Understanding your business needs, one solution at a time.
A mid-sized NBFC in the UK handling high volumes of digital payment and card transactions relied on a rule-based fraud detection system to meet regulatory and risk requirements.
Through discovery workshops with the client’s fraud, risk, and compliance teams, we identified three key requirements:
Research. Understood. Proposed.
We proposed an AI agent that works alongside the client’s existing fraud detection system. As soon as an alert is generated, the AI reviews it instantly, around the clock, just like an experienced fraud analyst would.
Instead of making analysts gather information from different systems, the AI automatically collects everything they need, such as transaction history, device and location details, merchant risk, and customer behavior, and brings it together into one clear view.
Using the client’s fraud policies and past fraud cases, the AI recommends whether an alert should be closed, sent for manual review, or escalated as high risk. It also explains why it made that recommendation in simple, audit-friendly language. For uncertain cases, the final decision always stays with the human analyst.
Our team analyzed the client’s end-to-end fraud investigation workflow, identifying manual touchpoints, data silos, and bottlenecks across the fraud engine, core banking, CRM, transaction logs, and card network systems.
We reviewed historical fraud alerts with the client’s risk and compliance teams to define AI decision criteria, confidence thresholds, and validation rules while ensuring zero tolerance for auto-closing genuine fraud cases.
Using an agile approach, we built the AI-powered triage engine, automated data enrichment layer, and audit framework, integrating seamlessly with the client’s existing fraud ecosystem.
The solution was validated against historical data before running in shadow mode alongside live operations, allowing analysts to verify recommendations and fine-tune the AI without impacting production.
The AI agent was rolled out incrementally, starting with low-risk alert categories. Automation expanded as accuracy targets were consistently achieved, with full auditability and compliance controls in place throughout.
From nothing to a star!
A 24/7 AI agent that picks up every alert instantly and classifies it as auto-close, human review, or high-risk escalation.
Real-time API integration across core banking, CRM, transaction logs, and the card network portal, one connected case view per alert.
LLM reasoning with RAG over the client's fraud policies and historical dispositions, with confidence-threshold guardrails.
Every alert routed to a human arrives with a complete case summary attached. Cutting review time from [15–20 minutes] to [under 4].
Every automated decision is logged with a plain-language justification, satisfying internal audits and regulatory reviews.
Analyst decisions feed back into the system, improving triage accuracy month over month.
The measurable impact delivered after deployment.
“I have used Zealous for several of my projects, I have found the team to be very professional yet personable. When I work with Zealous, I know I am getting the best developers who understand my requirements before they start.”
Sales Director at Digital Dilemma
“From day-1 Pranjal and his team have been very good at delivering quality work on time to budget. They are dynamic, if resources need to be shuffled around depending on what work needs to be done.”
Senior Product Manager at Ecentric Payment Systems Driving
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