Combining data exchange with generative AI enables banks to manage data more efficiently, particularly in personalizing the banking experience. This is why IBM and Artefact have jointly developed the platform based on generative AI to improve persona creation.

Combining data exchange with generative AI enables banks to manage data more efficiently. This synergy promotes more personalized banking experiences while meeting the trust, legality and data accuracy requirements expected by their clients and stakeholders. Because the marketing sector faces the same challenges, IBM and Artefact have jointly developed the platform based on generative AI to improve persona creation.

Data at the heart of bancassurance decision-making

The banking sector is inextricably linked to data: payment data, customer information, The banking sector is inextricably linked to data: payment data, customer information, transactions, etc. It’s a simple fact that banks know their customers better than most other industries. And data sharing between financial institutions and other businesses paves the way for highly personalized experiences. This phenomenon is amplified by a favorable regulatory context, with standards such as the Payment Services Directive 2 (PSD2) which encourage data sharing between banks and third-party actors. In addition, banks operate in a competitive environment where they constantly seek growth levers, and one of those levers is data sharing.

Raw data exchange has little intrinsic value

Generative AI enables data sharing to create value for both banks and businesses by providing a better understanding of the clientele. For example, by cross-referencing a company’s customer data with that of banks, new segments emerge, enabling more precise targeting.

Data sharing in the banking sector addresses three major challenges:

  • Trust risk: How much data can banks share without compromising the trust of their clients? In France, banks are generally perceived as the most trustworthy guardians of personal data, even more so than the government. This trust must be maintained.

  • Legal risk: Data sharing must comply with current regulations, especially the General Data Protection Regulation (GDPR), to ensure the proper use of sensitive data.

  • Identifying needs: Understanding the types of data and granularity required to meet the needs of merchants is essential.

GenAI: more advanced and efficient than traditional machine learning

At the forefront of generative AI technology and use cases in data sharing for banks, Artefact and IBM have developed a rapid persona creation platform for marketing campaigns: provides advanced data processing capabilities, including advanced natural language models, text generation capabilities, and data analysis. The platform covers the entire lifecycle of artificial intelligence projects, from data collection to model deployment.

It also enables the creation of generative AI applications without requiring deep technical expertise. Users can participate in ideation and refinement workshops for specific client needs. makes AI model creation faster, more accessible, and more tailored to specific business needs.

“[ generates] value through persona creation, which takes a lot of time on a large scale. Artefact’s teams had access to multiple low-code studios on the platform to develop the solution quickly. Generative AI enables this acceleration because it requires only a small amount of data to produce excellent results. This is a real innovation compared to the previous machine learning paradigm”.
Jean-Armand Broyelle, Principal Data Scientist / Client Engineering France – IBM

Real-time persona generation for ultra-personalized marketing

The persona generation process begins with the selection of several parameters:

  • Choice of the number of clusters to create based on the needs of their marketing campaign, from a few clusters for a broad approach to several dozen for fine segmentation.

  • Selection of the relevant industry for the campaign to ensure that the generated personas match the company’s business sector.

  • Specification of the demographic characteristics of personas (age, gender, residence, income).

  • Definition of segmentation criteria that allow personas to be grouped into clusters based on their buying behaviors, preferences, and habits (amount spent, types of products purchased, number of transactions).

Once all parameters are configured, generates personas in real time. Each persona is accompanied by a randomly generated face that illustrates the customer segment. A natural language description in English explains who they are from a business perspective. These synthetic data refine the understanding of the profile for better command of marketing campaigns.

Interaction with personas to better understand them

The application goes further by providing the ability to interact with personas. Users can initiate a conversation with a specific persona, ask questions, and receive answers based on the data provided. They gain a better understanding of the needs and preferences of each customer segment.

They then personify their personas. In other words, users can ask the model to behave in a certain way by providing it with psychological and socio-demographic characteristics that are useful for understanding how to respond and putting themselves in the shoes of the targeted profile.

“To fully understand a target, it is possible to interact with its persona. Then, following the same principle as ChatGPT, writes hyper-personalized messages adapted to the chosen channel and to each target. This approach is extremely fast and saves time in the implementation of marketing campaigns”.
Jérémie Cornet, Senior Manager Banking Services – Artefact

The platform also enables the generation of personalized marketing campaigns with just a few clicks. Users specify the communication channel, the products to be promoted and the messages to be sent. These messages can be automatically produced for each persona based on their characteristics.

Generative AI coupled with data sharing is the winning duo

Whether for a small business or a multinational, offers considerable time savings and increased precision for marketing campaign creation:

  • Significant reduction in time needed to create personas: from weeks or months to hours.

  • Much finer customization, with personas based on current, real-world data.

  • Interaction with personas to place them in situations.

This application demonstrates how data sharing, combined with generative AI, can bring substantial benefits to the banking industry by providing more effective and better-tailored marketing solutions for customer needs.