Data Integration Guide - Loan Applications

Loan Application Data for Analysis

Application data fields, as well as customer profile data fields associated with the application, are an important driver of DataVisor’s ability to identify loan application fraud. This document serves as a general integration guideline for identifying application fraud as it pertains specifically to loans. 

Loan Application Data

Fields that are helpful for loan application use cases include (but are not limited to):



Data Field



Account-Level Information

Account Number

Unique account number 


Loan Application ID

A unique ID that identifies the specific loan application


Bank-Level Information 

(if available)

Bank Account Type

The type of account to which the loaned amount is sent to (e.g. savings, checking, etc.)


Bank Account Number

The applicant’s bank account # for the account to which the loan will be disbursed


Bank Routing Number

The applicant’s bank routing #


Bank Account Name

The full name of the applicant as found in their bank account


Bank Account Balance

The balance in the applicant’s bank account


Credit Information

FICO Score

The FICO Score of the applicant, as pulled from a credit report


Credit Report Pull Date

The date when the report was last pulled by the loaning institution


Credit Report Provider

The credit report agency from which the report was pulled (e.g. Equifax, Experian)


Other Credit Report Data

Any other fields that are parsed from the credit report (as applicable)


# of Recent Credit Inquiries

The number of credit inquiries requested by the applicant in the last X months (X could be 6, 12, 24, etc.)


Loan-Level Information 

Loan Amount

The amount requested in the loan application (in US dollars)


Loan Type

The type of requested loan (personal, commercial, business, etc.)


Loan Drill-Down Info

Any channel-specific information around the loan 

(e.g. for auto loans, make/model of car)


Loan Product

The type of loan product, if applicable


Loan Requested Amount

The amount requested by the applicant on the loan. May differ from the final loan amount


Loan Application Time

Timestamp of the loan application


Loan Duration

The total length of the loan period, preferably in either days or months


Monthly Payment

Estimated monthly payment on the loan, if calculated by the lender


# Good Payoffs in last X months

How many loans were successfully paid off by the applicant in the past X months (commonly X = 12 or 24)


# of Delinquent Payments in last X months

How many loans had delinquent / no payment by the applicant in the past X months (commonly X = 12 or 24)


Cosigner / Joint Applicant?

Is there a joint applicant or co-signer on this loan?


Cosigner / Joint Applicant Information

If applicable, all personal info about the joint applicant or co-signer (name, email, address, phone, SSN, etc)


OFAC Sanction Status

Whether the applicant appears on any OFAC sanction lists


Citizenship Status

Is the applicant a US Citizen or Permanent Resident?


Lender Branch Information

If applicant applied in person, branch geo information (address, latitude / longitude)


Device Information

If the applicant applied online, information around the device used to apply (e.g. IP, Device ID, including 3rd party signals)



Loan Never Paid Indicator

An indicator of whether the loan has not been paid off within X days 

(X based on lender’s business policies)


Loan Charge Off Status

A status of whether the lender has marked the loan as charged off 


Loan Charge Off Date

The date on which the loan was charged off by the lender


Loan Charge Off Reason

The reason for charge off, if one is available



An example of loan application data:

Loan App ID

Account ID

Application Type

Transaction Time

Loan Requested Amount

Loan Duration




Business Loan

2022-04-16 12:35:06






Personal Loan

2022-04-16 12:35:06





Customer Profile Data

Customer profile data is also important for fraud detection, when merging with transaction level data.DataVisor uses various types of at-rest and in-transit encryption methods to make sure the PII data shared in the customer profile data is handled in a secured way. If PII data sharing is not available, we recommend using SHA-256 hashing to hash the data before sharing the customer profile data with DataVisor.

Fields that are helpful for customer profile data include:


Data Field



Customer Profile Data

Customer ID / SSN

Unique identifier of the customer who performs the transaction


Registration time

The time the user first registered with the loan provider


Registration Channel

The method through which the customer first registered for an account with the lender


Registration Address 

For in-person registrations, the address of the location where the customer first registered for an account


Registration IP

For online registrations, the IP from the device where the customer first registered for an account


Product types

A list of products that the customer has previously subscribed to from the lender


Customer tenure

Tenure of the customer



Email address of the customer



Phone number of the customer, or phone prefix


Full Name 

The full name of the customer



The address of the customer



The country of the customer



The city of the customer



The state of the customer


Zip Code

The zip code of the customer


Date of Birth 

Year of birth of the customer


Annual Income

Annual income of the customer


Monthly Rent

Monthly rent paid by the customer


Employment Tenure

How long the customer has been working for their current employer


Employment Status

Customer’s current employment status



Employer name of the customer


Applicant History

Any information about previous loan applications from the customer. Includes the following: 

  • Prior accepted or declined loans
  • Payoff status of such loans
  • Loan amount for each loan previously applied


An example of customer profile data:

Customer ID


Customer Tenure

Product Type


Registration Time


Alice Jane

14 months

Premier Credit Card

2014-01-01 12:03:03


John Doe

60 months

Premier Credit Card

2017-01-02 12:00:00

Data Structure Report

Before sending the full data over, please send over a data structure report to your Technical Account Manager. This process allows DataVisor to ensure a faster turnaround time and a higher quality of results during the fraud assessment. This data structure report should contain the following for each data set:

  • Schema
  • Preview of 10 rows
  • Earliest date and latest date (If there is an associated timestamp)
  • Number of rows

Data Anonymization

DataVisor’s algorithm is able to work with anonymized data fields if required. For sensitive PII information, such as name and address, anonymized information can be processed by our algorithm as long as the data structure remains.

Choosing a Connection Type: Batched or Real-time data transfer

For a batch data transfer, the client sends data in bulk to DataVisor. The frequency of batch data transfer is determined by client’s use case and business requirements. Batch transfers are faster to implement, as they don’t require an integration with DataVisor’s APIs. Account application data should be given as is at the end of the batch time period, and included in the batch. 

Real-time data connection

For a real-time data connection, the client integrates DataVisor’s APIs to send a real-time stream of data. After a ~2 week observation and tuning period, DataVisor returns real-time results, which can be used as an additional signal in the client’s fraud detection infrastructure. All account application data should be uploaded at the beginning of the fraud assessment. 

Formatting and transferring data

Formatting Data

DataVisor can accept data in the following formats:

  1. JSON (preferred) 
  2. Tab Delimited
  3. CSV

For other formats, like TXT or report exports, please contact your Technical Account Manager.

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