Project detail - PT BINA ARTHA VENTURA

PT BINA ARTHA VENTURA

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Who is our client

PT. Bina Artha Ventura (BAV) is a Venture Capital Company actively engaged in the microfinance sector in Indonesia which started operations in December 2011. The company offers working capital through a flexible version of the Grameen methodology and focuses on women with limited access to the formal financial sector. The company also provides business loans to small enterprises.

Funding objective

The aim of this project is to develop a data warehouse and improved business intelligence in order to improve company performance, but also to improve BAV’s client service and product offerings. As part of its regular business process, CAA-Indonesia collects a wealth of information about clients as well as transaction-level details for each process. To obtain a deeper understanding of patterns and trends in business performance and relate them to client segments, geographical areas and other associated data points, BAV considers it key to create a unified data warehouse along with a reporting platform.

Why we fund this project

BAV is active in Indonesia, which has a high, unmet and latent demand for microfinance, and focuses on female entrepreneurs which means it is closely aligned with the MASSIF priorities. Furthermore, digitisation and fintech offer great opportunities for financial inclusion in terms of increasing FI efficiency, but most importantly in terms of offering new means of reaching and serving financially excluded people and businesses. Experience from the FinForward program and other client engagements shows us that one of the key constraints faced by FIs as they digitize, is a lack of adequate, accurate and structured data. This project addresses this prerequisite to digitisation of BAV.

More investments

Date Total FMO financing
3/1/2022 USD 10.00 MLN
11/18/2016 USD 5.00 MLN
Region
Asia
Country
Indonesia
Sector
Financial Institutions
Signing date
7/3/2019
Total FMO financing
EUR 0.02 MLN
Fund
MASSIF
Risk categorization on environmental and social impacts, A = high risk, B+ = medium high risk, B = medium risk, C = low risk Environmental & Social Category
(A, B+, B or C)
C