Throughout history humans have seen various revolutions take place, caused by creations or innovations in the way that goods are manufactured alongside new technologies developed by states or companies. This is not something which has stopped; on the contrary, during the previous few decades, people around the world are experiencing the impacts of technology on their lives and the global economy.
Source: World Bank Group
The implications of being unbanked
Nowadays, we are seeing the effects of the introductions of artificial intelligence in different aspects of our lives. Many companies in the world are looking forward to mastering this technology whilst also creating new ecosystems and business models around it. One important aspect of this is how artificial intelligence could help the banking and financial industries, specifically in the field of financial inclusion.
Bank history was built on the “brick and mortar” model, and even though that is currently being challenged from a digital perspective, there are still strong remains in many institutions. In addition to that, the typical approach in how banks know and evaluate individuals before accepting them as customers, results in many people being excluded. Furthermore, it creates a space where other companies could take advantage of this situation and offer high expense financial services to those who were rejected from the system.
Being “unbanked” these days implies a lot of consequences on the daily lives of people. This includes the difficulties to access credit and also the lack of access to a secure and comfortable means of payments. This is because the unbanked have to use cash for all their transactions, which creates additional barriers and complications in the payment of basic services. Furthermore, being unbanked means not getting promotions since these are designed around bank products. And these are only a few of the implications of being unbanked.
But AI is laying the foundations to change that. Pioneers and FinTechs, followed now by some banks, are using AI to bring financial services to the unbanked, starting from “branchless banking” models, which are one hundred percent based on digital channels and with new business models leveraged in economies of scale. These companies are using AI to improve (and also create new) processes related to communication, fraud prevention, credit scoring and financial education.
AI in finance: from chatbots to fraud prevention
Communication is now in a very different place from where it started. It is shocking to think that in the beginning, people received their account statements by mail, and, if they wanted to cash out or transfer money, they had to go to the bank. These days, not only are we seeing the use of AI to proactively contact customers through digital channels with personalized offers, but also, many FinTechs and banks use chatbots to solve customers' questions and doubts about their services, and any issues related with it. This is very important since many people who live outside cities, in farms or in small towns now do not need to travel anymore to communicate with their bank or financial institution. Also, chatbots and event-based communications extend their business hours, since the communications are available (in most of the cases) 24x7.
In fraud prevention, AI allows reinforcement of customer authentication, adding new layers of control. As an example, related with the onboarding process, the introduction of machine learning and deep learning into images forensics, allows for cross verifications across data documents but also validates the right ownership of the document information by comparing real time selfies with the photos included on documents. Also, in the field of transactions, AI brings the possibility of understanding the nature and purpose of a transaction and analysing it to see if it matches with the customers' profile and spending patterns. This is helpful for financial institutions to perform due diligence across every transaction but also to protect vulnerable people which could be exposed to cyber attacks.
The application of artificial intelligence on credit scoring allows FinTechs and banks to drastically include the unbanked on the market, who typically were not capable to demonstrate incomes or credit history, being mostly cash intensive users. Historically, this was a chicken and egg problem since in the past banks asked about incomes before giving their basic services as savings accounts or a debit or credit card. Now, new customers can use those products in their everyday life, building in the background a credit history, which in the future, would be used as the primary indicator to get access to loans or mortgages. Since the unbanked are not able to get the right qualifications to access those basic services and products, they won’t be able to build their credit history, cutting any possibility to get in the future access to credit lines.
Now, AI brings the tools to allow the unbanked to build a credit history and most importantly to access affordable loans according to their capabilities. Using behavioral attributes available for everyone, such phone information (contact lists, locations), bills or social media information and introducing them into machine learning models which create predictions about the potential of repayment of a person. Some companies also include, as part of their analysis, the use of digital wallets, prepaid cards and the spending patterns to create personalized credit proposals.
Also financial education is being benefit from AI, since FinTechs or banks could take an advisory role for their customers, providing tools which allow them to manage their financials, identifying patterns which could expose them to liquidity problems and also urging them to save money through challenges or daily habits.
The challenges ahead
But even when AI has a lot of applications for financial inclusion, it also has some risks which could aggravate the problem and unintentionally exclude more people from the system. First of all, and this is something intrinsically related with technology in general, with financial ecosystems becoming one hundred percent digital, it could be a problem for elders and people with disabilities which could have additional barriers to overcome in a truly digital world, which could not be considered in the first stages of implementation.
Besides, models developed for AI are at the end, made from algorithms and datasets, which could include unconscious bias in their designs, such as not fully representing the diversity of needs for the unbanked in terms of their ethnics, gender or socio-economic conditions. Also, the introduction of AI technology across the entire financial ecosystem, could generate job displacement in the operations levels of the structures, since manual processes could be automated across software or even with the inclusion of robotics for that.
These are real challenges which any financial institution should take into consideration for their implementation of AI and work to eliminate (or at least mitigate) the impact on the vulnerable populations.
In the end, the inclusion of AI across financial ecosystems has benefits for the both parties: the unbanked and companies will benefit from the positive effects of this technology. In the incoming years, more and more companies will advance in the application of AI in their solutions, and hopefully, financial inclusion will be a reality in most of the societies.
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