EveryBooks / Industries / Financial institutions / Document intake and validation
Financial institutions
Document intake and validation
Incoming documents are read, the fields that matter are extracted and checked against your own systems, and only genuine exceptions reach an analyst.
Who this is for. Head of operations, operations manager, or the transformation lead who owns a document-heavy process.
The problem today
Documents arrive in every format a customer can produce: scans, photographs, spreadsheets, forms completed by hand. Someone reads each one, types the fields into a system that already holds most of the answer, and checks the parts that disagree.
The volume makes it a headcount question and the error rate makes it a risk question. Re-keying introduces mistakes that are only caught later, and the capacity needed scales directly with volume, so a good quarter for the business is a bad quarter for operations.
What we deliver
Extraction that handles the documents you actually receive
Built against your real intake, including the poor scans and the formats a customer invented, rather than against a clean sample.
Validation against your own systems
Extracted values are checked against what you already hold, so a mismatch is surfaced at intake instead of discovered downstream.
Confidence that is visible
Each extracted field carries how certain the agent is. Fields below the threshold you set are shown to a person rather than written through silently.
Exceptions routed with context
The analyst sees the document, the extracted value, the conflicting value and the reason it was flagged, side by side. Resolution takes a moment rather than an investigation.
A full trail per document
What arrived, what was read, what was proposed, who decided and when. Exportable for an examination without reconstruction.
Deployment inside your perimeter
The agents run in your cloud tenancy against your systems. Customer documents do not leave your control.
What agents do, and what your team approves
What the agents do
Agents classify the document, extract the fields, validate them against your systems, score their own confidence and prepare the exception for review.
What they never do
A named analyst approves anything the agent is not certain about, and anything that conflicts with your records. The agent never overwrites a system of record value on its own judgment.
Systems we work with
- ServiceNow
- Salesforce
- AWS
- Excel
From past work
What we have built
We have built document validation agents that run inside an institution's own systems and cloud, with operations staff approving every exception and a per document audit trail available for examination.
Questions we get
Does our data leave our environment?
No. The agents are deployed into your own cloud tenancy and work against your own systems. This is usually the question that decides whether a project can happen at all, so we design for it from the start rather than arguing about it later.
What accuracy should we expect?
It depends entirely on your document mix, and anyone quoting you a number before seeing your documents is guessing. We measure against a sample of your real intake and report what we actually get, including the document types where we would not recommend automation.
How does this survive an audit or examination?
Because every field carries its source document, its confidence and the person who approved it. The trail is a by-product of the process rather than something assembled afterwards.
Can we start with one document type?
Yes, and we recommend it. One high-volume document type proves the control model and the accuracy on your own data before you commit to the rest.
Related
- Fee reconciliationFee income is checked against the agreement every period, not sampled.
- Onboarding and know your business checksOnboarding checks are prepared in full so the analyst decides faster.
- SOX and audit readinessControls and evidence stay ready all year.
- All Financial institutions workOperations teams re-key documents and check fees by hand because the alternatives all involved sending data somewhere else.
- How we workRead the books, design for agents, ship them, train your operators, then run and improve.