Financial Services

RPA & Screen Automation for Financial Services

RPA & Screen Automation for financial services, built around the constraint that defines the sector: every automated decision must be explainable and reproducible months after the fact.

Regulations in scope
5
Systems we integrate
5
Typical first release
6 weeks

What changes when it is financial services

Bots need orchestration as much as they need logic, queues, scheduling and retries are what make a fleet of them manageable.

In financial services, every automated decision must be explainable and reproducible months after the fact. 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 client communication review, usually integrated against SAP and Oracle financials. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

Deployed across regulated and unregulated sectors, with audit trails where the regulator expects them. Six weeks to something running in production, not six quarters to a strategy document.

The sector constraints we design around

Defining constraint
every automated decision must be explainable and reproducible months after the fact
Regulations in scope
RBI guidelines · SEBI regulations · DPDP Act 2023 · PMLA and AML rules · IRDAI where insurance applies
Systems of record
core banking · trading and OMS · loan origination · SAP and Oracle financials · regulatory reporting platforms
Where we usually start
credit memo drafting

RPA & Screen Automation workloads in financial services

  • credit memo drafting
  • KYC and onboarding checks
  • regulatory report assembly
  • reconciliation
  • client communication review

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

Can we use AI in credit decisions?

With explainability, documented model governance and human review on adverse outcomes, yes. RBI expects you to be able to explain any decision that affects a customer.

How do you handle data residency?

Deployment inside Indian regions or on your own infrastructure, which is the usual requirement for regulated financial data.

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.

RPA & Screen Automation for financial services, 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