The Funding Gap: A global challenge

Missing Data: Lacking credit data about businesses

Back in 2014, my partner Thorsten Neumann and I embarked on a mission to create technology to enable greater financial inclusion within emerging markets. We succeeded in bringing much needed electronic payments and agency banking services to tens of thousands of people. However, during this journey, we witnessed first-hand the difficulties which small and medium enterprises (SMEs) faced in obtaining finance. As we dug deeper, it became clear the primary cause is a lack of trustworthy digitised credit data to make borrowing and lending simple and cost-effective.

SMEs: Underappreciated economic powerhouses of emerging markets

According to the International Finance Corporation, SMEs generate nine of ten new jobs, while Emerging Market (EM) countries contribute over 80% of world GDP growth. So it’s safe to say that SMEs in aggregate power the world economy. They are greatly underappreciated.

However, they do struggle to obtain financing — to the extent of over $5.2 Trillion per annum. This severely limits the potential to grow, provide jobs and drive sustainable communities, not to mention centres for dialogue, and micro-entrepreneurial opportunities.

Today, the shortage of funding at reasonable rates is due to a myriad of factors including, most notably, the lack of digital data such as Know Your Customer (KYC), limited access to trustworthy cash flow information, absence of liquid collateral, high transaction costs and inefficient loan application processes.

Benefits of Data: How empowering merchants will jump start EM economies

Around 40% of all micro, small and medium-sized enterprises in EM countries lack access to credit. Their need for funding is almost endless as they manage cash flow, improve inventory, renovate, expand their footprint and, more generally, grow in size.

Governments, financial institutions, companies, NGOs, trade partners and the public would also benefit greatly from accurate and comprehensive credit data records about merchants and businesses at the grassroots level.

Types of Data: Relatively static and dynamic

Business credit data comes in two forms — relatively static and dynamic. Firstly, static data consists mainly of KYC records such as name, address, business licenses and ownership information. This information does not change frequently and remains valid for a long period of time.

The second type of data such as cash flow-related figures, turnover and supplier relationships, is dynamic in nature. For example, a business might enter into a new lease agreement, purchase insurance, engage new trading partners, and receive tax clearance certificates. These developments are material in nature, and directly reflect on the business’ good standing and ongoing trade activity.

Lenders, insurers, and financial service providers are constantly looking for this insight to improve their credit rating models. They need visibility on both static and dynamic data to evaluate the creditworthiness of an SME.

The Value of Data: Credit bureaus monetizing your information

Developed countries, primarily in the West, established regulatory frameworks and policies for credit bureaus to collect data about individuals and businesses. These bureaus have grown into large institutions, consolidating hundreds of millions of records across all sectors of society. They’ve created their own marketplace for precious data at the expense of the real data owners.

Credit bureaus such as Transunion, Experian and Equifax are billion dollar enterprises. They charge high fees for access to third parties, thereby earning income from selling other people’s data. Not only do the participants not earn from their own data, they are often at a loss as to how they can correct errors or otherwise influence their credit scores.

In recent years, these credit bureaus have come into the limelight for their significant data breaches as their valuable credit data was not well protected. Malicious users had broken into their inadequately secured systems and extracted millions of records. It is estimated that up to 145.5 million individuals and businesses were affected. The hackers downloaded large datasets containing social security numbers, addresses, dates of birth, tax IDs and driver’s license information. To add to the significance of these breaches, the numerous unauthorised incidents went undetected and unreported for months.

Emerging Markets: The absence of credit bureaus

The fast growing economies have their own challenges. Most notably, there is a small number of credit bureaus and their data sets are much smaller in size. Only a few organizations including banks, telcos and government departments collect information about the private sector. This leaves a void for precious credit data due to the lack of technology automation, challenges in consolidating records, and the lack of incentive for collaboration.

The challenge specifically in emerging markets, exists where organizations keep only their own data and are unable to efficiently share it with third parties. A bank will have its own ledgers of businesses’ transaction histories, while an insurance company sees only the frequency of insurance premium payments. The data is often unstructured and kept in separate information silos by each organization.

A Better Model: Empowering the data owners

A better model is needed to empower the data owners. In a new technology-driven approach, one could propose a solution to bring direct benefit to business owners and their businesses. We believe there can be a model whereby they can monetize their own data, while being economically incentivized to contribute new information towards improving their credit scores.

In this approach, a business owner could receive payments from other organizations which want access to their credit data, and in turn, make payments to verification services to improve trust as well as their own credit history. We believe there can be a practical solution for the collection and sharing of credit information as well as a means for easy continual updating of credit data by every business.

As SmartPesa, we want to tackle this problem of missing data to specifically address the funding gap. A token-based economic model that gives control back to the data owners seems to be a well-matched solution.

For more information on SmartPesa Credible, visit www.smartpesa.io

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