Banking — AI, data & automation
Read regional-language handwritten forms and reduce repeated document-processing work.
A practical delivery view
Read the real document
An Indian banking engagement reads handwritten regional-language money-transfer forms, with high accuracy and near-zero failures reported since launch.
- Regional-language handwriting
- Form extraction
- Delivered banking engagement
Build the downstream flow
Extracted information still needs validation, exceptions and a clear next step in the bank’s workflow.
- Document validation
- Exception routing
- Application integration
Scope sensitive access
Banking workflows require explicit data-access and review boundaries. Security and regulatory requirements need client-specific assessment.
- Restricted data access
- Human review
- Project-specific governance
Where banking operations get stuck
Banks still receive a great deal of paper: mandates, transfer requests, account forms. Many arrive handwritten, and in India often in a regional language. Staff type the details into core systems, check them and chase the unclear ones. The work is repetitive, prone to error and grows with every new customer. Standard OCR struggles with handwriting and mixed scripts, so earlier automation attempts often stopped at printed documents.
- Paper mandates and transfer forms
- Handwriting in regional languages
- Manual keying and checking
- Earlier automation limited to printed text
What we delivered for an Indian bank
For an Indian bank, we automated the processing of physical mandates and other money-transfer forms. The system reads handwritten text in Indian regional languages. It has run with high accuracy and near-zero failures since launch. Those results belong to that engagement. The same pattern, AI to read the document and automation to carry out the steps that follow, applies to other paper-heavy banking work, with each case scoped on its own documents.
- Physical mandates and money-transfer forms
- Handwritten Indian regional languages
- High accuracy, near-zero failures since launch
- AI reading combined with automation
Start with one form type
Choose one high-volume document, gather a sample that includes the messy cases, and take it to a short call or process review. We look at the languages, the handwriting quality, the fields that matter and what happens after extraction. A pilot on your own samples shows how well the reading works on your documents before anything touches production. For a broader view of where AI fits in the bank, request the free AI readiness report.
- One document type, real samples
- Languages, fields and downstream steps
- Pilot before production
Questions that come up
Can AI read handwritten forms in Indian regional languages?
Yes, within limits that depend on the handwriting and the form. For an Indian bank, we built a system that reads handwritten regional-language text on mandates and money-transfer forms, with high accuracy and near-zero failures since launch.
What happens when the system cannot read a field?
It should not guess. Fields read with low confidence are routed to a person, who corrects and confirms them. Setting those thresholds and the review queue is part of the design, alongside validation against the bank’s own rules.
Does this replace our core banking system?
No. Document AI and RPA sit around your existing systems. They read the form, validate the details and carry out the data entry steps a person would otherwise do. Integration points are reviewed for each engagement.
How do you deal with security and regulatory requirements?
They are assessed with each bank. Data access, where processing happens, audit needs and review responsibilities are agreed before the build, around your privacy and compliance requirements. We do not offer a blanket compliance guarantee.
Let’s talk about your next step.
The workflow, the data and what needs to change.