1. A system comprising: a network interface configured for communicating with a user device; a processing device; and a memory device in which instructions executable by the processing device are stored for causing the processing device to: configure a neural network to generate risk indicators and adverse action codes, the adverse action codes indicating impacts of respective predictor variables on the risk indicators, wherein the configuration of the neural network includes operations comprising: (a) retrieving, from a database in the system, a plurality of predictor variables, wherein each predictor variable corresponds to an entity, (b) determining a correlation between each predictor variable and an outcome, (c) generating the neural network, the neural network having a hidden layer for determining a relationship between each predictor variable and a risk indicator based on the correlation, wherein the risk indicator is a level of risk associated with the entity and wherein the neural network is operable for determining whether a monotonic relationship exists between each predictor variable and the risk indicator, and (d) iteratively adjusting the neural network so that the monotonic relationship exists between each predictor variable and the risk indicator as determined by the neural network, wherein each adjustment comprises adjusting at least one of a number of nodes in the hidden layer of the neural network, a predictor variable in the plurality of predictor variables, or a number of layers in the neural network, wherein the processing device is configured to determine, based on a rate of change of the risk indicator with respect to each predictor variable, that the monotonic relationship exists between the predictor variable and the risk indicator, and generate and provide, after the monotonic relationship exists between each predictor variable and the risk indicator, an output risk indicator and output set of adverse action codes by performing additional operations comprising: (a) retrieving, from the database, an input set of predictor values for the predictor variables, wherein the input set of predictor values corresponds to a target entity, (b) determining the output risk indicator by applying the iteratively adjusted neural network to the input set of predictor values, (c) determining, using the neural network, impacts of the predictor variables, respectively, on the output risk indicator, (d) generating, using the neural network, the output set of adverse action codes that respectively indicate the impacts of the predictor variables on the output risk indicator, (e) generating an electronic communication that includes the output risk indicator and the output set of adverse action codes, and (f) configuring the network interface to transmit the electronic communication to the user device for display of the output risk indicator and the output set of adverse action codes at the user device.