Whether you are currently using scoring, have tried and failed to use scoring or are considering using scoring in your collections operation, doing it profitably can be an elusive endeavor. You can hardly turn a page in our industry reading without hearing someone tout the benefits of it. But is scoring really all it is cracked up to be? Are companies really making more money because of it, or are they finding it a giant waste of time and money? We will shed light on this, no matter which group above you are in.

Let's first speak to those who don't use scoring or have tried and failed. Are you in this group?

Your client mandates you have to contact every account no matter what. So you do, mostly.

Your corporate culture is that you believe contacting everyone no matter what, squeezing every drop from any and every account, is the best business practice.

You got burned, because your experience changed and now you don't trust those misguided scores. You called on accounts that had a high likelihood of "collectability" scores, but they performed poorly. Conversely, you found that debtors who had low scores actually yielded some decent collections. You lost faith in the scoring model.

You used to use scoring but the results were scattered and you have no way to calibrate a scoring algorithm to the complexion of your collection portfolio. So you reverted to calling everyone simply by the way it's queued up in your dialer.

Your operation is too small to even need analytics.

The balances you collect are too small, say for example, on video rentals or library books.

You have been in this business a long, long time and you believe you can make your own decisions using MS Excel and intuitive or internal intellectual capital.


NEWSFLASH!

Scoring is still a strong choice. Why? Because done correctly, it can be inexpensive effective and a good score will translate to increased profitability which, in turn, means you have a terrific return on investment. If you are apprehensive about it, just learn more about it first. Or, if you have tried and didn't see results, perhaps you were not doing it correctly?

Knowledge is Power, especially for this industry.

To really truly gain the benefits of scoring, you need to do the necessary upfront homework. In doing so, you ensure the most predictive attributes are captured by your scoring model. In addition to the predictive elements, you also have to factor in the variables around your operating costs because, at the end of the day, the key metric is how much, in total, you collected, and not how many people from whom you collected. This is a typical example and it might be something you experienced in your own operation: A collection company scores a portfolio of accounts using a recovery score from a credit bureau. In looking at the results, the scores show the highest scores are on accounts that have the lowest collection balances. However, the "seat-of-the-pants" (i.e., heuristic) approach of the seasoned collection manager told him that he would collect more from the higher-balance accounts, irrespective of the poor scores they received. The result was the manager was proved right and his cash flow velocity improved dramatically over doing what the scoring told him to do. This is an example of how generic scores don't account for the operational constraints of the particular individual collection business.

The moral of the story: generic, black-box scores are usually not taking in to consideration the best interest of your business. As a corollary, there is a tremendous benefit to investing in your own analytics and it is a consequence of doing your upfront work.

If it is not personal to your company, it is not as profitable to your company.

Even if you are a small operation and think you cannot afford a custom collections model, or if you think your own data set or database is too small, you actually have some viable models. There are, for example, already collection models out there for most asset classes. One can take a model and use it as a template to tune the model for your own collection portfolio. Once you have the model and deploy it within your operation, you will have gained the sort of analytics capabilities that have typically only been within the grasp of larger organizations, and by using this "semi-custom" technique, will achieve this level of analytics at a far lesser cost.

Who would not want to gain tremendous insight in to their portfolio if you could do it quickly, inexpensively and accurately, and while we are at it, let's throw in easily, since the results can be interfaced with your contact management system?

To a person who is not an auto mechanic, rebuilding an engine is daunting task, even if your life depended on it. Similarly, if you are not an electrical engineer", you probably wouldn't want to deal with a high-voltage wiring problem. What you do is go get an expert to handle the job. Smart collection companies don't say no to opportunity, they investigate it, and find an expert they are confident in using. Adequately spending time, with whatever company, and really discussing scoring for your types of debt portfolio and your business model, is time well spent.

So you are already scoring? How is that working out for you?

Many companies are using one-size-fits-all, black-box scores. Obviously, your portfolio is unique and you can only expect these black-box scores to perform to a certain level. If you have not lost faith in it and are still using generic scores, you may not know what you don't know, so to speak. But most studies and tests will tell you that you are likely leaving significant money on the table. Even if you think you are using most of your resources on those most likely to pay, environmental changes are constant and unless your analytics was adapting to these changes, the performance of your scoring will only deteriorate. Many external factors such as new regulations or laws, mortgage rates, unemployment rates, a new factory coming to town, or closing, all impact your true optimal group to focus on. Scores from credit reporting agencies are not local and they are certainly not personal. So, your scoring analysis and results will be skewed.

Perhaps your score is included in a package and it's good enough. You don't want to pay more for true analytics and you don't have any quantitative analysts on staff anyway.

Let's do the math.

A custom scoring solution for your company might cost $40,000 to $100,000 or more. If you absolutely knew it would help you lower what you pay for labor, collect more from your portfolio with even small incremental lift and possibly allow you to leverage your prowess in to getting more customers, you would, at the very least, talk to some company that was an expert at helping collection operations with scoring.

If you absolutely, unequivocally knew you would see a 200% return on your investment within the first 6 months, you would be reaching for your pen.

The trick in scoring for your company is to get to a point with a provider where you can either see a qualified return on investment and/or not be tied in to any long term contracts.

For example, if the solution costs $100,000 and on your $5,000,000 portfolio, you see an increase of $250,000 and you saved $40,000 on salaries, and you didn't have to hire the $80,000 "quant" analyst, suddenly scoring looks like a wise investment. It is. If you pay $40,000 for your custom solution and you saved $100,000, it is still very beneficial to the bottom line of a small company and exponentially critical in a larger organization.

In another example, many generic scores are based on variables that may not be what you specifically want. For example, your generic results might state to spend time on Account 1, with a balance of $500 because it shows you can collect 50% or $250. Meanwhile, Account 2 with a balance of $3000 only shows you will collect 10%, or $300. Because the collection expectation is lower, some scores will incorrectly suggest that you take action on the account with the higher score, even though from a financial perspective, it is the wrong action to take. While you focus spending resources to collect $250, you could have (should have) also spent time collecting on Account 2. That's where individual scoring helps a company gain incremental "lift".

Scoring is an investment. Like any investment, you want to do it right, smart, and profitably.

Scoring is even more critical if it helps you to transform collection accounts into recurring payment opportunities. Because by doing so you will have successfully helped a debtor move into a settlement with recurring revenue (for you or your client), which carries with it a much higher ROI component. When you deal with these debtors over time, you enhance your data repository with new data that you can now model against your historical data. A software system that allows you to harness that experiential data is priceless. Your agents don't have to pretend to be analysts. The results, as run through your scoring model, would be right in front of them, based on algorithms, not educated guesses.

Accurate real time data allows for accurate real time decisions.

Erik Cofield is a Vice President and Business Strategist with Cambio Technologies, a software and consultancy company providing business data optimization, business intelligence, analytics and modeling solutions based in Phoenix with offices around the United States. He speaks to associations, groups and companies on analytics software and business strategy. He can be reached at erik.cofield@cambiotechnologies.com.