Intake & Extraction
AI Document Validation
Checks documents for completeness and consistency against rules.
Intake & Extraction
AI Document Extraction for Financial Services
Client onboarding paperwork read into structured fields, checked against your rules, and only reviewed data written to the client record.
Onboarding a client means reading application forms, bank statements and proof-of-address documents, then typing the same details into your CRM. This build extracts the fields you define with a confidence score on each, checks them against your rules, such as statement age, and holds anything doubtful for a reviewer. It never approves a client. Your qualified staff make every decision.
- Client documents read into scored, structured fields
- Rule failures held for review before the client record changes
- Statements from different banks handled under one document type
$5,400
20–30 working days
Optional maintenance $270/mo
What it is
AI Document Extraction for Financial Services reads the documents clients send during onboarding and service requests, such as application forms, statements and proof-of-address documents, and extracts the fields you define with a confidence score on each. Rule failures and doubtful fields go to a reviewer before your CRM is updated.
Why businesses buy it
In financial services, slow onboarding loses clients and careless onboarding creates compliance problems. Staff who should be talking to clients spend hours keying forms, and a single mistyped account number can surface months later in a complaint or audit. This build takes over the reading and checking, and puts only the doubtful values in front of your team, with the failed rule shown. The written scope fixes the document types, fields, rules and systems before you buy, so the decision is easy to defend.
Problems this solves
Client onboarding stalls while staff key details from application forms
The system reads application forms sent during onboarding and extracts the fields you define, each with a confidence score. Checked data updates your CRM without a second round of typing.
Out-of-date or mismatched proof-of-address documents slip through
Financial services validation rules check details such as document dates and name matches. Any rule failure goes to a reviewer before your CRM record changes.
Statement figures are copied by hand into client records
Statements are one of up to three document types set up, with up to twenty-five fields each. Doubtful values are held for review, so only checked figures reach the record.
A good fit if
Client onboarding stalls while someone retypes names, addresses and account details from uploaded documents.
Your operations are rule-bound, and a wrong figure in a client record costs more to fix than to check.
Documents arrive through one inbox or a folder fed by your client portal, in up to three main types.
You want every uncertain field reviewed by a named person, with a record of what was corrected.
Not the right fit if
You need clients guided through onboarding and chased when they stall. See AI Customer Onboarding Agent for Financial Services.
You need completeness and consistency checks across a whole document pack as a separate quality step. See AI Document Validation.
The paperwork is supplier invoices for your own accounts team. See AI Invoice Intelligence.
Your bottleneck is answering client questions, not processing their documents. See AI Customer Support Agent for Financial Services.
How it works
- Client documents arrive through one route. Uploads from your portal, or attachments sent to a dedicated inbox, are collected in the intake route you choose.
- Fields are read from the content. Name, address, dates, account references and the other fields you define are extracted wherever they sit on the page, up to 25 per document type.
- Every field carries a confidence score. You can see which values the model is sure of and which it is not, field by field, rather than trusting a whole document at once.
- Your rules are applied before anything is saved. A document dated outside the window your policy allows, or a name that does not match the application, is held as an exception.
- Reviewed data reaches the client record. Clean, high-confidence fields are written to your CRM or document management system; everything else waits for your reviewer.
- Nothing is decided for you. The build extracts and checks data; approving a client, assessing suitability or giving advice stays entirely with your qualified staff.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- At least 20 real samples of each document type, redacted where you need to.
- The fields to extract from each type, and the validation rules each must pass, such as acceptable document age.
- Access to the intake inbox or the folder your client portal feeds.
- Access to the destination: your CRM or document management system.
- The reviewer for low-confidence fields and rule failures.
- Admin access and API keys for both systems, never sent by email.
- One decision-maker who approves the field list and the launch.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake verified, sample documents, field list and rules confirmed.
Weeks 1–2
Extraction and validation rules built from the Financial Services template.
Week 3
Intake route and CRM or document system connected, review queue set up.
Weeks 3–4
100 sample documents processed, field-level accuracy report delivered.
Week 4
Your review and two rounds of changes.
