Millions of African households are still living off-grid. Living without
access to electricity usually means families have to spend income on
candles, dirty and expensive kerosene lighting and expensive batteries for
flashlights. To make electricity more accessible to individuals, off-grid
solar companies offer solar home system (SHS) to off-grid households on a
pay as you go basis (PAYG). PAYG SHS’s allow customers to pay in affordable
instalments (~30–50 cents a day they would spend on poor kerosene
alternative). SHS includes: solar panel, battery, 2-5 modern LED lights,
radio, an optional TV and allows users to pay with mobile money. SHS can be
turned off automatically if payments are overdue. When a payment plan is
complete and no further payments are due the customer owns the equipment and can
benefit from free electricity. PAYG SHS’s providers currently require
hundreds of millions of dollars in working capital financing. Solar Frontier
Capital (SFC) is a dedicated impact investment company, looking to change
lives by providing working capital to SHS’s providers acquiring existing and
future SHS receivables.
Overview and Challenge
African Frontier Capital (AFC) sponsors the installation of SHS. These SHS
are signed up on a contract by vendors that are on the ground installing the
SHS. These vendors send through contract files for AFC to evaluate and
select contracts that will be sponsored.
The project objectives were to automate the process of ingesting the vendors
files, provision is made for contract, payment, mobile and adjustment files.
Then using this data to create calculations on the contracts, their value,
and payment history.
These files are uploaded into Google Cloud Storage by the vendor. The files
are processed using a Google Cloud Functions and inserted into Big Query. The
data is then analysed using Big Query.
Using this solution AFC is able to easily select files that will be sponsored
as well as track the contracts they are already sponsoring. Doing such a
process in Excel is time consuming and prone to errors. Automating this
process into scheduled queries and views ensures that the data is readily
available in various pivot tables, either on Google sheets or Microsoft
Excel, and that the formulae are uniformly applied, thereby achieving the
objectives of automation, speed and accuracy.