Telecommunications, Cable & Utilities

By: Wendy Greenawalt Given the current volatile market conditions and rising unemployment rates, no industry is immune from delinquent accounts. However, recent reports have shown a shift in consumer trends and attitudes related to cellular phones. For many consumers, a cell phone is an essential tool for business and personal use, and staying connected is a very high priority. Given this, many consumers pay their cellular bill before other obligations, even if facing a poor bank credit risk. Even with this trend, cellular providers are not immune from delinquent accounts and determining the right course of action to take to improve collection rates. By applying optimization, technology for account collection decisions, cellular providers can ensure that all variables are considered given the multiple contact options available. Unlike other types of services, cellular providers have numerous options available in an attempt to collect on outstanding accounts.  This, however, poses other challenges because collectors must determine the ideal method and timing to attempt to collect while retaining the consumers that will be profitable in the long term.  Optimizing decisions can consider all contact methods such as text, inbound/outbound calls, disconnect, service limitation, timing and diversion of calls.  At the same time, providers are considering constraints such as likelihood of curing, historical consumer behavior, such as credit score trends, and resource costs/limitations.  Since the cellular industry is one of the most competitive businesses, it is imperative that it takes advantage of every tool that can improve optimizing decisions to drive revenue and retention.  An optimized strategy tree can be easily implemented into current collection processes and provide significant improvement over current processes.

By: Tom Hannagan Understanding RORAC and RAROC I was hoping someone would ask about these risk management terms…and someone did. The obvious answer is that the “A” and the “O” are reversed. But, there’s more to it than that. First, let’s see how the acronyms were derived. RORAC is Return on Risk-Adjusted Capital. RAROC is Risk-Adjusted Return on Capital. Both of these five-letter abbreviations are a step up from ROE. This is natural, I suppose, since ROE, meaning Return on Equity of course, is merely a three-letter profitability ratio. A serious breakthrough in risk management and profit performance measurement will have to move up to at least six initials in its abbreviation. Nonetheless, ROE is the jumping-off point towards both RORAC and RAROC. ROE is generally Net Income divided by Equity, and ROE has many advantages over Return on Assets (ROA), which is Net Income divided by Average Assets. I promise, really, no more new acronyms in this post. The calculations themselves are pretty easy. ROA tends to tell us how effectively an organization is generating general ledger earnings on its base of assets.  This used to be the most popular way of comparing banks to each other and for banks to monitor their own performance from period to period. Many bank executives in the U.S. still prefer to use ROA, although this tends to be those at smaller banks. ROE tends to tell us how effectively an organization is taking advantage of its base of equity, or risk-based capital. This has gained in popularity for several reasons and has become the preferred measure at medium and larger U.S. banks, and all international banks. One huge reason for the growing popularity of ROE is simply that it is not asset-dependent. ROE can be applied to any line of business or any product. You must have “assets” for ROA, since one cannot divide by zero. Hopefully your Equity account is always greater than zero. If not, well, lets just say it’s too late to read about this general topic. The flexibility of basing profitability measurement on contribution to Equity allows banks with differing asset structures to be compared to each other.  This also may apply even for banks to be compared to other types of businesses. The asset-independency of ROE can also allow a bank to compare internal product lines to each other. Perhaps most importantly, this permits looking at the comparative profitability of lines of business that are almost complete opposites, like lending versus deposit services. This includes risk-based pricing considerations. This would be difficult, if even possible, using ROA. ROE also tells us how effectively a bank (or any business) is using shareholders equity. Many observers prefer ROE, since equity represents the owners’ interest in the business. As we have all learned anew in the past two years, their equity investment is fully at-risk. Equity holders are paid last, compared to other sources of funds supporting the bank. Shareholders are the last in line if the going gets rough. So, equity capital tends to be the most expensive source of funds, carrying the largest risk premium of all funding options. Its successful deployment is critical to the profit performance, even the survival, of the bank. Indeed, capital deployment, or allocation, is the most important executive decision facing the leadership of any organization. So, why bother with RORAC or RAROC? In short, it is to take risks more fully into the process of risk management within the institution. ROA and ROE are somewhat risk-adjusted, but only on a point-in-time basis and only to the extent risks are already mitigated in the net interest margin and other general ledger numbers. The Net Income figure is risk-adjusted for mitigated (hedged) interest rate risk, for mitigated operational risk (insurance expenses) and for the expected risk within the cost of credit (loan loss provision). The big risk management elements missing in general ledger-based numbers include: market risk embedded in the balance sheet and not mitigated, credit risk costs associated with an economic downturn, unmitigated operational risk, and essentially all of the strategic risk (or business risk) associated with being a banking entity. Most of these risks are summed into a lump called Unexpected Loss (UL). Okay, so I fibbed about no more new acronyms. UL is covered by the Equity account, or the solvency of the bank becomes an issue. RORAC is Net Income divided by Allocated Capital. RORAC doesn’t add much risk-adjustment to the numerator, general ledger Net Income, but it can take into account the risk of unexpected loss. It does this, by moving beyond just book or average Equity, by allocating capital, or equity, differentially to various lines of business and even specific products and clients. This, in turn, makes it possible to move towards risk-based pricing at the relationship management level as well as portfolio risk management.  This equity, or capital, allocation should be based on the relative risk of unexpected loss for the different product groups. So, it’s a big step in the right direction if you want a profitability metric that goes beyond ROE in addressing risk. And, many of us do. RAROC is Risk-Adjusted Net Income divided by Allocated Capital. RAROC does add risk-adjustment to the numerator, general ledger Net Income, by taking into account the unmitigated market risk embedded in an asset or liability. RAROC, like RORAC, also takes into account the risk of unexpected loss by allocating capital, or equity, differentially to various lines of business and even specific products and clients. So, RAROC risk-adjusts both the Net Income in the numerator AND the allocated Equity in the denominator. It is a fully risk-adjusted metric or ratio of profitability and is an ultimate goal of modern risk management. So, RORAC is a big step in the right direction and RAROC would be the full step in management of risk. RORAC can be a useful step towards RAROC. RAROC takes ROE to a fully risk-adjusted metric that can be used at the entity level.  This  can also be broken down for any and all lines of business within the organization. Thence, it can be further broken down to the product level, the client relationship level, and summarized by lender portfolio or various market segments. This kind of measurement is invaluable for a highly leveraged business that is built on managing risk successfully as much as it is on operational or marketing prowess.

The value of a good decision can generate $150 or more in customer net present value, while the cost of a bad decision can cost you $1,000 or more.  For example, acquiring a new and profitable customer by making good prospecting and approval and pricing decisions and decisioning strategies may generate $150 or much more in customer net present value and help you increase net interest margin and other key metrics.  While the cost of a bad decision (such as approving a fraudulent applicant or inappropriately extending credit that ultimately results in a charge-off) can cost you $1,000 or more. Why is risk management decisioning important? This issue is critical because average-sized financial institutions or telecom carriers make as many as eight million customer decisions each year (more than 20,000 per day!).  To add to that, very large financial institutions make as many as 50 billion customer decisions annually.  By optimizing decisions, even a small 10-to-15 percent improvement in the quality of these customer life cycle decisions can generate substantial business benefit. Experian recommends that clients examine the types of decisioning strategies they leverage across the customer life cycle, from prospecting and acquisition, to customer management and collections.  By examining each type of decision, you can identify those opportunities for improvement that will deliver the greatest return on investment by leveraging credit risk attributes, credit risk modeling, predictive analytics and decision-management software.        

-- 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: https://www.experian.com/whitepapers/index.html

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?"