The signature solutions, as IBM calls these offerings, go beyond generic analysis software to address three different specific tasks: detecting financial fraud, predicting consumer behavior and estimating financial risk.

"Having software is important but having industry expertise and domain knowledge is also pretty essential," said Deepak Advani, IBM vice president of predictive analytics. IBM's intent behind these packages is to combine its analytic software with the lessons it has learned installing such software for clients, Advani said.

In its work of deploying systems, the IBM services arm sees a lot of the same challenges, or patterns, across different clients, Advani explained. These packages will utilize what IBM has learned deploying such systems. It also draws from the company's considerable research expertise and IBM software, such as SPSS, Cognos, Clarity and WebSphere.

Potential customers will start with a workshop to help identify which datasets they have that can be better utilized. IBM will then work with each customer to develop an analysis system, using as much of the customer's existing systems as possible. The cost for each customer will vary depending on implementation.

IBM developed the fraud detection package to help insurance agencies, health care companies and government agencies detect phony claims before they are paid out. Typically such organizations have practices in place to identify cases of fraud, but they identify the misbehavior only after the claims are paid. An IBM system could be built that recognize the subtle hints of fraud, based on analysis of historical data, Advani said.