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

Projektinformationen

BigDataScore

ID Finanzhilfevereinbarung: 662652

DOI 10.3030/662652

Abgeschlossenes Projekt

EK-Unterschriftsdatum 28 Februar 2015

Startdatum 1 März 2015

Enddatum 30 Juni 2015

Finanziert unter

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Gesamtkosten € 71 429,00

EU-Beitrag € 50 000,00

Koordiniert durch

BIG DATA SCORING
Estonia

Ziel

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€

Wissenschaftliches Gebiet

• natural sciences › computer and information sciences › data science › big data
• social sciences › political sciences › public administration › bureaucracy
• social sciences › economics and business › business and management › business models
• social sciences › sociology › social issues › unemployment
• social sciences › sociology › demography › human migrations

Programm/Programme

• H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT) Main Programme
• H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument

Thema/Themen

• ICT-37-2014-1 - Open Disruptive Innovation Scheme (implemented through the SME instrument)

Aufforderung zur Vorschlagseinreichung

H2020-SMEInst-2014-2015

Andere Projekte für diesen Aufruf anzeigen

Unterauftrag

H2020-SMEINST-1-2014

Finanzierungsplan

SME-1 - SME instrument phase 1

Koordinator

BIG DATA SCORING

• Netto-EU-Beitrag: € 50 000,00
• Adresse: VAHTRAMAE TEE 12-1 ; 11912 TALLINN ; Estland
• KMU Die Organisation definierte sich zum Zeitpunkt der Unterzeichnung der Finanzhilfevereinbarung selbst als KMU (Kleine und mittlere Unternehmen). Ja:
  Region
  Eesti › Eesti › Põhja-Eesti
• Region: Eesti › Eesti › Põhja-Eesti
• Aktivitätstyp: Private for-profit entities (excluding Higher or Secondary Education Establishments)
• Gesamtkosten: € 71 429,00

Beteiligte (1)

AASA GLOBAL AS

Estland

• Netto-EU-Beitrag: € 0,00
• Adresse: LAEVA TN 2 ; 10111 TALLINN
• KMU Die Organisation definierte sich zum Zeitpunkt der Unterzeichnung der Finanzhilfevereinbarung selbst als KMU (Kleine und mittlere Unternehmen). Ja:
  Region
  Eesti › Eesti › Põhja-Eesti
• Region: Eesti › Eesti › Põhja-Eesti
• Aktivitätstyp: Private for-profit entities (excluding Higher or Secondary Education Establishments)
• Gesamtkosten: Keine Daten