Fraud Types

Financial Frauds

Type	Description
Document Fraud (First party)	This classifies under first party fraud where applicant commits fraud in his own name. Applicant provides an altered / fabricated document which does not match the real document at the time of verification with data source. Usually done for National IDs like PAN, Voter ID, etc. However it can be applicable to other types of documents as well which are submitted at the time of loan application.
Identity Fraud (Third party)	This classifies under third party fraud where applicant commits it in the name of another person (victim). Applicant deliberately uses personal information of another person without any approval, for the sole purpose of performing a fraud. Hence, the 3rd party here becomes the victim.
Synthetic Identity Fraud	It is created by using a combination of real and fabricated credentials leading to a fictitious entity that is not associated with an actual / real person. E.g., using A's PAN with B's address or a fictitious address altogether.
Financial Fraud	Cases where financial crimes have been committed like Cheque fraud, manipulation of bank statements, false financial statements, chargeback fraud, etc.
Employment Related Fraud	Instances of misrepresentation of information / documents on account of education, personal background or professional history. E.g., salary slip / employment letter tampering. This can be clubbed under Document Fraud if not a significant category.
Non-starter fraud	Cases where post loan disbursal the borrower does not repay starting from the first installment itself. It then clearly shows his fraudulent intention. Also known as never payment fraud, lenders can start tagging borrowers under this category once DPD has reached 90 days - as a uniform definition to classify. This is different from delinquency since it is linked to non-payment from inception of the loan and not midway in the lifecycle.
First-party application fraud	A consumer refuses to repay legitimate debts and/or falsely claims to be a victim of identity fraud to evade the obligation
Account takeover	Someone other than the owner uses an account without permission

Other Frauds

Type	Description
New account	Accurately distinguish between legitimate and high-risk customer account registrations so you can selectively introduce additional steps or checks based on risk. For example, you can setup your customer account registration workflow to require additional email and phone verification steps only for account registrations that exhibit high risk characteristics.
Online payment	Reduce online payment fraud by flagging suspicious online payment transactions before processing payments and fulfilling orders. With Amazon Fraud Detector, you can setup your checkout flow to evaluate new orders and flag suspicious ones for review prior to processing payments.
Guest checkout	Spot potential fraudsters among customers without transaction histories. With Amazon Fraud Detector, you can send as little as two pieces of data from a guest checkout order (e.g., email, IP address) to assess its potential fraud risk, so you can decide whether to accept it, review it, or collect more customer details.
Online service and loyalty program abuse	Identify accounts that are more likely to abuse online services such as loyalty or ‘Try Before You Buy’ programs that ship goods for customers to try before sending payment. With Amazon Fraud Detector, online businesses can assess the risk of customers abusing programs, for example by stealing merchandise or engaging in returns abuse, so businesses can limit their risks by applying appropriate limits on the value of goods or services provided.
Account takeover	Identify fraudulent online activity by detecting accounts that were compromised through malicious takeovers, phishing, or from credentials being stolen. With Amazon Fraud Detector, you can improve account takeover detection by observing behavior patterns and treating anomalous user login activity as more risky, while minimizing the level of friction for legitimate users. Based on outcomes you receive, you can take appropriate actions on each login, for example challenge only the highest-risk authentication attempts.
Product review	Safely automate whether to approve or block review submissions. With Amazon Fraud Detector, you can reduce the number of review submissions sent to moderation queues, while reducing fraud and spam and adding friction for risky review submissions.