Go-live
Live on client documents, recorded handoff, support begins.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $5,400 |
| Express | 15–25 working days | $6,200 |
| Rush | 10–20 working days | $7,000 |
What you receive at handover
- AI Document Extraction for Financial Services configured on one intake route and connected to your CRM or other agreed system
- Financial services field sets and validation rules for up to three document types, such as application forms, statements and proof of address
- A human review queue for rule failures and low-confidence fields
- A test report using financial services scenarios, from 100 sample documents with an accuracy report
- An admin guide and a recorded 60-minute handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can help new clients get set up sooner after sending their documents.
- Helps catch document problems before a file reaches a compliance check.
- Makes it easier to show which checks each document passed.
- Onboarding time from documents received to CRM complete
- Compare timestamps in your CRM for a month before launch and a month after.
- Files returned for rework at compliance check
- Count returned files each month from your compliance log, before and after launch.
- Rule failures caught in review
- Count review-queue items by rule each month to see which document problems are most common.
Before you start: Record how long onboarding takes from first documents to a complete CRM record. Note how many files compliance sent back last quarter.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build is paid once. Running costs are roughly $30 to $200 a month in your own accounts for OCR and AI usage plus storage, depending on how many pages your clients send. Busy onboarding periods sit higher in that range.
AI usage during build and testing is billed to your own accounts too, so document data and provider contracts stay under your control.
Ask about running costsCustom requirements
A fourth document type, more than 25 fields per type, a second intake route, or matching extracted data against a third system is outside the Scope Card. Add a note at checkout for a written Change Quote.
Request a custom versionKeep it running
Monthly maintenance covers monitoring, fixes, updates, a health report and change hours each month, enough for a new form version, a changed validation rule or an added field. It starts after the 30 days of support.
$270/mo (5% of the build price a month, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A document capture platform often bills per document with a minimum commitment | A custom build is quoted after discovery | Ours is one fixed price, shown on this page before you buy |
| Uncertain fields | Often accepted unless someone spot-checks | Depends on what was agreed | Ours scores every field and queues doubtful ones for review |
| Your rules | Configured by your team inside the tool | Depends on the brief | Ours applies the validation rules you specify before saving |
| Delivery | Quick sign-up, then weeks of setup | Usually several weeks | Ours has a fixed delivery time shown before you buy, with faster options |
Questions about this product
Does AI Document Extraction for Financial Services make onboarding decisions?
No. It extracts fields, scores them and checks them against your rules, but approving a client, assessing suitability or giving financial advice is excluded and stays with your qualified staff. The build's job is to get accurate data in front of those people faster, with doubtful values clearly marked.
Which client documents can it read?
Up to three document types you choose, often an application form, a bank statement and a proof-of-address document. Each type can have up to 25 fields. Extraction reads content rather than fixed positions, so statements from different banks usually work under one document type without a template for each.
How is sensitive client data protected during extraction?
Data moves only between the intake route and the destination you connect, both in your own accounts. You can leave sensitive fields off the field list and redact samples before we see them. For stricter handling, the PII Redaction Layer, $2,500, and Data Retention and Deletion Configuration, $1,500, are add-ons bought with this product.
What happens when a document fails one of our rules?
It is held as an exception in the review queue with the failed rule shown, for example a statement older than your accepted window. Your reviewer decides whether to accept, correct or request a new document. Only after that does anything reach the client record, so failures never slip in unnoticed.
How quickly can the financial services build go live?
Go-live depends on the delivery speed you choose, shown in the panel on this page, and the clock starts once intake is complete and access is verified. Your 20 samples per document type, field list and validation rules are due within 72 hours of ordering. Redacted client samples are fine. Each day late moves delivery back by 3 working days.
What does it cost to run for a busy onboarding team?
Roughly $30 to $200 a month in your own accounts for OCR and AI usage plus storage, rising with the number of pages processed. There is no per-client or per-document fee from us. Monthly maintenance is optional and covers form and rule changes.
Get client paperwork into your systems accurately, the first time.
Order AI Document Extraction for Financial Services.
Works well with
Lifecycle
AI Customer Onboarding Agent
Guides new customers through setup milestones and nudges when they stall.