The same business intelligence that helps companies large and small manage everything from supply chains to revenue may soon help lenders judge credit risk, too. Check out this latest MarketWatch post about a new tool for lenders accessing Canada's largest commercial risk database.
Some of the obvious benefits, the tool provider says, include:
allowing lenders access to a huge and trusted database with information on credit history and payment performance
providing an easy-to-use tool good for identifying profitable customers and managing risk with data from credit groups, collection agencies, and bankruptcy courts
conversely identifying potentially dangerous or risky accounts with comprehensive information from an estimated two million businesses
creating easy-to-understand data and reports highlighting potential credit problems including bankruptcy alerts, inquiry totals, and bank reports.
You can easily see how important this technology can be, and not just in flush economic times. After all, bad credit decisions presumably in part led to the credit crunch of 2007 and 2008. Thus, instability in the credit system in the US and worldwide helped directly contribute to global economic slowdown.
Leaving aside the impact of "subprime" and other exotic lending instruments, bad credit risks stood at the heart of this debacle. I think we can safely assume that business intelligence aimed at helping lenders make better decisions will be a major asset not only in the ongoing economic recovery but also in staving off future credit difficulties.
Of course, in recent years, business intelligence has seen even more remarkable growth than the tech sector in general, according to data collected in financial circles. This, no doubt, is because of this technology's value in reducing costs and improving return on investment, especially in hard economic times.
But just think for a moment how valuable tools applying intelligent analysis to relevant credit records could be to the mainstream business community as well. Using this technology to access and compile data on financial histories would allow companies to:
evaluate the payment history of potential clients and customers
project the financial stability of future or existing suppliers and partners
probe beneath simple credit information to observe patterns that might indicate future difficulties
anticipate development difficulties with an existing customer or supplier that may indicate trouble ahead in terms of meeting future obligations.
Now, I already hear one question coming. "Hey, what is business intelligence going to really tell us that a simple credit check can't?"
The fact is that credit checks are only a snapshot in time reflecting a company's current financial situation. As anyone who has ever experienced those gradually later and later payments knows, a credit check isn't always the measure of overall financial competence.
So what do you think? Could your company or clients use the kind of business intelligence and analytics technologies now being introduced into the lending industry? Could you benefit from the kind of detailed financial history they can provide? Would it help you make more informed decisions about future or existing customers, clients, and suppliers? Let us know by commenting on the message board below.
While I agree that entrepreneurs have great instincts anyone can be burned by the unscrupulous. I have numerous associates that are dealing AR issues because even good clients went bad. Some type of proactive credit monitoring service would be awesome to prevent these issues at the small biz level.
I agree that more, if it's good info is always better, but there can also be too much. To the small business owner instinct is a factor in credit decisions and credit checks only validate. Predictive numbers although useful, may be preceived as unnecessary intrusion in decision making.
One of the places I really see this revolutionizing things is in small business. It's true that large companies have had access to such tools and numbers for years, but as BI and analytics filter into the hands of smaller and smaller firms and entrepreneurs, I wonder if we may see a day when predictive numbers may be available on potential customers, clients, partners, vendors, suppliers etc. My experience with entrepreneurs is that many already have or have developed excellent instincts about these issues, but more information could certainly help avert some of those horror stories we've all either experienced or heard of.
This is awesome I would use it in my business and many of peers would as well. We all use our best judgement with clients but am sure everyone has had their story to tell. This would be D&B score option for small biz with limited budgets
If the information helps make better decisions, it is better. But as Kahneman and Tversky explained in their Noble [memorial] Prize winning research in economics, more data makes people worse at estimating the level of uncertainty they have around a conclusion - exactly the opposite of what is needed in this case.
Agreed in the case of lenders, at least. I suspect the tool is in part to inspire confidence in the lending institutions and in part to either identify those accounts that represent risks outside acceptable overall parameters or to set those overall risk parameters in the first place.
All good points, David, and definitely food for thought. Thanks for the detailed comments. I'm certain that no system will ever effectively eliminate risk and to be honest am not certain to what degree levels of uncertainly can even be whittled down. Then again, as in everything, it would seem more information is always better.
Until and unless uncertainty is factored into the models, there is no way it can lead to better judgement.
What is the confidence in each input? How likely is it that the metric is wrong? What macro-economic factor can cause the analysis to fail? What is the actual risk?
With credit checks, I would say that the first question is how predictive they actually are. If 90% of people who defaulted in the last year default again this year, that is short term-predictive. If 10% of people who defaulted last year default his year, and 9% of people who did not default last year default this year, it's almost useless. Is the credit score useful for predicting short term or long term default rates? Are there other items that work better? Is the stated income compared to the average for the profession a more useful metric than industry type? Is industry type (cyclical versus growing) predictive? Maybe it is more predictive if the person is making less than average for the profession, adjusted for age - and then credit score is useless.
Then, is the score more predictive in times when the economy is bad, or good? By how much? Are we really just fiddling around the margins, becuase the real risk is economic? At this point, we need to look at our overall risk metrics - if the underlying risk is economic, should we hedge it elsewhere? Or do we not make loans that are sensitive to that risk?
These are the types of questions needed - not simply finding the most predictive single model for "lending" generally.
@ Shawn I agree with SaneIT and Terry on this topic, the risk associated with a potential customer(s) is of little importance - if a company's internal models support the conclusion money can be made, and it has been shown that lenders are willing to accept their models more than the reality of risk.
These models as I understand them allow for a certain degree of "potential loss" and then it is just is a question of how much profit the lender ( in this case ) is willing to accept.
In most cases, the model is based on 100% markup and unless the market collapses as it did two years ago, a realized gain (profit) from these seemingly risky transactions is almost certain.
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