Finance
Insights Gained from Data Mining and Predictive Modeling
With the downturn in the economy, managing an organization’s liquidity needs has become a higher priority. In other words, increasing cash flows and freeing-up working capital have become critical for many organizations’ viability.
With a decline in revenue and the financial weakness of many of your customers, your company’s inventories and accounts receivable have been increasing rapidly causing cash shortages. To add to the misery, tighter or non-existing bank credit has limited even further the capacity to make ends meet.
The use of data mining and predictive modeling can help you to predict pending liquidity issues, spot credit problems before they become serious, and decrease working capital freeing-up needed cash flow.
Using data mining and predictive modeling tools in marketing and sales, finance can also gain a better understanding of the customer activity, segmentation strategies and customer profitability resulting in better planning, budgeting and forecasting.
With this understanding, finance can better support sales and marketing in their customer initiatives (cross and up-selling programs), reduce customer churn (loyalty and targeted retention programs), etc.
Models Highlighted in this Section
The following pages provide details on three commonly used applications of the data mining and predictive technologies in the areas of liquidity, sales demand/inventory control, extending customer credit, and managing collections risk.
These pre-built models are shown for illustrative purposes and are not, by any means, the only models we have built in the financial or related areas. Models detailed are: