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

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€

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

SME-1 - SME instrument phase 1

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-SMEInst-2014-2015

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Coordinator

BIG DATA SCORING
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 50 000,00
Address
VAHTRAMAE TEE 12-1
11912 TALLINN
Estonia

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Eesti Eesti Põhja-Eesti
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 71 429,00

Participants (1)

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