US 2021/0012418 A1 · RESPONSIBILITY ANALYTICS

Abstract

A request to generate a responsibility score is received that characterizes a likelihood of a change in a level of creditworthiness of an individual in response to at least one unknown financial event. Such responsibility score can provide useful insight into a consumer that is complementary to a credit score. Thereafter, a responsibility score is generated based on historical creditworthiness data for the individual using at least one predictive model. The at least one predictive model was trained using historical creditworthiness data of a plurality of consumers subjected to a plurality of financial events. In addition, the at least one predictive model associates the historical creditworthiness data of the individual with matching states for each of a plurality of pre-defined performance behaviors—with each pre-defined performance behavior having at least two corresponding states. The responsibility score can be later provided to a user (e.g., persisted, transmitted, displayed, etc.). Related apparatus, systems, techniques, and articles are also described.

Claims27

Dependent claims

1-18. (canceled)

A computer implemented method, comprising:

querying a plurality of databases and retrieving, in response to the querying, a first data set corresponding to data changes from a first state to a second state associated with each first entity in a plurality of entities occurring over a first period of time and a second data set corresponding to data changes from the first state to the second state associated with each second entity in the plurality of entities occurring over a second period of time, wherein the data changes associated with each of the first and second entities are determined using a plurality of data attributes;
selecting one or more attributes in the plurality of attributes for matching of data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities, wherein the one or more first entities and the one or more second entities share at least one similarity with respect to the one or more selected attributes;
matching data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities using one or more selected attributes;
generating, using the matched data changes, at least one predictive model to model expected data changes over time with respect to the one or more selected attributes for each of the first and second entities;
predicting, for each entity in the plurality of entities, based on the modeled expected data changes, data changes during at least another period of time associated with the entity for each of the one or more selected attributes;
and
generating, for each entity in the plurality of entities, a score associated with the entity quantifying predicted data changes.

4 more elements

A computer program product comprising a non-transitory machine-readable medium upon which are stored instructions that, when executed by one or more programmable processors, result in implementation of a model for predicting data changes associated with an entity during a period of time, the model resulting from a process comprising operations of:

querying a plurality of databases and retrieving, in response to the querying, a first data set corresponding to data changes from a first state to a second state associated with each first entity in a plurality of entities occurring over a first period of time and a second data set corresponding to data changes from the first state to the second state associated with each second entity in the plurality of entities occurring over a second period of time, wherein the data changes associated with each of the first and second entities are determined using a plurality of data attributes;
selecting one or more attributes in the plurality of attributes for matching of data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities, wherein the one or more first entities and the one or more second entities share at least one similarity with respect to the one or more selected attributes;
matching data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities using one or more selected attributes;
generating, using the matched data changes, at least one predictive model to model expected data changes over time with respect to the one or more selected attributes for each of the first and second entities;
predicting, for each entity in the plurality of entities, based on the modeled expected data changes, data changes during at least another period of time associated with the entity for each of the one or more selected attributes;
and
generating, for each entity in the plurality of entities, a score associated with the entity quantifying predicted data changes.

4 more elements

A system comprising:

one or more programmable processors;
and
a non-transitory machine readable medium storing instructions that, when executed by the one or more programmable processors, result in the one or more programmable processors performing operations to result in generating a score quantifying predicted data changes associated with an entity, the operations comprising:
receiving one or more data changes associated with one or more entities in the plurality of entities from a plurality of databases;
using the received one or more data changes as model inputs to a model for predicting data changes associated with the entity during a period of time, the model resulting from a process comprising operations of:
querying the plurality of databases and retrieving, in response to the querying, a first data set corresponding to data changes from a first state to a second state associated with each first entity in the plurality of entities occurring over a first period of time and a second data set corresponding to data changes from the first state to the second state associated with each second entity in the plurality of entities occurring over a second period of time, wherein the data changes associated with each of the first and second entities are determined using a plurality of data attributes;
selecting one or more attributes in the plurality of attributes for matching of data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities, wherein the one or more first entities and the one or more second entities share at least one similarity with respect to the one or more selected attributes;
matching data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities using one or more selected attributes;
generating, using the matched data changes, at least one predictive model to model expected data changes over time with respect to the one or more selected attributes for each of the first and second entities;
predicting, for each entity in the plurality of entities, based on the modeled expected data changes, data changes during at least another period of time associated with the entity for each of the one or more selected attributes;
and
generating, for each entity in the plurality of entities, a score associated with the entity quantifying predicted data changes.

9 more elements

A method for generating a score quantifying predicted data changes associated with an entity, the method comprising:

receiving one or more data changes associated with one or more entities in the plurality of entities from a plurality of databases;
using the received one or more data changes as model inputs to a model for predicting data changes associated with the entity during a period of time, the model resulting from a process comprising operations of:
querying the plurality of databases and retrieving, in response to the querying, a first data set corresponding to data changes from a first state to a second state associated with each first entity in the plurality of entities occurring over a first period of time and a second data set corresponding to data changes from the first state to the second state associated with each second entity in the plurality of entities occurring over a second period of time, wherein the data changes associated with each of the first and second entities are determined using a plurality of data attributes;
selecting one or more attributes in the plurality of attributes for matching of data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities, wherein the one or more first entities and the one or more second entities share at least one similarity with respect to the one or more selected attributes;
matching data changes in the first data set associated with one or more first entities to data changes in the second data set associated with one or more second entities using one or more selected attributes;
generating, using the matched data changes, at least one predictive model to model expected data changes over time with respect to the one or more selected attributes for each of the first and second entities;
predicting, for each entity in the plurality of entities, based on the modeled expected data changes, data changes during at least another period of time associated with the entity for each of the one or more selected attributes;
and
generating, for each entity in the plurality of entities, a score associated with the entity quantifying predicted data changes.

6 more elements

Dependencies are inferred from the claim text.

Facts

Application

16/908,169Filed 22 Jun 2020

Priority

4 Nov 2009

Published

14 Jan 2021

Term ends

Not estimatedThe source records don’t support an estimate.

Classification3 codes

G06Q 40/03
Finance; Insurance; Tax strategies; Processing of corporate or income taxes: credit; Loans; Processing thereof
G06Q 40/02
Finance; Insurance; Tax strategies; Processing of corporate or income taxes: banking, e.g. interest calculation or account maintenance
G06Q
Information and communication technology [ict] specially adapted for administrative, commercial, financial, managerial

Responsibility analytics

Life of this patent

Responsibility analytics

Life of this patent

Abstract

Claims27