Opendata, web and dolomites

BigDataScore

Improving loan quality and acceptance rates by predicting credit behavior through social mediadata.

Total Cost €

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EC-Contrib. €

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Partnership

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Project "BigDataScore" data sheet

The following table provides information about the project.

Coordinator
BIG DATA SCORING 

Organization address
address: VAHTRAMAE TEE 12-1
city: TALLINN
postcode: 11912
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Estonia [EE]
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-1-2014
 Funding Scheme SME-1
 Starting year 2015
 Duration (year-month-day) from 2015-03-01   to  2015-06-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BIG DATA SCORING EE (TALLINN) coordinator 50˙000.00
2    AASA GLOBAL AS EE (TALLINN) participant 0.00

Map

 Project objective

The problem: Credit Losses on Banks’ Loan Portfolios - Youngsters and 2nd generation immigrants still have difficulty in obtaining credit.

The solution: Our credit scoring model called Big Data Score assesses the credit quality of people and accurately predicts their payment behaviour based on data from social media (Facebook) and internet browsing behaviour.

Objectives of the overall innovation project: 1) Bring the present Technology Readiness from level 7 to 9. 2) Provide the system with complete access to real life data and Open Data made available from governments. 3) Development of a marketing and sales strategy based on two key principle: vertical approach and distribution approach.

Value Proposition: To help lenders to save money on credit losses and to make more money on increased acceptance rate.

Business Model: Business follows a simple and easily scalable model where lender pays for each score: 0.99 EUR per Facebook score and 0.20 EUR per browser score.

Users/Clients: Our target client is anyone who is taking a short to medium term (1-36 months) credit risk.

Competition: Traditional credit bureaus and innovative credit score (Kreditech, Leendo, ZestFinance).

Revenue Streams: 36M€ revenues at the 3rd year after commercialization.

Team: Big Data Scoring AS, Aasa Global AS.

Required funding: 1,5M€

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "BIGDATASCORE" project.

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Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "BIGDATASCORE" are provided by the European Opendata Portal: CORDIS opendata.

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