Financial Services
Drive smarter decisions, faster innovation, and stronger outcomes in finance without compromising data privacy
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Driving innovation in financial services through secure, privacy-preserving collaboration
Sherpa.ai’s Federated Learning platform enables banks, insurers, and other financial institutions to securely collaborate on high-impact use cases—such as fraud detection, anti-money laundering (AML), credit scoring, and cross-selling—without ever sharing sensitive customer data.
By applying privacy-preserving AI across decentralized datasets, Sherpa.ai empowers financial organizations to unlock the full value of collaboration while staying fully compliant with data protection regulations—enhancing risk management, boosting personalization, and accelerating time-to-insight.
Federated Learning and, in particular, Sherpa.ai’s Artificial Intelligence platform have multiple applications to the financial industry. One of the most important ones is fraud detection, which continues to be one of the main challenges the industry faces on a daily basis.
Former CEO of La Caixa and Banco Sabadell
Former General Manager of Banco Santander
Federated Learning Cases in Financial Services
Credit Scoring and defaulter's prediction
Enable accurate credit scoring and early identification of potential defaulters through secure, collaborative AI. Sherpa.ai’s Federated Learning platform allows multiple institutions to train models on decentralized data—without ever sharing sensitive customer information.
Enhance Cross-Selling in Banking & Insurance
Unlock new revenue by securely connecting banks and insurers. Sherpa.ai enables to develop better AI models for cross-selling—without sharing customer data between banks and insurers.
Prevent High-Value Churn with Secure Data Collaborations
Enhance churn prediction by securely integrating third-party insights—like insurers or telecoms—without sharing data. Our platform enables privacy-preserving AI to help you retain high-value customers.
Enhance Anti-Money Laundering & Fraud Detection with Secure Collaboration
Strengthen fraud detection and AML capabilities by leveraging insights from multiple financial institutions or third parties—without exposing sensitive customer data.
Reducing by 99% the Communications of a Single Training
This paper presents a novel Federated Learning framework that enables secure, collaborative model training across multiple organizations without sharing raw data. By optimizing communication efficiency, it reduces network exchanges by up to 99%, dramatically enhancing data privacy and security. The proposed architecture improves scalability, lowers energy consumption, and achieves state-of-the-art performance across real-world applications in healthcare, finance, manufacturing, cybersecurity, aerospace and defense.
Collaborative Defaulter Detection Across Banks with Sherpa.ai’s Federated Learning Platform
Accurate defaulter detection is critical for banks to effectively manage credit risk and reduce financial losses. Yet, enhancing prediction models through interbank collaboration is often limited by strict privacy regulations, competitive sensitivities, and restrictions on data sharing.
Sherpa.ai’s Federated Learning platform enables multiple financial institutions to collaboratively train a global defaulter detection model—without ever exchanging sensitive customer data.
This project demonstrates that secure collaboration across banks using Sherpa.ai’s platform leads to a global model that consistently outperforms individual bank models, all while maintaining full data privacy.
The approach not only minimizes risk and ensures regulatory compliance but also scales seamlessly across institutions.
Federated Learning Reaches Its Maturity Point in the Financial Sector, According to Gartner
The recent Gartner Hype Cycle for Artificial Intelligence in Banking 2025 positions Federated Learning (FedML) at the peak of inflated expectations — the point where technological innovation captures maximum market attention before widespread adoption.
This position confirms a trend we have long observed at Sherpa.ai: financial organizations, and increasingly other sectors, recognize that the future of artificial intelligence lies in collaborating without sharing data.
How Federated Learning Is Transforming the Financial Sector
Artificial intelligence (AI) has become the most powerful driver of transformation in the financial sector over the past decades. From process automation to fraud detection and service personalization, AI is redefining how banks, insurers, and fintech companies understand and manage risk, efficiency, and customer experience.
However, the massive adoption of these technologies has been held back by one fundamental challenge: data privacy and security. Financial information is among the most sensitive assets that exist.
