Tamara and Tabby need big data to compete with Apple
Recently, Apple announced its Pay Later service, with plans to launch in the US and, in the future, expand elsewhere. This service establishes Apple’s presence in the buy now and pay later (BNPL) market.
The BNPL is a new Fintech solution that uses technology to revolutionize an existing solution. The old form of BNPL was the credit book that existed in local grocery stores in countries like Saudi Arabia and India. This old form has since been digitalized and is now being offered by big companies instead of small and fragmented local stores.
The business model for BNPL companies (BNPLCs) is part payment processing and part banking. Buyers pay installments but pay nothing extra. BNPLCs pay the seller immediately and receive a percentage from the sale, and the seller enjoys an increase in the sales volume. BNPLC business models differ from that of credit cards companies.
Credit cards companies offer pay later, but with interest to the buyer, who also pays an issuance fee. Further, there is no clear separation between transactions with credit cards, while with BNPL, each new transaction is a new agreement. Credit cards can be used anywhere while BNPLCs cover a limited network of stores as of today.
The BNPL market has been booming in many countries. The top 10 countries using BNPL are mostly Europeans in 2020, but other countries are catching up. Researchers expect the Saudi BNPL to grow to $636.7 million in 2022, while the global market is expected to be in the trillions by 2030. Apple seems to be aiming for a big slice from the whole global market.
Apple’s move made some Saudis speculate rough times ahead for Tamara and Tabby, the biggest players in the Saudi BNPL market, and similar speculations are taking place in other countries. Apple’s move is not only making waves in the Saudi BNPL market, but the BNPL global market, too.
Apple’s biggest competitive advantage is not only its Apple Pay, but also its big data. Through its big data, Apple can identify customers’ behavior and predict whether a customer will pay or not with reasonable accuracy using artificial intelligence (AI). Because of this, they can target a more extensive base of customers and avoid losses.
Bad debt customers (bad customers) is Tamara and Tabby’s biggest risk. Bad customers are those who won’t pay back their debt. In fact, Tamara and Tabby need to worry about them more than Apple, because their negative impact is big. Tamara and Tabby may need twenty good customers to recover from one bad one. If the number of bad customers increases beyond a certain point, they could end up making big losses and even facing bankruptcy.
Tamara and Tabby need to follow Apple’s likely steps in using AI to deal with bad customers. However, their AI won’t be as good as Apple’s. The reason is: AI is only as good as the data fed to it. Apple has its customers’ wallet, movement, and usage data, to name just a few. Thus, Apple has richer data, so its AI will likely perform better in predicting bad customers. Nevertheless, AI with limited data is a step in the right direction.
One possible option for Tamara and Tabby to compete with Apple’s AI is to collaborate with other companies. They can team up with local companies such as stc, which has data as rich and diverse as Apple’s. Through this kind of data, AI comparable to Apple’s can be built, reducing the risk of bad customers and limiting Apple’s competitive advantage.
The ultimate success of Tamara, Tabby, and other BNPLCs seems to be determined mostly by AI and big data.