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Synerise

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"AI-driven platform for behavior-based customer interactions."

Synerise assists marketers by applying AI and machine learning to analyze and interpret behavioral data in real-time, enabling them to create personalized and automated customer experiences based on actionable insights gained from this data.
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BlurbSTAR Case Study
BNP Paribas & Synerise
Synerise revolutionized BNP Paribas through effective AI implementation.
45%
Decrease in data processing time
100%
Data processing on customer infrastructure
1.
Situation
Synerise enhances BNP Paribas innovation
→
BNP Paribas needed innovative digital solutions.
→
Implemented Synerise's BaseModel.ai for customer insights.
→
Aimed to boost personalization and efficiency.
BNP Paribas, a leading Polish bank, sought to improve its digital offerings through innovative technologies and became the first in Poland to implement BaseModel.ai. This strategic move aimed to transform vast amounts of raw customer data into insightful behavioural profiles. The collaboration with Synerise, a European leader in AI and big data, was a foundational step in their AI industrialization strategy, focusing on elevating customer experience through personalization and efficiency.
2.
Task
Deploy BaseModel.ai with precision
→
Integrate and validate BaseModel.ai for effectiveness.
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Target various client segments for better insights.
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Enhance data interpretation and personalized communication.
The task was to integrate Synerise's BaseModel.ai within BNP Paribas to automate the conversion of raw data into actionable behavioural profiles, enabling deeper customer understanding. This required validating the framework's effectiveness through a proof-of-concept phase. The goal was to roll out AI models across various client segments, ensuring quick adaptation and scalability, reducing the interpretation time of massive datasets, and enhancing personalized communication strategies to improve customer satisfaction.
3.
Action
Rapid AI deployment in banking
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Trained multiple business models swiftly.
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Reduced data processing time markedly.
→
Improved service delivery with precision.
During the proof of concept, BNP Paribas trained and deployed foundation models along with eight business models based on these foundations. This setup significantly reduced the time required for processing and delivering actionable insights, dropping from months to mere days. This streamlined implementation fostered more efficient banking operations, allowing targeted service delivery precisely when required. The models allowed for refined customer profiling and improved personalization efforts, creating bespoke offerings that aligned with individual customer needs.
4.
Result
Improved personalization and efficiency
→
Enhanced data processing and personalized offers.
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Increased customer satisfaction and predictive accuracy.
→
Reduced costs and maintained security integrity.
The collaboration brought substantial improvements in data processing speed and personalization, optimizing banking operations without extra workload. BNP Paribas experienced enhanced analytical accuracy, allowing for timely and appropriate offers based on individual customer needs. The successful deployment of BaseModel.ai delivered significant business benefits, including improved customer satisfaction and loyalty, better predictive capabilities, faster implementation of innovations, and reduced operational costs while maintaining robust security and data integrity.
Keywords
BNP PARIBAS
SYNERISE
BASEMODEL.AI
AI IN BANKING
CUSTOMER PERSONALIZATION
BEHAVIORAL DATA
DIGITAL TRANSFORMATION
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