Fraud detection and prevention is important to Provident Personal Credit, a leading lender in the United Kingdom's home credit industry.
According to Paul Wilkinson-Smith, a fraud analyst in the Field Security Department within Provident Personal Credit (PPC), a subsidiary of Provident Financial, "We split our test data in half. We use half to train the Clementine neural network and the other half to test the network once we believe it is ready. We also test the network using raw data that has not been analyzed previously."
It takes in-depth business understanding to find effective solutions to business problems. SPSS Clementine's interactive data mining process helped PPC by incorporating valuable business expertise at every step to create powerful predictive models that addressed their specific business issues.
"We look at the neural network results and then manually evaluate that data to determine how well the network performed. We can tweak the neural network to some extent by adjusting thresholds, maximum performance levels and other factors. While the neural net is self-contained, it can be adjusted and tuned for optimal performance", said Paul.
PPC's Clementine model further enhances the company's fraud detection capability. "We can look at the rules that Clementine generates and test them against known data," Wilkinson-Smith said. "This combination of modeling tools provides a very powerful data mining system that allows us to target our investigations and save our field agents an unbelievable amount of time.
"Fraud profiles change very frequently," he noted. "Using Clementine, we can change our models as often as we need to. We can retrain the Clementine neural network and ruleinduction engine whenever we detect a shift in fraud patterns and profiles."
"Nearly 80 percent of the fraud discovered is identified using Clementine modeling, which provides a superb visual development environment that saves us time and money. It's brilliant!"
The complete list of global SPSS success stories can be found here
“Nearly 80 percent
of the fraud
discovered is
identified using
Clementine
modeling, which
provides a superb
visual development
environment that
saves us time and
money.”
- Paul Wilkinson-Smith, Fraud
Analyst, Provident Personal
Credit
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