Banking
RPA & Screen Automation for Banking
RPA & Screen Automation 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
Orqent Labs builds RPA for the systems that will never get an API, and recommends against it everywhere else.
In banking, core banking systems are not to be touched, so everything integrates around them. That single fact reshapes how rpa & screen automation 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 account opening documentation, usually integrated against loan management systems. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.
Built by engineers who ship production systems, not by a practice that subcontracts the build. Six weeks to something running in production, not six quarters to a strategy document.
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
RPA & Screen Automation workloads in banking
- account opening documentation
- AML alert triage
- customer service automation
- loan file assembly
- branch reporting
What is included
- Process selection scored on stability and volume
- Bots with AI-assisted element detection for resilience
- Exception handling and human escalation
- Orchestration, scheduling and queue management
- Monitoring with alerts on failure
- Maintenance plan for when applications change
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.
Is RPA obsolete now that we have AI agents?
No, but its scope has narrowed. RPA is right where there is no API and the interface is stable. Everywhere else, integration or agentic automation is more durable.
Why did our last RPA project fail?
Usually one of two reasons, the process changed faster than the bot could be maintained, or a process was automated that should have been fixed first.
Which platform do you use?
UiPath, Automation Anywhere or Power Automate, and sometimes a lighter custom approach when licence cost outweighs the benefit.
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
- Voice AI Agents for Banking
- Document Processing & IDP for Banking
- AI Copilot Development for Banking
- Predictive Analytics & Forecasting for Banking
- Data Engineering for Banking
RPA & Screen Automation 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