Role of AI in BNPL Fraud Detection

The growing popularity of Buy Now Pay Later has increased the risk of fraud in the process stated Bahaa Abdul Hussein. Fraudsters look at innovative ways to try and scam users. Detecting and also preventing fraud is important to ensure the success of BNPL. This is why BNPL service providers have brought in Artificial Intelligence (AI) to aid them.

BNPL Frauds

There are three types of fraudulent activities that can take place in BNPL:

  1. Account takeover: Fraudsters can take over a customer’s account and use it to make purchases through BNPL. Since payment is delayed, the parties involved may not get informed of the fraud on time.
  2. Chargeback fraud: Fraudsters can make a purchase and then later claim that their account was compromised. Since they get possession of the product, they may refuse to make payments.
  3. Synthetic user fraud: Fraudsters create accounts with fake information or partially correct information. They may abscond after buying a product and not make payments. With less information available, service providers find it difficult to track down such users and get back their money.

Use of AI for BNPL fraud detection

Artificial Intelligence is a boon in the cyber age. With instances of fraud increasing, it is vital that service providers be prepared to deal with fraud. They need to constantly on their toes, and AI will help them do it. The following explains how BNPL providers can use AI to detect and even prevent fraud:

  • AI systems can identify patterns that include behavior of customers, the devices they use for shopping, method of payment they choose, etc. Through such patterns they can classify transactions by assigning a risk score. If a transaction has a higher risk score, the AI system can tag it as fraudulent. Such transactions can be rejected, preventing stakeholders from becoming victims of fraud.
  • AI systems use machine learning, which allows the system to learn just like humans do. The system learns from data that is analyses from different transactions. The learning allows the system to be more effective in flagging fraudulent transactions. Both the efficiency of fraud detection and accuracy can be improved through machine learning.


Fraudsters can scam BNPL users causing losses. Thankfully, AI offers a convenient way of dealing with such frauds. AI with machine learning not only helps in detecting fraud, but also can help prevent it. With new developments in AI, BNPL providers can be confident that they have a foolproof system to deal with fraudsters. The article has been written by Bahaa Abdul Hussein and has been published by the editorial board of Fintek Diary. For more information, please visit

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