Banking
Voice AI Agents for Banking
Voice AI Agents for banking, built around the constraint that defines the sector: core banking systems are not to be touched, so everything integrates around them.
- Regulations in scope
- 4
- Systems we integrate
- 5
- Typical first release
- 6 weeks
What changes when it is banking
Indian-language speech is not a solved problem at the accent and code-mixing level. We test against recordings of your actual callers rather than clean studio audio.
In banking, core banking systems are not to be touched, so everything integrates around them. That single fact reshapes how voice ai agents has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.
The workload we are most often asked to take on first is AML alert triage, usually integrated against Finacle. We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.
Multi-model by default, so a provider outage is a routing decision rather than an incident. You own the code, the models where they are open-weight, and the documentation to run it without us.
The sector constraints we design around
- Defining constraint
- core banking systems are not to be touched, so everything integrates around them
- Regulations in scope
- RBI master directions · PMLA and AML · DPDP Act 2023 · cybersecurity framework for banks
- Systems of record
- Finacle · Flexcube · core banking platforms · CRM · loan management systems
- Where we usually start
- account opening documentation
Voice AI Agents workloads in banking
- account opening documentation
- AML alert triage
- customer service automation
- loan file assembly
- branch reporting
What is included
- Telephony integration with your existing numbers
- Indian-language speech recognition and synthesis
- Sub-second turn latency with barge-in support
- Live transfer to a human with context
- Call recording, transcription and QA scoring
- Compliance with calling and consent regulations
Questions from this sector
Will this touch our core banking system?
No. We integrate through supported interfaces and read replicas, never by modifying the core.
How do you handle AML false positives?
Context enrichment and tuned scoring so alert volume matches investigator capacity, with every decision explainable in a case file.
Which Indian languages are supported?
Hindi, Tamil, Telugu, Kannada, Malayalam, Marathi, Bengali, Gujarati and Punjabi among others, including code-mixed English. We test on recordings of your real callers, not studio audio.
How fast does it respond?
We target sub-second turn latency end to end, with barge-in so callers can interrupt naturally. Anything slower and callers assume the call has dropped.
Can it transfer to a human?
Yes, warm transfer with the transcript and caller context handed over, so the agent does not ask the customer to repeat themselves.
Other capabilities for banking
- AI Agent Development for Banking
- Agentic Workflow Automation for Banking
- LLM Application Development for Banking
- RAG & Knowledge Retrieval for Banking
- Chatbot Development for Banking
- Document Processing & IDP for Banking
- AI Copilot Development for Banking
- Predictive Analytics & Forecasting for Banking
- Data Engineering for Banking
- Enterprise AI Platform for Banking
Voice AI Agents for banking, worth a conversation?
Tell us the workload and the regulation it sits under. We will tell you what is realistic.
Or email bd@dtrasglobal.com · call +91 74118 77878
