Client Overview
The client is a regional retail bank in the US Northeast serving around 400,000 customers with approximately $6 billion in assets. With 900 employees, 45 branches, and a 24-hour contact center, the bank offers personal and business banking services through branches, online banking, and mobile channels. Rising call volumes made phone support especially important for urgent needs such as card blocks, payment issues, and suspected fraud. They needed voice AI in their banking solutions to automate routine calls, strengthen fraud protection, maintain compliance, and improve their voice assistant capabilities while keeping customer interactions natural.
Project Summary: The client needed to cut hold times and call-center costs, speed up identity verification, and address fraud risks such as social engineering and spoofed caller IDs. We developed a voice AI solution for their banking operations. The software helped combine speech recognition, natural language processing, and large language models with approved bank policies and product information. It connects with the core banking system, CRM, and fraud tools to enable intelligent banking automation, while voice biometrics, controlled responses, and human escalation strengthen security. It handles customer calls 24/7, verifies identities, and completes routine requests. It also flags suspicious activity and generates required documents, with human agents stepping in when cases need additional attention.
Project Challenges
The client’s first challenge was the growing number of calls for simple requests such as account balances, recent transactions, card status, payment due dates, and branch hours. Customers often waited on hold for basic information, especially during busy hours, while the touch-tone menu sometimes routed them to the wrong department. This left agents with less time to handle complex issues and created a need for intelligent banking automation that could work with the bank’s existing systems. The bank therefore needed to introduce automation without replacing its core infrastructure, making AI legacy system integration an important part of the approach.
Security was another concern. The bank relied on security questions that could be guessed or stolen, while spoofed caller IDs, account takeover attempts, and synthetic voice scams were becoming more common. The client needed an AI voice agent for financial services that could verify each caller’s identity and detect suspicious behavior before providing access to sensitive account information.
They also needed a reliable voice AI for their banking solutions that could understand different accents and noisy calls, provide accurate answers without guessing, and follow approved policies for fees, rates, and account rules. It also had to generate documents correctly and maintain complete call records to meet GLBA, FFIEC, and CFPB expectations. The goal was to introduce voice assistant banking capabilities that improved customer service without compromising security, accuracy, or customer trust.
Solutions
To handle the call volume, we built an agentic voice AI assistant that answers calls through natural conversation instead of menu options. The platform uses speech recognition, NLP, and conversational AI to understand caller needs, complete requests, and confirm results. It handles balance and transaction questions, card freezes, payment scheduling, and branch information. We tuned latency for real-time conversations, allowing callers to experience short pauses and interrupt the assistant naturally.
To secure every call, we added voice biometrics and caller ID forensics at the start of the conversation. The system compares the caller’s voice against an enrolled voiceprint, checks signals such as number spoofing and call-routing anomalies, and scores risk before sharing any account details. Each call also runs through liveness and deepfake detection, helping flag cloned or synthetic voices before the voiceprint match is trusted. Fraud detection workflows run during the call, with suspicious patterns triggering step-up verification or a transfer to a fraud specialist, along with a summary explaining why the call was flagged.
To keep answers accurate, we built a grounded answering approach. The assistant responds only using approved bank content and live system data, declines requests outside its knowledge, and hands off to a human agent with the full conversation context. Letters are generated from approved templates using verified data from the core banking system and sent only after the caller has been verified. The platform runs on Google Cloud in US regions with encryption and role-based access, while an operations dashboard tracks call outcomes, accuracy, containment, and fraud flags. Our team worked as the client’s extended engineering partner for eight months, from discovery and pilot to full rollout, using an approach aligned with AI agent development expertise.
Technologies and Tools Used
Results
Within six months of launch, the voice AI used for financial services transformed how the bank handles customer calls. Routine requests are resolved quickly, fraud checks begin at the start of each call, and agents can focus on complex or sensitive cases that require human attention.
Key Outcomes
- 62% of inbound calls fully resolved by the voice agent
- 70% reduction in average hold time
- 48% reduction in call abandonment
- 34% reduction in average handle time
- Identity verification time reduced from 90 seconds to under 15 seconds using voice biometrics
- 41% increase in account takeover attempts detected
- 38% reduction in contact center cost per call
- Official documents delivered in under 2 minutes
- 21-point improvement in customer satisfaction (CSAT)
- Zero policy or fee misstatements recorded in sampled compliance reviews
- 100% of calls transcribed and logged for compliance review
- GLBA, FFIEC, and CFPB requirements supported through documented call records
Words of Appreciation
“The WPWeb Infotech team made it much easier for us to improve our phone support. They understood our banking needs, helped us make calls faster and safer, and ensured customers could get help without long wait times. We were satisfied with how smoothly the system worked with our existing processes while keeping security and compliance in focus.”
Future Scalability
As the bank scales its services, our team remains committed to providing continuous support. We will support voice AI in banking through speech model tuning, accuracy and fraud performance monitoring, and updates as product requirements evolve. The platform’s flexible, modular design lets us add new features without changing or rebuilding what already works. These may include payment reminder calls, loan application assistants, fraud alerts, multilingual support, and chat and mobile integrations. We will also help scale the infrastructure to handle higher call volumes and refine the assistant using real call data. As AI requirements grow, they can also hire AI developers to extend the platform and add new capabilities, helping improve consumer experience and operational efficiency.
