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by Emmanuel Mogaji
LONDON - While artificial intelligence (AI) is somewhat of a buzzword which everyone now finds relevant to their business, this disruptive technology has huge potential to add value in financial services firms is enormous.
Fintech is competing with traditional financial methods in the delivery of financial services, using technology and innovation to improve activities in the financial sector. Fintech generates a comprehensive data view of customers which AI can be used to refine and better shape the customer experience and service offering. This will enable a long-term societal change in the way services are provided for those who are financially excluded and under-served. Conversely, AI is opening more opportunities for the financial services industry.
The United Nations expects digital financial inclusion to become a priority given its prominent position as an enabler of other developmental goals in the 2030 Sustainable Development Goals. It is also anticipated that fintech will extend the reach of financial markets, notably to the excluded and underbanked at a reasonable cost, and on a sustainable basis.
Chief among these unbanked groups are vulnerable individuals who rely on payday loans to meet their financial obligations. Often, these are members of social minority groups, those living in disenfranchised neighbourhoods, and those neglected by traditional banks. Payday loans are small, single-payment loans that are repayable on the borrower’s next payday. This is considered a form of high-cost, short-term credit (HCSTC) in the UK.
While recognising the opportunities AI is bringing to fintech, this article highlights three critical implications which require further consideration as vulnerable individuals apply for payday loans. While in the past, most payday-loan lenders operated on the high street, today there is a shift towards making applications online. Advancements in technology have contributed to the growth of the payday loan industry. People no longer have to visit a physical store to request a payday loan; instead, they can apply online with the assurance that they will be granted the loan.
Currently, the advertising opportunities for payday loan companies are quite limited. They often only have their website to showcase what they can offer to prospective borrowers, and they expect potential borrowers to use their website to apply for the loan. This website is used to acquire much information from prospective customers.
Some payday loan sites position themselves as direct lenders, assuring customers that they will process their application more quickly and that decisions will be made faster. Also, some brokers also front as direct lenders, suggesting that they offer loans themselves when, in fact, they only collect information from borrowers and share it with the actual lenders.
The vast amount of data being generated and provided by the consumers, increased use of the mobile device for online application presents a significant development of artificial intelligence for data processing and modelling. The implications of this collected information are worthy of consideration, as there are no indications that it would not be shared with other third parties without the knowledge of the individual.
The data of those who have applied for a loan can be shared among lenders for retargeting, highlighting the ethical and marketing issues surrounding these lenders. Data is essential in understanding the customers, their journeys, and developing the advertising campaigns.
Personalised and automated content creation based on the data collected through the website is now very much possible. The AI algorithm receives a massive amount of information from these vulnerable individuals and targeting them with another advertisement, encouraging them to borrow more money and continually be in debt even though they have not finished paying their original loan.
Likewise, other lenders may contact them with marketing communications, luring them to apply for new loans since they have their details. The Competition and Markets Authority’s Payday lending market investigation report found that demand for payday loans is typically recurring, three-quarters of customers take out more than one loan in a year, and more than 80% of all new loans were made to customers who had previously borrowed from the lender.
Although the companies state that the Information Commissioner’s Office licenses them, there are considerable concerns about the information that is being shared between lenders and brokers in an attempt to make easy payday loans available, as the commercial success of the brokers depends on the commission they earn.
These applications are processed with AI. Lenders even take pride in their technological advancement. They acknowledge that their technology was created to search the market for top deals, generating a 100% no obligation quote that borrowers can choose to accept or reject. They also acknowledge that technology is responsible for offering unique service such as personalised quotes using auto decisioning.
This allows lenders to decide on loan application without the need for human interaction. The website asks a few simple questions about their circumstances and affordability and gives an instant decision about whether they are likely to be accepted for your chosen loan.
The human understanding and empathy while processing the payday loan application are consequently missing. Unlike when consumers go to the shop to get their loans, the staff can be helpful, provide information and signpost for help, but now with things almost automated with AI, the human though and consciousness is missing.
AI is expected to bridge the gap between the brands, the customers and data in other to transform the customer experience. No doubt, consumers will continually provide more data for AI to learn from. However, the ethical handling of these data needs to be considered, especially by understanding that there are vulnerable individuals who may not have the financial liberty to make an informed choice.
It is recognised that AI in financial services can be used for Customer Profitability Optimization and Credit Approval Process Optimization, however, there is a limitation with regards to the human empathy in understanding the underlying need for the fast cash which the Machine might not be able to determine. This presents implications for policymakers, financial services providers and developers to provide a sustainable and ethical financial product.