Payments Dispute
AI Agent
From intake to decision in 30 minutes. End-to-end. 24/7. Compliant
Trask Payments Dispute Agent helps banks resolve payment card disputes quickly, accurately, and in line with card scheme requirements. It automates the full dispute lifecycle end to end, from customer claim to final decision, so teams can process growing volumes without adding operational load. The agent supports 24/7 processing and helps banks meet regulatory deadlines with a consistent, compliant workflow, keeping every decision fully documented and auditable.
The result: lower operational costs, fewer erroneous payouts, and faster resolution for customers.
Proven in practice on thetrask.com.
The agent ingests and understands every page of your website – from product specifications and blog posts to help center articles. It utilizes vector databases to retrieve information based on semantic meaning, ensuring users get accurate answers drawn from the source of truth.
Powered by advanced Large Language Models (LLMs), the agent engages visitors in natural dialogue. It understands context, nuance, and intent, handling complex follow-up questions while maintaining a polite, brand-aligned tone.
The solution is designed for quick deployment. You can launch an out-of-the-box version with core AI engines and basic training rapidly, or opt for a fully customized deployment fine-tuned on your domain-specific data.
Security is paramount in regulated industries. The agent is configured to respect privacy guidelines, with options for private cloud or on-premises deployment. It ensures no sensitive internal data is divulged, offering transparency without the "black box" risk.
Serve a global audience effortlessly. The agent automatically detects and interacts in multiple languages, including English, Czech, and Slovak. Its architecture supports extension to other channels, such as mobile apps or internal support systems.
The system doesn't just answer; it learns. Through feedback loops during testing phase and analytics dashboards, the agent improves over time, providing you with data-driven insights into what your visitors are truly seeking.
The agent is built on retrieval-augmented generation (RAG). It uses vector databases to retrieve information by semantic meaning, so answers are drawn directly from your content, not from general training data. Automatic language detection enables the agent to respond in the visitor’s language without separate localization effort. If no relevant passage is found, the agent declines to answer.
Helps back-office teams process client requests faster. Classifies inputs, validates information and supports consistent decisions under pressure.
Finds answers across your enterprise knowledge sources. Delivers clear responses with exact source links in seconds.
Explains risk metric movements and turns model outputs into executive-ready insights. Reduces reporting work and improves commentary consistency.
Monitors regulatory changes, identifies relevant updates and helps teams prioritize what needs action. Reduces manual tracking and the risk of missed obligations.
We’ll test the agent on your own website content and show how it can answer visitor questions in a 4-week PoC.
