Informal Employment and Alternative Lending from fintech services
Its no secret that fintech has bridged the gap between supply and demand for financial services especially in emerging markets. Few people had access to the official banking services because of challenges such as financial literacy, poor or outdated telecommunications and banking infrastructure, especially in rural areas, security risks and concerns regarding system resilience and inconsistent regulatory. Fintech businesses overcame those challenges, offering tailored services for the unbanked and low income services.
A recent article at entrepreneur.com shows us that low unemployment rate characteristic for most developing countries is another reason which led to the massive adoption of fintech services and especially alternative lending services.
According to this article, the informal employment sector, which official GDP does not reflect, holds a significant share in the economies of developing countries. “In some countries, more than 50 per cent of the working population are to some extent involved in the informal sector. The reason is that this kind of income is usually additional to the earnings at the official place. Workers can produce a particular product to be counted in official GDP but have small official wages and the rest paid in an envelope.”
The article notes the low unemployment rates of many emerging markets in Southeast Asia, which to some extend can be attributed to the utter lack of unemployment benefits available. “That’s what makes people ready for any job to satisfy the need in finance. As a result, there is a situation when nearly all the population is employed, many of them have official jobs and earnings but low that make them seek additional work and source of income”.
Until now banks have used traditional methods to principally estimate borrower’s financial reliability and credit history. They ask for the confirmation of the official income and address credit bureaus for information about the applicant's repayment discipline. But these methods have proven ineffective for a significant part of the population which faces labor conditions as those described above. Official documents cannot provide a “full picture” about borrower’s reliability, that’s why a lot of people become simply considered as insolvent and cannot access finance.
On the other hand, fintech companies use a much different approach. They use AI, big data and machine learning, focusing on the borrowers' digital footprints. Scoring programs are looking for hundreds points of data about the person on the Internet and as a result of the analysis of many unstructured and scattered pieces of this information, companies understand the probability of debt repayment. That’s why they are able to provide unique micro and nano finance solutions (as those provided by Channel VAS) “boosting financial inclusion and accelerating subsequent economic growth by increasing the penetration of financial products into people's lives”.
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