2022 | Finance/ Credit Companies | Nigeria | Promising | SDG3 | SDG9
Novel Machine Learning Approach for Credit Risk assessment using Non-Traditional Data Sets

Company or Institution

Vittas Inc

Industry

Finance / Credit Companies

Website

https://www.vittasinternational.com/

Country

Nigeria

Sustainable Development Goals (SDGs)

SDG 3: Good Health and Well-being

SDG 9: Industry, Innovation and Infrastructure

General description of the AI solution

Vittas was selected as a promising project for 20191 and asked to resubmit its proposal. Vittas intends to use Machine Learning to execute micro-segmentation based on customer behaviors rather than solely on credit history identifiers. Machine Learning will “train” models based on behavioral and traditional data sources to enhance the predictive power of the credit models and has shown consistent accuracy and capacity to capture non-linear relationships characteristic of credit risk. This research will allow Vittas to innovate and introduce new products and services within emerging markets (initially Nigeria)– where there is a lack of a centralized infrastructure that monitors consumer credit history, which has led to risk averse lending practices minimizing SMB’s access to affordable working capital. The credit to GDP ratio in Nigeria is 11% compared to 191% in USA. By providing access to affordable loans – SMB’s (the backbone of an economy) will be able to grow their businesses and hire more people from their local communities. This will increase quality of life from the ground up. Initially Vittas has focused on the healthcare market – ensuring hospitals/pharmacies have money to purchase medications to reduce inventory stockouts which occur 30-50% of the time in Nigeria. Vittas is the first stage of the development process.

Publications

https://www.vanguardngr.com/2022/09/vittas-intl-providing-tech-enabled-inventory-financing-solutions-for-healthcare-providers/

https://ircai.org/top100/entry/novel-machine-learning-approach-for-credit-risk-assessment-using-non-traditional-data-sets/

https://newsandviews.vilcap.com/press-releases/hyper-protect-accelerator-2020-cohorts-2-3

https://disrupt-africa.com/2021/06/21/15-startups-selected-for-6th-google-for-startups-accelerator-africa/

Needs

Funding

Personnel

Public Exposure

CONTACT

International Research Centre
on Artificial Intelligence (IRCAI)
under the auspices of UNESCO 

Jožef Stefan Institute
Jamova cesta 39
SI-1000 Ljubljana

info@ircai.org
ircai.org

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