This Ghanaian startup is giving customers credit where it's due, on their smartphones

The past decade has brought huge innovation to the lending industry. Companies like LendingClub, OnDeck, Kabbage and Fundera made online lending platforms a standard. Each of these companies enables borrowers to more easily obtain a loan, while investors can purchase notes backed by payments made on the loan.

These companies filled an important void -- financial institutions were reluctant to provide small business loans to businesses without good enough credit history or individuals facing a similar problem.

This trend didn’t go unnoticed by major banks looking for more ways to drive revenue and in late 2015 JPMorgan Chase teamed up with OnDeck to offer small business loans. The financial world has gotten smaller.

Yet, it didn’t go too small. Micro-loans, which provide customers loans of $50 to $500 on a short term basis, have been historically provided by family and friends. It was just a question of time until innovation revolutionized this area as well. Tomer Edry, Nadav Topolski and Nir Zepkowitz are Israeli entrepreneurs with a passion for finance and doing business in Africa.

Each with MBAs from top US universities and success conducting business in Africa, these 3 friends became intrigued by the micro-lending space. Specifically, how people were going about applying for and getting approval for small business and personal loans in Ghana.

The feedback they received from both loan officers and loan seekers was that lack of data makes this process extremely complicated and inefficient, with most people not getting approved for loans purely due to lack of data.

It got them thinking that there must be a better way to go about it, by using mobile technology while focusing on developing a data driven approach to this problem. That was the beginning of the FIDO Solutions story.

After the initial idea was developed, Edry, Topolski and Zepkowitz brought in Eden Kfir, Gadi Regev, and Boaz Jacobi to enhance the team and propel Fido’s development. Jacobi (CEO) led the process of developing the risk analysis model, and very quickly ran into a major crossroad.

Jacobi states “we asked ourselves whether we could count on third party data sources for making decisions on who to approve, or whether we need to develop the entire system ourselves. We decided to develop the entire risk model in-house and not rely on banks, telcos and other sources of data, which ultimately separates us from other companies in the micro-loan space.

At the end of the day, we want to be in every developing country, and relying on our own systems assures us scalability”.

FIDO developed a robust technology platform that offers automated operations of micro-loans by leveraging mobile technology that reaches new customers in developing countries. Ghana was an initial case study and the sandbox in which the company was able to develop their proprietary end-to-end solution.

In Ghana, FIDO provides fast and easily accessible short-term loans for people in need of amounts between $50 to $200. Previously, the only resources available to most people in Ghana and other African countries for this type of loans were family and friends. Now FIDO provides a mobile first solution where customers can apply directly for a loan using their mobile device or at a FIDO branch and receive an instant credit decision and money in their mobile wallet or bank account within minutes.

The loan is available to salaried, self-employed professionals and small businesses , no collateral or guarantors are required, but rather an automated instant online KYC (Know Your Customer) process prior to disbursement. Approved customers can receive their cash within minutes. This is a significantly more efficient process for people looking for quick, micro-loans, and for many in Ghana it’s been simply revolutionary.

Data Is Everywhere. Literally.

In order to develop a reliable home-grown alternative risk model FIDO had to develop a unique set of data points. They accomplish this by focusing on data generated from mobile phones of loan applicants.

This includes data generated via the actual application form, the time it takes to complete the form, whether or not there are spelling mistakes, the phone location, contact list and even the exact timing of when the phone was last charged.