Banking

Tensor9 for Banking

Banks and financial institutions leverage advanced AI solutions for fraud detection, risk management, and customer service personalization. These applications require access to highly sensitive data, such as account information, transaction histories, and credit risk profiles, making security and compliance top priorities.

Tensor9 enables banking software vendors to deploy their platforms directly into customer-controlled environments, ensuring compliance with stringent regulatory requirements while maintaining a cloud-native experience.

Key Challenges for Banking Software Vendors

1. Data Privacy and Compliance:
   Banks must adhere to strict regulations that govern the storage and processing of sensitive financial data, such as customer records and transaction details.

2. Fraud Detection and Prevention:
   Real-time analytics platforms must continuously monitor transaction data to detect and prevent fraudulent activities.

3. Customer Trust and Security:
   Banks must ensure that their systems and third-party solutions safeguard customer information against cyberattacks and unauthorized access.

4. Operational Resilience:
   Banking platforms must remain operational 24/7 to support essential services like transactions, payments, and account access, even during external disruptions.

How Tensor9 Helps

Tensor9 addresses these challenges by enabling Any-Prem deployments of banking solutions within customer environments.

1. Data Sovereignty and Security:
   Tensor9 ensures that sensitive customer data remains within the bank’s secure infrastructure, meeting compliance mandates and maintaining customer trust.

2. Customer-Controlled Change Management:
   Banks can control when software updates and patches are applied, ensuring they occur during maintenance windows to minimize service interruptions.

3. Audit-Logged Observability:
   Tensor9 provides secure, audit-logged monitoring and telemetry, allowing vendors to support their applications without direct access to sensitive customer data.

4. Resilient Deployments:
   Tensor9 supports high availability and failover configurations to ensure continuous service for critical banking operations.

Example Scenario: Fraud Detection Platform

A banking software vendor offers a fraud detection platform that uses machine learning to analyze real-time transaction data and identify suspicious activities.

Traditional SaaS Challenges:

• Banks cannot allow transaction data to be stored or processed in external cloud environments due to compliance restrictions.
• Centralized cloud infrastructure introduces risks of downtime during cloud outages, potentially delaying fraud detection.

Tensor9 Solution:

• The fraud detection platform is deployed directly within the bank’s environment, ensuring compliance and data security.
• The vendor can provide audit-logged support and performance monitoring without accessing sensitive data.
• The bank’s IT team can implement high availability and disaster recovery measures to maintain continuous fraud detection capabilities.

Why This Matters

In banking, secure and resilient solutions are essential for maintaining customer trust and meeting regulatory requirements. Tensor9 enables vendors to deliver secure, compliant platforms that empower banks to adopt innovative AI-driven solutions while keeping sensitive customer data protected and ensuring uninterrupted service.