document ai

4.8/5  (30+ reviews)

Turn every borrower file into decision-ready data

Extract and cross-check payslips, bank statements, tax returns and IDs in real time. One API for lenders, brokers and credit software to complete files at upload, verify income across documents and feed clean data to underwriting and scoring.

Trusted by top-tier teams worldwide

v2-Carlabella
v2-Spendesk
v2 Payfit
v2 Lucca
v2 Circula
v2-Carlabella
v2-Spendesk
v2 Payfit
v2 Lucca
v2 Circula

Every incomplete file is a borrower you might lose

Three payslips, three months of statements, two tax returns, an ID: one missing page or one figure that doesn’t add up, and the file goes back to the borrower. Meanwhile, analysts retype income and debts by hand, and a faster lender makes the offer.

1

Application

The borrower applies directly or through a broker

2

Upload documents

Friction

Missing payslip or outdated statement: a new upload is requested by email.

3

Manual review

Friction

Files wait in the underwriting queue, figures retyped by hand.

4

Mismatch

Cross-checks

Friction

Income on the payslip ≠ salary on the bank statement. Back to step 02.

5

Loan approved

If the borrower hasn’t signed elsewhere

RESULT

Incomplete files sent back and forth, analyst time spent on data entry instead of credit decisions, and borrowers lost to faster lenders.

See how Mindee fixes it

Every document in a borrower file, read in one flow

Mindee recognises each document automatically and extracts the fields you need, ready to be checked against each other.

Auto-classify documents

ID card

  • Surname
  • Given names
  • Date of birth
  • Document number
  • Expiry date
  • Nationality
  • Sex
  • Place of birth
  • Issuing country
  • Issue date
  • Issuing authority
  • Address
  • Personal number
  • MRZ lines
  • Photo
  • Signature

Passport

  • Surname
  • Given names
  • Date of birth
  • Passport number
  • Expiry date
  • Nationality
  • Sex
  • Place of birth
  • Issuing country
  • Issue date
  • Passport type
  • MRZ line 1
  • MRZ line 2
  • Photo

Pay stub

  • Employee name
  • Employer name
  • Pay period start
  • Pay period end
  • Gross salary
  • Net pay
  • Job title
  • Contract type
  • Employer address
  • Employer registration number
  • Employee address
  • Employee ID
  • Social security number
  • Employment start date
  • Pay date
  • Net before tax
  • Income tax withheld
  • Year-to-date gross
  • Hours worked
  • Salary details (base, overtime, bonuses)

Bank statement

  • Account holder name
  • IBAN
  • Bank name
  • Period start
  • Period end
  • Opening balance
  • Closing balance
  • Transactions (date, description, amount)
  • Account holder address
  • Bank address
  • Account number
  • BIC / SWIFT
  • Statement date
  • Total credits
  • Total debits
  • Currency

Tax return

  • Taxpayer names
  • Tax year
  • Reference tax income
  • Total tax due
  • Tax ID / fiscal number
  • Notice reference
  • Address
  • Filing status / household
  • Number of tax shares
  • Gross income
  • Taxable income
  • Withholding & payments
  • Refund or balance due
  • Issue date

Mortgage

  • Borrower names
  • Lender name
  • Loan amount
  • Interest rate
  • Loan term
  • Monthly payment
  • Property address
  • Co-borrower
  • Rate type (fixed / variable)
  • APR
  • Start date
  • First payment date
  • Maturity date
  • Insurance cost
  • Fees
  • Total cost of credit
  • Loan reference
  • Signature date

Proof of address

  • Holder name
  • Full address
  • Issue date
  • Document type (energy bill, tax notice, …)
  • Issuer name
  • Street
  • Postal code
  • City
  • Country
  • Period covered
  • Reference / account number

Collect

Loan application or broker file with documents

Mindee Classify

ID, payslips, bank statements, tax return

Mindee Extract

Employer, net income, salary credits, debts…

VERIFY

{Your business rules to check}

Cross-check

Valid data is automated

Decision-ready data sent to underwriting

Exceptions to human

Flag for human review

Prototype in minutes, go live with the API

Test the full document flow with a no-code scenario first. When the results convince your team, plug the same models into your platform.

What changes for each team

Engineering, finance and product don't look for the same thing in document-based projects. Here is what each of them gets.

3 teams · 1 platform

Technical

· CTOs, Lead devs

A fast, documented API, live in days, with no extra tech debt

Robust infrastructure and features that scale.

Low effort : up-to-date docs and SDKs

No production surprises : continuous monitoring and drift protection

finance & ops

· CEOs, CFOs, COOs

Process more loan files per analyst, with time spent on credit decisions, not data entry

Lower costs, stronger compliance, better margin

Change management eased by no-code templates

Data protected : SOC 2 Type II infrastructure, GDPR compliant

product

· CEOs, Product managers

Complete loan files at upload, so borrowers never get the “missing document” email

  • Missing or outdated documents flagged before the borrower leaves
  • Income and debts structured for your scoring rules
  • Doubtful files routed to an analyst, never a dead end

Results measured by customers, in average

Teams that process loan files with Mindee spend less time checking documents and approve loans faster. Here’s what changes once document checks run on autopilot: less manual review, more loan files handled by the same team, and a fast path from first test to production.

-68

%

less time spent on document checks

TIME PER FILE - Before/After Mindee

5

k

documents processed every month

Volume - last 6 months

2 weeks

from first API call to production

Test - integrate - live

FAQ about this use case

Can't find what you're looking for? Our team answers within one business day.

About Mindee

How do lenders calculate the debt-to-income ratio?

The debt-to-income (DTI) ratio is a borrower’s total monthly debt payments divided by their gross monthly income, expressed as a percentage. For example, $2,000 in monthly debt payments with $6,000 in gross monthly income gives a DTI of 33%. Many lenders look for 36% or less, though the maximum depends on the loan type and program. To calculate it, lenders need reliable figures from several documents: gross income from payslips, and existing debt payments from bank statements and mortgage statements. Mindee extracts these figures automatically, so analysts can calculate the DTI without retyping any data.

What counts as proof of income for a loan?

For employees, proof of income usually means recent payslips (pay stubs), often supported by W-2s, tax returns or an employer letter. Self-employed borrowers typically provide tax returns, 1099 forms, profit and loss statements and bank statements showing regular deposits. Lenders often ask for several documents because each one confirms the others. Mindee extracts the key figures from payslips and bank statements, such as gross and net pay, YTD earnings, employer name and salary deposits, so you can verify income across documents in seconds instead of reading every page.

How long does loan underwriting take, and how can it be faster?

Underwriting can take from a few days to several weeks, depending on the type of loan and how complete the borrower’s file is. A large share of that time goes to collecting documents, retyping their data and going back to the borrower for missing or inconsistent information. With Mindee, each document is classified and its data extracted in seconds as soon as it is uploaded, and incomplete files are flagged immediately. Underwriters start from a ready-to-review file and spend their time on credit decisions rather than data entry.

Can Mindee cross-check information across a borrower’s documents?

Yes. Since every document becomes structured data, consistency checks can run automatically across the whole file. For example, you can check that the net pay on the payslips matches the salary deposits on the bank statements, that the name and address are the same on the ID, the proof of address and the application, and that the monthly payment on an existing mortgage statement appears in the account’s transactions. Consistent files go straight to underwriting, and those with discrepancies are flagged with the fields that don’t match. This saves time and helps detect altered or inconsistent documents before a credit decision is made.