Mobi724 Global Solutions – Marketing Payment Cards with Artificial Intelligence

March 16, 2023

The payment card market is booming. According to Equifax Canada, in Canada alone, the average monthly credit card spent per consumer rose by 17.5% in the first quarter of 2022 in comparison to the lows of previous year; new card volume was up to more than 31% from Q1 2021; and credit limits set by lenders for new cards reached an average of $5,500, the highest in seven years.

The most in-demand cards promise rewards:  eight in ten consumers (78%) have at least one such credit card (source: Ratehub Report on 2021 digital currency). Rewards, the Holy Graal of client loyalty for financial institutions, comes in different forms: cashback, store credit, travel card. “Consumers are looking for value beyond spending loyalty rewards in the same programs they are earning them in. They are looking for the freedom to choose how they earn and redeem their loyalty currency.” Hence, the systems that generate valued rewards are required today to offer a high degree of customization, flexible redemption options and timing. Sadly, banks are falling behind.

In the debit and credit card space, marketing has always been a pillar for growing business. Attracting new customers and finding incentives that increase business from active customers are at the forefront.

Card issuers segment their marketing campaigns with « generic » variables based on purchase history: the recency, the frequency, the monetary value.

This era is coming to an end.

Banks must define individualized offers based on variables that generate new revenue streams and that monetize transactional data.

« Banks must define individualized offers based on variables that generate new revenue streams and that monetize transactional data. »

Mobi724 Global Solutions is a fintech platform, which enables banks and merchants to offer real-time payment card-linked incentives. Mobi724’s objective is to add a layer of AI-driven actionable intelligence to every payment transaction creating engaging consumer experiences and generating incremental commercial opportunities to its clients. Always at the forefront of the latest advances and ensuring their clients reap the benefits, Mobi724 called upon CRIM to define the innovative approach to individualized offers.

The goal consists in predicting one of these scenarios:

  1. The probability that consumer A will be more prone than consumer B to purchase a given product, let’s say an automobile, as part of a promotional campaign.
  2. The probability that consumer A will make a purchase from a new category from which he/she never bought based on her past purchases from other categories, within a given timeframe. We are looking to predict that consumer A will purchase his/her first car (category 1) considering that he/she is a frequent buyer of plane fare (category 2)  – Michel Savard, Practice Lead, data science CRIM.


To make such predictions, CRIM experts have modelized buying habits of over 100 million cardholders in Latin America and from a wide range of merchant categories to which are linked to redeemable rewards. Their work resulted in a fine characterization of buying behaviour and context-rich inferences and generated the future expected value (FEV) of purchases over a given period.

Merchant Category Examples


The buying predictions generated by this model will enable clients to make better marketing decisions and program campaigns based on place and context – at the airport, on a cab ride, in pharmacy, at the grocery store, etc. A plethora of use cases can be imagined putting CRIM machine learning to test.  Experimenting on real-life campaigns would be the next phase.  Stay tuned.

1. Anonymous data provided by Mobi724 Global Solutions.

2. Merchant Category Code – indicating the merchant type from which originated the credit credit transaction.

Sources :


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