Finding smarter ways to manage large data sets

From its early roots in 1933, CBE Group has evolved into a national leader in accounts-receivable management. Today, the company is defining the future of debt collection by embracing a powerful combination: an innovative analytical infrastructure and an organizationwide commitment to ethical and professional interactions with consumers. The result: efficient operations and superior results from a data-rich environment and stronger brand reputations for its clients.

The Analytics Solutions Group (ASG) is the heart of the company's initiative to improve business insights using SAS^® technologies for a variety of tasks and projects, including data manipulation and statistical model building. Each day, CBE receives high-volume data updates to huge client databases that store client information about consumers and debt statuses. That data can be unorganized, unformatted, redundant and sporadic, requiring reformatting and transformation into structured data sets for analysis – a process that was previously cumbersome and time-consuming.

Seeing all areas of the business

To more efficiently manage those databases, ASG relies on SAS tools to pull together data from different data sets and aggregate various sources. The resulting time savings enable analysts to spend much more time exploring, mining and analyzing that unified data resource to uncover trends, patterns, and insights that improve business operations.

According to CBE analyst, Shane Roberts, the value from SAS is extensive. "SAS is becoming an invaluable tool for data manipulation and data mining," he said. "For the databases we're analyzing – which are quite large – SAS is essential for us to drill down on each client and measure performance and create granular reports. SAS provides reporting and dashboard capabilities that we've never had before – whether it's inventory management, payment statistics, or dialer performance. Now we can easily and quickly see what's happening in all corners of our business."

Optimizing profitability and efficiency

Specifically, SAS solutions are helping CBE improve debt-recovery efficiency and collection-agent performance. To maximize profitability and efficiency, CBE needs to focus its team of professionals on the accounts that present a projected optimal combination of recovery amount and ease of recovery. Determining the ranked priority of accounts to pursue is a key task for ASG.

The team has turned to SAS Analytics Pro and SAS^® Enterprise Miner™ to create the sophisticated predictive models for each client group that identify the best candidates for debt collection. These well-developed models help CBE understand how certain consumer characteristics and variables can influence their ability to make payments. Assumptions and distributions in many CBE models will change over time, making it necessary to constantly monitor and adjust models to maintain or improve their efficacy. Analysts in ASG use SAS to monitor the applicability and performance of their models by creating distribution charts for all variables to detect possible population changes with each new wave of inventory (accounts) received. This SAS routine, which CBE calls its Model Distribution Program, combines data manipulation and data analysis to transform raw new inventory data into the desired format, append it to the base data set, and then compare the variable distributions for different inventory periods through histograms and Pareto charts. Instantly, the ASG analysts can see if modifications are needed in their models.

Exploring the data

Using JMP® data visualization software from SAS, ASG analysts can ask the exploratory questions and find patterns, interactions and stories hidden within the massive data volumes. For example, James Zheng, an ASG analyst, built a collection-agent performance measurement system that enables CBE to fairly compare each agent's actual versus expected performance.

"SAS is helping CBE capitalize on and manage the wealth of real-time and historical data to create an information-driven business that sets the standard for debt collection," said Chad Benson, Chief Operating Officer for CBE. "SAS processes large amounts of data and offers flexible data manipulation – both of which help solve critical business and decision making needs across our company. As our analytics team has grown to more than 20 analysts strong, our ability to efficiently analyze data and perform more complex analyses makes SAS the perfect fit. SAS will further benefit our clients as we move into real-time decision making and begin using advanced predictive analytics capabilities, like neural networks, to drive our collection efforts into the future."