Kyc aml · Production

Banorte cuts document validation time 60% with SS&C Blue Prism AI, ML and NLP automation

The problem

Banorte employees manually validated documents for payroll loan and credit card requests at high volume, with each analyst receiving up to 100 new requests per 1–1.5 hours, making it difficult to meet SLAs and respond to customers promptly.

Workflow diagram · grounded in source

Employee submits request notification

trigger

“when an employee receives a request for a new payroll loan, an instant-use credit card or payroll improvement, they notify an SS&C Blue Prism AI agent”

AI agent validates customer data

validation

“who validates the customer data via an internal banking application”

Documentation downloaded and uploaded

integration

“the AI agent downloads key documentation — like official identification and proof of address — and uploads it to Banorte's internal AI engine”

AI engine processes documents

ai_action

“The AI engine identifies the documents, interprets text and images, extracts the required data and sends it back to the SS&C Blue Prism AI agent”

Multi-system data aggregation

integration

“The AI agent uses this data, along with information from three other systems”

Checklist creation and approval

output

“to create a checklist and approve the customer's request”

Reported outcome

Document validation time dropped 60% from 20 minutes to eight minutes per request, returning 2,000 hours per month to the business.
Processing capacity grew 30% year over year without additional headcount, and automatic approval rates rose from 70% in 2022 to 91% in 2024.

Reported metrics

Document validation time reduction60%

Document validation time before automation20 minutes

Document validation time after automationeight minutes

Hours returned to business per month2,000 hours (250 days)

Show all 9 reported metrics

document validation time reduction60%

document validation time before automation20 minutes

document validation time after automationeight minutes

hours returned to business per month2,000 hours (250 days)

processing capacity increase year over year30%

automatic approval rate 202270%

automatic approval rate 202491%

analyst manual request volume (pre-automation)100 new requests in 1 to 1.5 hours

market adaptation turnaround timeless than 24 hours

Reported stack

SS&C Blue PrismAIMLNLPMicrosoft Azure

Source

https://www.blueprism.com/resources/case-studies/banorte-automation-ai-document-processing/

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Document validation time dropped 60% from 20 minutes to eight minutes per request, returning 2,000 hours per month to the business.

What tools did this team use?

SS&C Blue Prism, AI, ML, NLP, Microsoft Azure.

What results were reported?

Document validation time reduction: 60%; Document validation time before automation: 20 minutes; Document validation time after automation: eight minutes; Hours returned to business per month: 2,000 hours (250 days) (source-reported, not independently verified).

How is this kyc aml AI workflow structured?

Employee submits request notification → AI agent validates customer data → Documentation downloaded and uploaded → AI engine processes documents → Multi-system data aggregation → Checklist creation and approval.

Document validation time dropped 60% from 20 minutes to eight minutes per request, returning 2,000 hours per month to the business.Processing capacity grew 30% year over year without additional headcount, and automatic approval rates rose from 70% in 2022 to 91% in 2024.