Statistically, a “hot hand” in basketball doesn’t exist. In a detailed analysis of the 76ers and Celtics plus controlled experiments with Cornell’s varsity teams, researchers found that streaks were just positive random sequences with little evidence of correlation between outcomes and successive shots.
Tag: Predictive Data
This week’s SBA announcement that the Agency will make available borrower’s credit score that takes into account both personal and business attributes has sent shock waves through the industry. The funny part is that these shock waves were not the ones intended. The intention was to let the Nation know that Maria Contreras-Sweet, the new head of the SBA, is ready to help minority lending and that will further stimulate the economy.
What if there were a set of three easy to distinguish factors that, if all present, could predict the future performance of your customer and reduce the probability of default to half that of their respective industry? Would you do anything differently? Would you price lower? Would you extend more credit? Would you change your sales or marketing process at all to go after those accounts?
A couple weeks ago we discussed Part I of the best tactics we learned for building a bank customer base over the holiday season. Traditionally, while the holiday season is one of the worst times to market, this campaign is designed to take advantage of bank customer behavior and put the odds back in your favor. Since growth is so difficult to come by these days, we are looking for every advantage we can get and this campaign starts the year off with forward momentum.
Yesterday, we covered a set of economic indicators that have proven to be unreliable at predicting the future of rates, credit, loan or deposit growth. The subject is topical as many banks are working through their budget forecasts and instead of just relying on history, many banks seek to increase the accuracy of their predictions by utilizing these indicators. One way to do this is to incorporate forecasts of these economic indicators and then use that as the basis for fine tuning bank budget variables.
While most banks understand the important data points when it comes to loans or deposits, most banks still could use help on collecting some of the basic information about their customers. The age of utilizing customer data to get predictive about risk, customer profitability and marketing is just beginning at banks so this is a new field for many. For example, a change in number of employees at your borrower is correlated to both credit risk and profitability.