My past and current working experience in the private and public sectors has taken me to places where I could not imagine a wilderness dream and given me first-hand experience of poverty, particularly in my country. Working for the United Nations (World Food Programme) and the World Bank has given me a meaningful purpose in my life; it is no longer a job or career; it has become a part of my personal goal in the poverty reduction process. To achieve that, I have chosen to study the Master in Finance at Goethe Business School, specializing in financial technology management, and this would be my second Master's degree. Having seen inequality and worked in the slum-upgrading project, I know that accessing the financial system is nearly impossible for rural migrant workers. This is why I have specialized in financial technology management, hoping to use Fintech to promote financial inclusion.
Fintech has proven to be a tool for leapfrogging straight into digital technologies.
Fintech is a suitable tool for promoting equitable financial services to unserved and underserved populations who are denied due to barriers such as limited physical infrastructure, high costs, and customer identification documents. In Myanmar, Fintech has proven a tool to leapfrog straight to digital technologies; in 2011, Myanmar mobile networks covered less than 10 percent of the country's population. Since lifting economic sanctions in 2013, its mobile network coverage has been propelled to be nearly universally accessible in 2020. The fourth generation (4G) mobile networks just launched in 2016, and within five years, it has achieved 95 percent population coverage. Followed by the unprecedented rise of digital payment applications in Myanmar, the most successful mobile money or digital wallet platform is Wave Pay, reaching 5 million users, and 65,000 shops accept payments through this application. In addition, several other similar applications are rising with the growing number of nationwide users.
Penetration of Fintech to the population that traditional brick and mortar banks denied
The garment industry comprises nearly 90 percent of the employees, including women and migrants from rural Myanmar. During the COVID-19 pandemic, garment factory workers in Myanmar have either been laid off or reduced working days due to reduced order demands. As a result, they cannot pay housing and food expenses and remit back their salaries to families all over the country. To contain this crisis, the European Union launched a financial support program called the EU Myan Ku Fund to support garment factory workers through cash support payments. The program supported over 60,000 workers since the program launched on May 1st, 2020; it has assisted workers who have been terminated or suspended due to the impact of COVID-19 and unemployed, pregnant workers, and unemployed workers with young children. This assistance of cash payment was possible due to the transfer of cash via the mobile money platform Wave Money; it was only successful with Fintech playing a major role and the leapfrogging of digital advancement. This is a classic example of fostering Fintech to promote financial inclusion and unserved and underserved populations. There is still a huge opportunity to grow in many areas and untapped markets, such as access to micro-finance loans, essential ingredients in poverty alleviation.
Data mining for welfare assistance, governance, and early warning signs such as employment
Potential to identify the volume of transfers either increasing or decreasing, which could inform early warning signs to the different stakeholders. For example, a country with weak statistical employment measures could be used to determine whether a continued trend in decreasing transfer volume indicates rising unemployment. The local government could quickly identify the zone or ward that dropped in remittance volume and concurrently measure the remittance-receiving locations that would also be affected due to a downward trend. Only such valuable data could be gathered through the rise in Fintech.
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