US 12,223,457 B2
Intelligent scoring systems and methods for scoring a level of performance of a business unit of a plurality of business units in an organization
Sarish Paul, Bangalore (IN); Anupam Adhikari, Bangalore (IN); Siddharth Gaur, Bangaluru (IN); Sheeba Bano, Hadapsar (IN); and Kamalnath KV, Bangalore (IN)
Assigned to ALLSTATE SOLUTIONS PRIVATE LIMITED, Bangalore (IN)
Filed by ALLSTATE SOLUTIONS PRIVATE LIMITED, Bangalore (IN)
Filed on Nov. 15, 2021, as Appl. No. 17/526,749.
Prior Publication US 2023/0153739 A1, May 18, 2023
Int. Cl. G06Q 10/0637 (2023.01); G06Q 10/0639 (2023.01)
CPC G06Q 10/06395 (2013.01) [G06Q 10/0637 (2013.01); G06Q 10/06393 (2013.01)] 16 Claims
OG exemplary drawing
 
1. An intelligent scoring system for scoring a level of performance of a business unit of a plurality of business units in an organization, comprising:
a scorecard tool comprising a scorecard and a neural network model;
one or more user input devices;
one or more memory components;
one or more processors communicatively coupled to the scorecard tool, the one or more user input devices, and the one or more memory components; and
machine-readable instructions stored in the one or more memory components that cause the intelligent scoring system to perform at least the following when executed by the one or more processors:
receive from the one or more user input devices a parameter rating for the scorecard of the business unit for each of a first portion of a plurality of business performance parameters;
automatically input the parameter rating for the scorecard of the business unit for each of a second portion of the plurality of business performance parameters;
automatically determine, via the neural network model, a weighting associated with each parameter rating;
automatically estimate, via the neural network model, a parameter outcome score for each of the first portion and the second portion of the plurality of business performance parameters based on each respective parameter rating and each associated weighting;
automatically estimate, via the neural network model, an overall outcome score indicating the level of performance of the business unit of the plurality of business units of the organization based on each parameter outcome score;
automatically generate one or more recommendations for improving the level of performance of the business unit based on the overall outcome score;
automatically display one or more portions of the scorecard including the weighting applied to each parameter rating as an indicator of an impact of each parameter to the overall outcome score;
store, to a training data server, at least one of the parameter rating, the weighting, the parameter outcome score, the overall outcome score, and/or the one or more recommendations as a historical parameter rating, a historical weighting, a historical parameter outcome score, a historical overall outcome score, and/or a historical recommendation;
update the neural network model, wherein the neural network model is retrained with the historical parameter rating, the historical weighting, the historical parameter outcome score, the historical overall outcome score, and/or the historical recommendation;
adjust the weighting, via the neural network model, of each parameter rating; and
generate one or more micro-organizational scores for one or more subgroups of the business unit, wherein the one or more recommendations for improving the level of performance of the business unit comprises a recommendation to at least one micro-organizational entity including a first sub group selected from the one or more subgroups and focused on a product or a geographic location.