Big data and AI are changing the nature of the financial industry in the United States and Europe. However, the impact on emerging markets is even more significant. The traditional financial infrastructure is less sophisticated in growing economies in Africa, the Middle East and Eastern Asia. These countries have invested more heavily in Fintech to overcome the limitations of their financial institutions.
Fintech is disrupting the financial industry in developing economies
Many factors are shaping the future of the financial industry in emerging markets. Fintech is among them.
What will be the role of Fintech in these countries? It is difficult to predict. However, recent figures show that the market for Fintech solutions in Asia alone is worth $200bn.
The demand for fintech is especially high in countries with limited exposure to traditional banks. China and India were the two countries with the highest reliance on fintech. More than 50% of consumers in India and nearly 70% of Chinese consumers relied on fintech for raising capital or money management.
AI makes fintech possible in emerging markets
AI is playing a vital role in the emergence of fintech. NetGuru discussed some of the reasons that big data is driving investment in more dependable and effective BI software and fintech technologies.
Here are some of the most important reasons:
AI helps improve actuarial lending options
Every financial institution needs to conduct an actuarial analysis before issuing a loan. Traditional banks are able to use credit scores to assess a prospective borrower’s financial responsibility.
Doing an actuarial analysis is more difficult for fintech companies, especially if their customers are in emerging markets. Developing economies don’t have the same credit scoring models and can’t always track customer incomes easily, even if they have access to tax documents. There are a variety of reasons for this, including record keeping technology and authentication models.
Artificial intelligence has helped development alternative lending solutions. P2P lending options often use social media platforms to help assess the creditworthiness of potential borrowers. Some of earlier P2P platforms have used systems where they give credits to users that refer people to the platform but penalize them if their referees defaulted on a loan. This system helped provide funding in emerging markets, while still weeding out people that made poor financial decisions. The theory was that people that conducted business with others that were more likely to default would be less creditworthy themselves. Companies like Lenddo are developing similar credit scoring models.
These earlier P2P lending models were a start. Newer models have helped Fintech companies find better ways to use financial business intelligence to create actuarial models for people in emerging markets.
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Improving asset pricing models with AI tech
Trading equities and other assets is a vital service that many fintech solutions provide. However, they need to be able to value those assets properly.
When cryptocurrency platforms were first introduced, they had difficulty properly valuing their models. This is largely because the transaction volume was low, which meant that it couldn’t operate as an efficient market. However, the growing interest in cryptocurrencies, better AI valuation models and efficiency of blockchain helped make the market much more efficient in recent years.
Fintech companies are using the same type of technology. They are also using generative adversarial networks (GANs) to help predict asset values. They use both predictive analytics and risk analysis models to forecast asset prices and value them accordingly.
AI assists in improving regulatory compliance
Meeting compliance standards is difficult for many financial institutions around the world. Fintech companies in emerging markets are no exception. These companies need to meet evolving expectations. The sudden surge in fintech companies has driven regulators in developing economies to implement stricter standards.
Fintech companies need help navigating these standards and ensuring they don’t deviate from them. The good news is that AI can help companies follow the standards and make sure that they don’t face unnecessary penalties.