Abstract: Artificial neural network models trained using historical lead data are used to identify leads that are likely to be fraudulent or inaccurate and to additionally identify lead sources that provide leads likely to be fraudulent or inaccurate. Related apparatus, systems, techniques and articles are also described.

Abstract: Data is received that characterizes one or more leads. Thereafter, it is determined, for each of the one or more leads, whether the lead is likely to be fraudulent and/or inaccurate using at least one predictive model. In some implementations, one or more of the utilized predictive models can be trained using a plurality of historical leads with known fraud or accuracy data. Data can be later provided that identifies and/or includes one or more of (i) those leads that are determined to be fraudulent and/or inaccurate and (ii) those leads that are determined not to be fraudulent and/or inaccurate. Related apparatus, systems, techniques and articles are also described.