Personalised Rural Credit classification: the link between FinTech and the rural use of energy.

Nataliey Bitature and Riccardo Ridolfi


Nataliey Bitature


Nataliey Bitature is a Ugandan entrepreneur: co-founder and Director at Musana Carts, the Chief of Staff at Simba Group and the Chief Executive Officer at Energrow. Born October 28, 1989 to Patrick Bitature and Carol Bitature, Nataliey Bitature is both a British and Ugandan citizen born at Paddington Hospital, London.


Nataliey Bitature has a Masters of Social Entrepreneurship (MSC) obtained from Hult International Business School, San Francisco, 2015 -2016. In 2014, she joined the London School of Business and Finance (LSBF) for Emerging Leaders Program which lasted for four months. Nataliey also has a Dual Honors Bachelor of Business Management and Education Studies (BA) from Keele University, Staffordshire, UK, 2010- 2013.


Currently, Nataliey is launching Energrow. Energrow is focusing on supporting disadvantaged rural customers in Uganda and increasing energy access through sustainable demand growth with a data and financial inclusion backbone. Energrow is a technology company using training results and big data analysis to offer bespoke business financing services to rural customers as well as the necessary business and financial training programs. They are building their model to work hand in hand with, and benefit from, the expansion of the electricity grid to rural areas. Through partnerships with banks, their customers will gain access to the capital markets and as such cheaper loans, whilst banks gain hard-to-reach rural customers whilst assuming minimal risk.


In 2016, The World Economic Forum named Nataliey Bitature as one of the Top 5 African innovators and in 2017, she presented Musana Carts at the World Bank Spring Meetings. Nataliey Bitature won a 2018 Young Achievers award in the business category and named on the 2018 Forbes 30 under 30 list.


Riccardo Ridolfi


Riccardo is a co-founder of EnerGrow, a data-driven asset financing company with the mission of delivering productive assets and training to enable rural Africans to fully benefit from access to energy.


Riccardo is also a co-founder and the CEO of Equatorial Power, a renewable energy developer focused on accelerating access to productive power with mini grids and a holistic business model.


Riccardo is a qualified lawyer in three jurisdictions and has advised private and sovereign entities on infrastructure, cross-border investment and project finance. He is also a pro-bono Investment Advisor to the Ugandan Embassy to Italy, assisting with matters on FDI to Uganda.


Riccardo currently sits on the Board of Directors of Umeme Ltd, Uganda’s national electricity distribution company.


Approximately 75% of the inhabitants of sub-Saharan Africa does not have access to electricity. National and international public funds are insufficient to close this gap quickly enough and one of the main problems with private investments is that rural customers consume very little power not allowing the utility to recoup on its investment.


Poor people in rural Africa can afford electricity, even where more expensive than the national tariff. What they cannot afford are the assets to fully benefit from that electricity, e.g. milling machines, welding machines, fridges, etc. These people generally also lack access to financing and, therefore, nothing changes.


The lack of a bank account and other similar means for many persons and the consequent impossibility to demonstrate their own credit worthiness create a “catch 22” scenario from which it is difficult to escape: no credit worthiness, no credit and so on.


Absence of a credit score denies access to financing and the possibility to commence or support a business, even when – in reality – the relevant subject could have otherwise done perfectly well with the opportunities available to them.


From the observation of the above-mentioned “macro trend”, multiple start-ups are looking to leverage technology and, particularly fintech, to devise new solutions with which to solve the huge bankability problem.


One of these is EnerGrow, which is a Ugandan start-up attempting to change the status quo, by making these customers bankable in the eyes of utilities and beyond. EnerGrow has partnered with leading organisations and has recently received recognition and support from the Government of Uganda.



EnerGrow is a platform that does 3 things:


  1. Credit scoring – by leveraging data from mobile phones, energy smart meters, the national ID database and EnerGrow’s physical surveys, to create the most qualitative credit scoring data set to date in rural Uganda.
  2. Training – lack of training constitutes the primary cause of failure of local rural businesses. EnerGrow provides basic business skills, financial literacy and energy literacy to its customers to fertilise their businesses and improve their credit rating.
  3. Financing – EnerGrow provides mobile phone based asset financing with a “business-in-a-box” approach, acting as guarantor for local financial institutions to lend money to rural customers in 3 components: (i) energy-utilising productive assets; (ii) working capital; and (iii) prepayment of the training course. EnerGrow is the first company in its niche, aligning the interests of all its stakeholders, including national Government, energy utilities, mobile network operators and commercial banks, while delivering deep-rooted socioeconomic impact for durable rural growth and job creation.


A little bit more about building a rural credit scoring model…


Rural credit scoring methodology


  • Existing Data: It is important to not reinvent the wheel and leverage all existing data sets, starting from mobile phone data and, in this case, energy consumption data, as proxies for spending capacity, payment habits and willingness to pay of the proposed customers.
  • Outcome: Define outcomes of research before starting. If you ask customers 50 questions, all questions should help you reach a series of conclusions. Concise results’ summaries are a key for data interpretation.
  • Overview: Data collection questions to be crafted so as to indicate how things currently are and why.
  • Gender: It is renowned that women in poor rural settings score better in terms of repayment characteristics and it would be a mistake to ignore this.
  • Productivity: Focus on financing assets that generate income for customers. For example, financing productive assets such as grain mills will increase customer revenue and help their ability to pay back, reducing the lender risk. Financing televisions on the other hand, might not.
  • Record: Has the customer been approved by any organisation previously? Obvious risk reducing factors would be prior bank / microfinance loan approval etc., but anything that ties the customer to somewhere or something is good. Does (s)he have a work contract or a job reference for instance?
  • Purpose: Understand the motivation behind the demand for financing. Ask customers not only whether they want to increase their earnings, but why.
  • Behaviour: How consistent is the customer’s payment behaviour? Also in terms of earnings / salary, expenses, investments, etc.
  • Saving: Does the customer save voluntarily? Has (s)he made conscious decisions to improve financial behaviour such as joining a savings group, or opening a bank account?
  • Concerns: What are the biggest financial expenses/concerns that the customer has? If they are consistently concerned about being able to pay school fees or emergency medical bills it might suggest irresponsibility, or a lack of income.Blockchain technology is also being explored as a solution to provide additional certainty and comfort in scale.
  • A successful credit scoring algorithm will have to take all these considerations into account and will necessarily involve an iterative approach towards gradually reducing customer default rate. Machine learning finds a particularly interesting application in this field.



14 January 2019