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In the first part of the talk, we describe our in-house real-time analytics engine. Enova is an online business operating in six countries that offer multiple lending products. When the customer makes an online purchase decision, we run six to eight models in the background that include fraud checks, credit checks and profitability calculations. Providing fast customer experience requires a powerful, real-time analytics engine that can support the analytics behind-the-scenes. Our analytics engine is built entirely in Mathematica, and was developed in collaboration with Wolfram. It delivers sub-second responses for model computations. It also facilitates efficient model deployment that helps us adapt to the fast changing landscape of new products and regulations. In the second part of the talk, we go over an example application of how we used Mathematica to merge XML files. This was part of an effort to parse and store XML data into a relational database. In situations where the schema definition was not available, we needed to approximate the complete XML structure by merging sample XML files. We go over the algorithm we used and provide timing information on two different implementations. We also provide some insight into how careful use of pattern matching can speed up execution of the program.
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