overhead costs starts with the automation of tasks that would otherwise be performed by a human resource. By leveraging an advanced segmentation approach, it is possible to better identify accounts that will not require collector intervention. While automation is not a new concept to collections, significant benefits of modern systems include: • enabling more functions to be automated; • effectiveness of the automated functions to be validated; and • more changes made per year versus legacy systems. Fixing a bad phone number: The old way To illustrate effective automation, let’s use an example where an account is found to have a bad phone number. A common approach to this problem might be for the outbound collector to route the account to a skip specialist who can perform research. This often has the receiving party starting the process after the nightly batch process has transferred the account across departments. If a phone number is found, the account may be manually routed back to an outbound queue and if not, a no-contact letter may be generated. Additionally, there are tasks that need to be performed such as noting accounts that consume a collector’s time. Fixing a bad phone number: The new way A more efficient and cost-effective approach would be for the employee identifying the need for a new number to click a pre-defined button to let the collections system know of the issue. The system could then automatically call out to an external data source to: • collect the new number; • repopulate the appropriate field; • reroute the account back to the most appropriate outbound queue; • log a history of all automated functions performed, and • do all of this within just a few seconds! If the appropriate number cannot be located, the system would know which letter to send and then route the account to the most appropriate holding queue. Reducing operational costs After automation, the operational costs are further reduced by identifying which actions can be effectively replaced by lower-cost options that yield the same results, or even eliminating actions that present no substantial value. For example, why make a call when a letter will suffice? And what happens if we subsequently replace that letter with a text message or take no action at all? Intelligent features of modern systems such as champion/challenger testing can be employed to support a continuous learning process that increases the financial benefits of automation as experience and knowledge is gained. As new automation is introduced and validated as beneficial, other improvement theories can be tested and subsequently abandoned or adopted. Considering the possible impact of automation and action reductions on cost savings let’s assume that three dial attempts are made on the average delinquent account in the first 30 days at a cost of 25 cents each and on the fourth attempt there is a right party contact, which costs an additional $2.50 (assuming the talk time is five minutes). Adding one letter at 75 cents, we have a total cost to collect of $4.00 before the account hits 31 days past due. With 250,000 customers entering collections each month, we can save $200,000 each month in the early stage alone with just a 20 percent improvement. This result could easily be achieved by reducing talk time and eliminating unnecessary actions or unproductive call attempts. Annually that adds up to approximately $2.5 million dollars in savings, in this example. Champion/challenger tests, as well as, the improved functionality of modern systems can also be extended beyond the in-house work stream. Evaluating and comparing external agencies can significantly improve agency performance as well as enable the lender to better manage placement costs. For example, if a lender allocates 1,000 accounts to an external agency each month, with an average balance of $3,000, the total dollars allocated annually is $36 million. If 22 percent of the debt is collected and a 25 percent commission is charged, the net to the lender is nearly $6 million. Improving that return by a mere 4 percent through better allocation strategies, which is a conservative goal, we add another million to the bottom line each year. By factoring in the ability of next generation collections systems to automate most aspects of the placement process itself, including recalling accounts, we further improve efficiencies, free up valuable resources and allow management greater control of the process. Additional benefits of functionally rich modern systems also enable management to grant external resources various levels of remote access to the collections systems to better monitor activities and ensure that transactional data is properly captured. In addition to granting external agencies remote access, modern collections systems can also enable collectors to work from home-based workstations to further reduce operational costs. Many industry analysts see this as an emerging trend over the next few years, particularly when productivity can be monitored in real-time. My next blog will continue the discussion on the benefits of next generation collections systems and will provide details on improved change management processes.

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 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.Future related articles will dive deeper into the various segmentation approach options and explain how advanced decisioning provides additional benefit over the score-only methods.


