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A System and Method of Data Access for Credit Scoring

IP.com Disclosure Number: IPCOM000241357D
Publication Date: 2015-Apr-21
Document File: 5 page(s) / 95K

Publishing Venue

The IP.com Prior Art Database

Abstract

In this system, we claimed two layers of protection and one reference score – confidence score for users to decide what data could or should be shared for credit rating and what should be protected. Two layers of protection 1) Authorization 2) Grain degree selection and One reference score 1) Confidence Score Based on the user authorized and selected data in local mobile, our method can calculate the confidence score to predict whether using these data can generate a reliable credit score.

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A System and Method of Data Access for Credit Scoring

Commercial and retail banks play a important role in traditional financial services but incur large operational costs and inefficiencies , for example, it is very usual that inside a bank's branch office one will find a long queue where clients are waiting for face-to-face services, such kind of inefficiency leads to low productivity and serious customer dissatisfaction. With technologies' great advancement and INTERNET's booming, a new way to conduct financial services is emerging, which is so called 'INTERNET finance'. Nowadays, INTERNET companies are aggressively threating banks' marketing share by leveraging their massive amount of online users and their behavior data to establish a new cash channel to absorb huge amount of cash into their financial pool.

One of the key dilemma in big data based credit evaluation is how to get relevant data to compute the credit score. Traditionally, Bank, e-commerce, facility and internet companies own their data. Each party in the ecosystem would like to get/acquire the external data but would not like to share their own data. To build a credit system, we need to convince and integrate the data in each party.

the problem is for credit assessment, the traditional methods to access the relevant data
1) Pull the credit relevant data or score from the credit bureau or the third-part agency
2) Collaborate with the big data provider

3) Use the in-house data generated in their own platform

Benefit of mobile data access for big data enabled credit assessment

1)Less effort for the cooperation between the different data providers
2)User have more decision-making authority - share data for credit

3)The diversity (hub capacity) and reliability (personal data) of mobile data

For mobile data collection, two important problems need to be considered

Privacy preserving problem

1) User shou...