CHALLENGE
As AI became central to the bank's customer operations, new vulnerabilities began to emerge. AI-powered systems were processing sensitive financial requests at scale, but without sufficient governance and oversight in place.
Three critical risks had surfaced:
Prompt injection attacks — Malicious inputs could compromise the system and expose sensitive customer data, creating serious security and reputational risk.
Biased AI decisions — The AI model handling chargeback requests was rejecting a high volume of disputes, with subtle nuances that are hard for LLMs to decipher. Under emerging regulation, banks must be able to provide a multi-month history of AI decisions to check for bias and black-box issues.
Compliance gaps — Leadership lacked an automated mechanism to generate regulatory reports or give boards and regulators actionable visibility into AI-driven operations.
Left unaddressed, these issues risked regulatory penalties, erosion of customer trust, and significant financial liability.
PROCESS
01
Customer submits a chargeback request
The customer raises a dispute through the bank's mobile app. The request is routed to the bank's employee portal for review.
02
AI generates a case summary
A bank employee opens the request and sees an AI-generated summary containing all key details. Reason code for card network, transaction history, dispute reason, customer profile, history and recommended action approve or deny chargeback.
03
Disseqt AI evaluates the summary in real time
Before the employee acts, disseqt automatically evaluates the Copilot output for accuracy, bias, and consistency. A confidence score is generated for each response in milliseconds and at each step in the triage process, LLM drift is closely monitored for every chargeback.
04
Human-in-the-loop escalation when needed
If the response fails disseqt’s evaluation driven by multiple validators , the employee is immediately alerted to review manually. A detailed root cause analysis explains exactly why the evaluation failed, enabling faster, more informed decisions by employees.
05
Compliance reports generated automatically
Compliance managers can generate regulatory reports on demand, while board members receive clear, real-time insights to support strategic decision-making.
OUTCOMES
Safer, fairer, faster, and fully auditable AI operations
Bias eliminated from chargeback decisions — no customer is unfairly denied.
Prompt injection threats neutralised through an additional assurance layer.
Regulatory compliance automated, with detailed decision trails available for audit.
Board-level AI visibility, with real-time insights backed by live performance data.
Continuous model drift monitoring, with remedial action triggered when issues arise.
This is the gap disseqt fills. In 2026, chargebacks are projected to reach $337 Billion, with fraud losses expected to hit $28 billion. Every basis point of improvement in AI governance at the triage stage above translates directly to hundreds of millions in recovered value for a bank.
"With disseqt in place, our team can resolve disputes confidently, knowing every AI decision has been evaluated for accuracy and fairness before it reaches our customers."
-Senior Operations Lead, Leading European Bank
