The AI-Driven Bank in Emerging Markets

AI use cases for fintech startups
Co-authored by: Abi Steinberg and Alexandre Lazarow
September 22, 2017 - 3 mins read


If you think artificial intelligence is a thing of the future, ask yourself why your Amazon homepage looks different from ours or how Google translates websites on the fly. Consumers in developed and developing countries are benefiting today from these smarter types of software. In particular, the subfield of Machine Learning is making rapid strides in everything from detecting rare types of cancer to correcting our grammar. In essence, software development is transitioning from a process where humans figure out a few rules for the machines, to one where the machines learn the many implicit rules from the existing data. This advance now allows software to recognize all past situations and make accurate predictions about when they happen again.

The AI pioneers mostly hail from the tech sector and have been disrupting the financial services industry through fintech innovations. Moreover, the larger financial players in developed economies are already adopting AI aggressively, in turn changing how finance operates. Provided they have sufficient quality data, financial institutions in emerging markets could also start adapting these technologies, facilitating better and more customized products, nimbler and cheaper operations, and eventually more profits.

We are already seeing the effects of AI across a range of use cases in emerging markets. For example

As the use of AI expands, we see it fundamentally transforming the ability of banks to drive financial inclusion. To picture what the future might look like, let’s sketch three bold, but plausible ways in which today’s barriers might be eliminated.

The first barrier to greater inclusion in many emerging markets is multiple languages and low literacy levels, which make basic communication between banks and customers very difficult and inhibits the development of trust. In South Africa, for example, where there are 11 national languages, English is the primary language for interaction with banks, but it often forces the unbanked and underbanked to transact in their second or third language. AI could boost access through voice responses and chatbots that speak local dialects in a jargon-free understandable manner, providing a radically different experience for most customers that creates trust, fosters a more personal relationship and ultimately drives greater usage.

A second barrier is the standardized products that require customers to stay within the confines of complex and rigid offerings. AI could empower an advisor finbot to customize and offer dynamic terms and services matched to the customer and his context. This hyper-tailoring would create services that are more useful and effective, improving usage and impact.

Related to the second barrier is the third: standardized service. With emerging-market micro-entrepreneurs now digitizing their operations, AI-powered banks could offer practical advice through specialist bots for retailers, farmers and restaurateurs, for example. These digital consultants could help small businesses manage their operations, automate processes and facilitate decisions, improving profitability for businesses and banks alike. These bots also could coach entrepreneurs as they develop more skills, become more productive and expand their businesses.

Clearly, AI technologies will enable financial organizations in emerging markets to provide far more value to customers. AI would keep their customers at the center, creating better and more meaningful experiences even at large-scale. We believe this is an exciting revolution in the works, and we just can’t wait to get past the pioneer stage.

We know that there are risks and challenges that lie ahead. In the meantime, if you are working on AI approaches that foster financial inclusion, let us know. Take our brief survey

Originally published at The Financial Revolutionist on September 07, 2017.

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