Generating optimal strategy for providing offers

Abstract

Generating optimal strategies for providing offers to a plurality of customers is described. A plurality of categorical attributes (for example, gender and residential status) and ordinal attributes (for example, risk score and credit line utilization) can be determined. Values of one of more categorical attributes can be changed as per a transition probability table. Some probabilities can be varied to determine a first tradeoff, based on which a first updated strategy can be generated. Further, noise can be added to one or more ordinal attributes. Standard deviation of a noise distribution associated with the noise can be varied so as to determine a second tradeoff, based on which a second updated strategy can be generated. The second updated strategy can be an update of the first updated strategy. Offers can be provided to the plurality of customers in accordance with the second updated strategy.

1 - 23 . (canceled) 
     
     
         24 . A computing system connected to a communications network for exchanging data, the computing system having at least one processor, a non-transitory data storage medium, and a plurality of data structures and executable code stored in the non-transitory storage medium, the data structures including a first decision tree and a second decision tree, the execution of the executable code by the at least one processor causing the computing system to:
 obtain data stored in at least one data storage medium, the data corresponding to a plurality of entities associated with a plurality of attributes;   determine a first offer for a first attribute from among the plurality of attributes based on the obtain data;   form the first decision tree and the second decision tree for characterizing one or more offers corresponding to the first attribute;   compare performance of the first decision tree with performance of a second decision tree in relation to the first attribute;   provide a first offer to a first entity in accordance with the first decision tree, in response to determining that the first decision tree is superior to the second decision tree in view of a performance threshold; and   provide a second offer to the first entity in accordance with the second decision tree, in response to determining that the second decision tree is superior to the first decision tree in view of the performance threshold.   
     
     
         25 . The system of  claim 24 , wherein a plurality of causal models are utilized to form at least one of the first decision model and the second decision model to evaluate one or more objectives of an entity, the causal model being used to determine a best offer for the first attribute. 
     
     
         26 . The system of  claim 25 , wherein the causal models characterize a response of an entity to a historical offer. 
     
     
         27 . The system of  claim 25 , wherein the determining of the best offer is based on evaluation of at least one of a global maximum value and a local maximum value by the first decision model and the second decision model. 
     
     
         28 . The system of  claim 24 , wherein the second decision tree is obtained by changing a value of one or more attributes associated with the first decision tree. 
     
     
         29 . The system of  claim 24 , wherein the performance of the first decision tree is characterized by business efficacy provided by implementing a strategy associated with the first decision tree, the business efficacy associated with the first decision tree being based on a plurality of iterations of strategy evolution, the business efficacy characterizes a profit of an entity providing the offers to the plurality of entities. 
     
     
         30 . The system of  claim 24 , wherein the performance of the second decision tree is characterized by business efficacy provided by implementing a strategy associated with the second decision tree, the business efficacy associated with the second decision tree being based on a plurality of iterations of strategy evolution, the business efficacy characterizes a profit of an entity providing the offers to the plurality of entities. 
     
     
         31 . The system of  claim 24 , wherein the plurality of attributes are represented by a graph having a plurality of dots with at least one of a corresponding color and a corresponding intensity to characterize a value of at least a first attribute for a first entity. 
     
     
         32 . The system of  claim 33 , wherein the first attribute is modified by adding noise to the first attribute by varying a standard deviation of a noise distribution to determine the noise. 
     
     
         33 . The system of  claim 32 , wherein the adding of the noise to the first attribute provides a first profit to a first entity providing the first offer, wherein the first profit is more than a second profit obtained without the addition of the noise to the first attribute. 
     
     
         34 . The system of  claim 33 , wherein the adding of the noise to the first attribute comprises adding Gaussian noise to the first attribute, wherein a standard deviation of the Gaussian noise is varied to determine a tradeoff. 
     
     
         35 . The system of  claim 34 , wherein an updated strategy associated with the tradeoff is generated and a second offer is provided based on the updated strategy being determined based on a first tradeoff characterizing a balance between cost of a business entity and a rate of updating the strategy. 
     
     
         36 . A computing system connected to a communications network for exchanging data, the computing system having at least one processor, a non-transitory data storage medium, and a plurality of data structures and executable code stored in the non-transitory storage medium, the data structures including transition probability table, the execution of the executable code by the at least one processor causing the computing system to:
 determine a plurality of attributes associated with a strategy;   change values of a first set of one or more attributes in accordance with a transition probability table;   vary one or more probabilities to determine a first tradeoff; and   generate, based on the first tradeoff, a first updated strategy.   
     
     
         37 . The system of  claim 36 , wherein the execution of the executable code by the at least one processor causes the computing system to:
 add noise to a second set of one or more attributes;   vary standard deviation of a noise distribution associated with the noise to determine a second tradeoff; and   generate, based on the second tradeoff, a second updated strategy, the second updated strategy characterizing an update of the first updated strategy.   
     
     
         38 . The system of  claim 37 , wherein the execution of the executable code by the at least one processor causes the computing system to provide, based on the second updated strategy, one or more offers to a plurality of entities. 
     
     
         39 . The system of  claim 38 , wherein the first set of one or more attributes include gender and residential status. 
     
     
         40 . The system of  claim 37 , wherein the second set of one or more attributes include risk score and credit line utilization. 
     
     
         41 . The system of  claim 40 , wherein based on the transition probability table, eligibility constraints for providing the one or more offers to the plurality of entities are determined and at least one of the first updated strategy and the second updated strategy are based on the eligibility constraints to exclude some offers to corresponding ineligible entities. 
     
     
         42 . The system of  claim 41 , wherein at least one of the first tradeoff and the second tradeoff are determined using corresponding tradeoff curves, at least one of the first tradeoff and the second tradeoff being characterized by a sweet-spot on a corresponding tradeoff curve, the sweet-spot characterizing a position where generated strategy data is more than a first threshold while profit is more than a second threshold. 
     
     
         43 . The system of  claim 42 , wherein the plurality of attributes comprise observed variables known at time of providing the offers, derived variables, predictive variables, and a score. 
     
     
         44 . The system of  claim 43 , wherein the observed variables comprise data filled by entities in applications, data associated with financial-accounts, demographics data, transaction data, credit bureau data, credit card score, credit card usage data, risk score, revenue score, credit line utilization data, social network data, conversations of one or more entities with one of other entities and third parties, and third party data. 
     
     
         45 . The system of  claim 43 , wherein the derived variables comprise text keywords, n-grams, merger and acquisition transaction data, and parameters of social networks. 
     
     
         46 . The system of  claim 43 , wherein the predictive variables comprise likelihood to default over a predetermined period of time in future and expected entity lifetime value and the score is calculated based on the observed variables.