AI Chatbot for Banking and Fintech

The chatbot authenticates the customer via OTP, biometric, or your existing session token before accessing any account data. Once authenticated, it pulls real-time balance and transaction history from your core banking API. Customers can ask questions in plain language -- "show me what I spent at Tesco last month" -- and the bot handles merchant name enrichment and natural language date parsing. It also provides statement download links and answers product-specific questions about account types, limits, and fees.

Before any query reaches an LLM, PII masking runs on the input using Microsoft Presidio or AWS Comprehend -- account numbers, card digits, and social security numbers are redacted so raw customer data never enters the language model context. The system is designed for PCI DSS compliance: sensitive data stays within the core banking API boundary and the chatbot layer handles only tokenised identifiers. A RAG pipeline backed by your product documentation, fee schedules, and regulatory FAQ knowledge base handles product queries -- the bot retrieves the precise answer from your authoritative content rather than generating it. This removes the majority of inbound support volume without touching a human agent, and leaves an audit trail for every query and response.

Customers who see an unrecognised transaction need to initiate a dispute quickly. The chatbot guides them through a structured dispute flow -- identifying the transaction, capturing the customer's statement, and creating a case in your CRM or dispute management system automatically. The dispute workflow is built as a LangGraph multi-turn flow: each node in the graph handles a specific data collection step -- transaction identification, merchant confirmation, customer statement, and evidence attachment -- with state persisted across turns so the customer can return to an incomplete dispute without starting over.

Plaid's balance and transaction APIs can be wired into the verification step where relevant, giving the bot real-time access to the flagged transaction's merchant name, amount, and timestamp to pre-populate the dispute form. Open dispute status is tracked and surfaced when the customer asks. FINRA and FCA disclosure requirements are embedded in bot responses for regulated complaint categories -- the bot includes the required language automatically based on complaint type. For complex cases -- chargebacks involving multiple parties, suspected first-party fraud, or complaints requiring regulatory escalation -- the bot hands off to a human agent via Twilio Flex or Genesys with the full conversation and transaction context attached. All conversation logs are retained in your compliance audit trail. No restarting from scratch on the agent side.

Customers mid-application have questions your branch staff currently handle by phone. The chatbot covers application status queries, outstanding document checklists, and document upload guidance without requiring a call. For loan products, it runs eligibility pre-screening questions -- income range, employment status, existing credit obligations -- before a customer invests time in a full application. The pre-screening logic follows UDAP consumer protection guidelines: no discouraging language based on protected characteristics and a clear path to the full application regardless of pre-screening outcome.

Before any account-level query, FIDO2 or WebAuthn step-up authentication confirms identity for sensitive operations. The bot calls your core banking API to retrieve the customer's current account standing and surfaces the most relevant product based on profile. Document upload guidance includes specific format requirements and quality checks before submission to reduce back-and-forth with underwriting. It books appointments with loan officers for customers who need a human conversation. For cross-sell, it surfaces relevant product comparisons based on the customer's account profile -- showing the right product at the moment the customer is already engaged, with RAG-powered answers drawn from your product term sheets and fee schedules rather than generated text.

When your fraud detection system flags a suspicious transaction, the chatbot sends a proactive outbound notification via the customer's registered channel and captures the customer's response. The customer confirms or denies the transaction in the chat. Identity is re-verified at this point using FIDO2 or WebAuthn step-up authentication before any account action is taken -- the bot will not freeze a card based on a message from an unverified session.

If the customer denies the transaction, the bot calls your card management API to trigger a temporary card freeze and immediately creates a structured case for your fraud operations team. The transaction data -- merchant name, amount, timestamp, and geolocation where available -- is attached to the case. PII in the conversation is masked before any LLM processing using Presidio, so the fraud context is handled without raw card numbers or account identifiers passing through the model. The full conversation log is retained in your compliance audit trail with a tamper-evident record of the denial and the freeze action timestamp. This replaces phone-based fraud alert calls and shortens the time between flag and card freeze from hours to minutes.

New customers going through KYC often abandon when they hit a confusing step. The chatbot guides them through the document upload process step by step, explains what each document needs to show, and tells them which documents are outstanding against their application checklist. The onboarding flow is a LangGraph multi-turn workflow with named states for each KYC step -- document type selection, capture guidance, upload confirmation, and liveness check instruction -- so the customer never loses their place.

When an ID verification check fails via Jumio, Onfido, or Alloy, the bot surfaces the specific rejection reason and tells the customer exactly what to resubmit. Common failure patterns -- low image quality, expired document, address mismatch -- are handled with specific remediation instructions rather than a generic error message. Customers with declined applications receive a clear escalation path to a human compliance review rather than a dead end. All KYC conversation data is retained in the compliance audit trail and linked to the customer's application record. This reduces KYC abandonment and cuts the volume of "where is my application" inbound queries your operations team handles manually, while keeping the process inside a HIPAA and PCI DSS compliant conversation layer.

Not every conversation should stay with the bot. Intent-based escalation rules determine when a conversation moves to a live agent -- regulatory complaints, vulnerable customer signals, complex disputes, or explicit customer requests. Escalation routes to your contact centre platform via Twilio Flex, Genesys Cloud, or Salesforce Service Cloud depending on your stack. The full conversation transcript, authentication event record, retrieved account data, and any actions taken by the bot transfer to the agent in structured format. The agent sees everything without needing to ask the customer to repeat themselves.

All conversations are logged with a complete audit trail: authentication timestamps, API calls made, data retrieved, responses given, and escalation events. This log satisfies FCA Consumer Duty oversight requirements, FINRA supervision requirements, and supports your compliance team's audit obligations. In agent-assist mode, the bot stays active during the human conversation and surfaces suggested responses based on the live conversation context -- drawing from the same RAG knowledge base used for automated responses. FINRA and FCA required disclosures are automatically appended to bot responses for regulated product categories, so the agent-assist suggestions include the correct regulatory language.