Payment risk management: A complete guide

The payment landscape has witnessed a significant transformation in recent years. Gone are the days when cards, wires or cash were the sole options for same-day settlement. Now, consumers and businesses have a variety of payment options, like same-day ACH and Real-Time Payments (RTP). However, the emergence of new payment rails and faster payment types also increases the risk of payment fraud.  

This article sheds light on the growing risk of payment fraud and explores effective payment risk management practices to help businesses stay ahead.

Key takeaways:

• Payment risk management is a layered process that runs before, during, and after every transaction, covering identity verification, account validation, and real-time risk scoring.

• Payment risks include fraud, credit and returns issues, operational problems, compliance and regulatory issues, settlement failures, and chargeback/friendly fraud.

• Plaid products such as Signal, Identity Verification, Protect, and Guaranteed Payments use real-time financial data to manage multiple layers of payment risk.

What is payment risk management? 

Payment risk management is the process of identifying, evaluating, and mitigating risks that can cause financial loss, fraud, or compliance issues throughout the payment lifecycle. It spans every stage, from account creation and bank verification to transaction authorization and post-payment monitoring. 

The goal is to stop bad actors before they transact, flag suspicious activity in real time, and limit exposure to ACH returns, chargebacks, and regulatory penalties. Done well, it protects revenue without adding unnecessary friction for legitimate users.

The growing threat of fraud makes payment risk management essential 

With the growth of digital transactions and the emergence of new payment rails, fraudsters have found new ways to exploit vulnerabilities in digital payments, making online payment risk management essential. The consequences of payment fraud can be severe, resulting in financial losses, a poor customer experience, and a decrease in trust. It also poses a threat to the overall integrity and security of the payment ecosystem.

For example, letting a fraudster open a deposit account means diverting resources away from real customers, and failing to protect against account takeover (ATO) at login lets fraudsters collect information to commit fraud elsewhere. 

While fraud isn’t a new problem, it’s a growing challenge. A study found 80% of organizations fell victim to payment fraud in 2023, and FTC data reported consumers lost over $12 billion to fraud in 2024, an increase of over $2 billion from 2023. For businesses, the impact can be even greater–every $1 of fraud results in $5.75 in losses for financial services companies.

By staying proactive and implementing robust payment risk management controls, businesses can mitigate the risk of payment fraud, safeguard their financial interests, and maintain customer trust.

What are the types of payment risk?

There are six main types of payment risk, and each one can affect a different part of your payment operations.

Fraud risk

Fraud risk is the potential impact of unauthorized or deceptive transactions, including account takeover, synthetic identity fraud, first-party misuse, and unauthorized ACH debits. For businesses, the consequences can include direct revenue loss, chargeback exposure, and reputational damage that's hard to repair once a pattern is established.

Return risk

Return risk is the risk that a payment can't be collected or is later reversed due to insufficient funds, a closed account, or a disputed ACH debit. Nacha mandates strict return rate thresholds (3% for administrative returns and 0.5% for unauthorized returns), and exceeding them puts your ACH processing privileges at stake.

Operational risk

Operational risk comes from failures inside your own payment processing risk management flow, such as processing errors, reconciliation gaps, third-party vendor outages, or misrouted transactions. The business impact includes delayed settlements, duplicate charges, and the manual cleanup costs that follow.

Compliance and regulatory risk

Compliance risk is exposure to fines, audits, or processor termination from failing to meet regulatory or payment network obligations. These obligations include Payment Card Industry Data Security Standard (PCI DSS), Anti-Money Laundering/Bank Secrecy Act (AML/BSA), Know Your Customer/Know Your Business (KYC/KYB) requirements, and Nacha Operating Rules. 

Payment finality risk

Payment finality risk occurs when a transaction can’t be recalled or reversed on irrevocable rails like FedNow and RTP, even if sent by mistake or to a fraudster. That makes pre-send verification, such as identity, account validity, and risk scoring, the only real defense.

Chargeback and friendly fraud risk

Chargeback and friendly fraud risk is the exposure from consumer disputes, including users claiming payments they initiated were unauthorized, or buyers filing fraud claims for purchases they actually made. High dispute rates trigger payment processor monitoring programs, and exceeding thresholds can result in account termination.

What does a payment risk management framework look like?

Payment risk management is a layered process that runs before, during, and after every transaction. 

1. Pre-transaction (Identity and user verification): This stage covers KYC/KYB checks, identity document verification, and fraud consortium screening, confirming that the user is who they claim to be before they can transact.

2. At-transaction (Account and funds verification): This stage validates account ownership, checks for sufficient funds, and scores the transaction for risk, catching mismatches and fraud signals before money moves.

3. Post-transaction (Monitoring, returns, and dispute management): This stage covers ongoing behavioral monitoring, ACH return tracking, dispute management, and pattern analysis that informs future risk decisions.

Reduce fraud risk: 3 core payment risk management controls 

Reducing payment fraud requires a proactive process that assesses risk at sign-up, during account verification, when transactions occur, and beyond.

User risk and identity verification

Upstream verification (before sign-up) verifies customer information during the account creation process to determine if a user is fraudulent or using a stolen identity. This payment risk mitigation step reduces risk by verifying users' identities before any transactions occur. 

Through the KYC process, customers provide details like name, address, ID, phone number, and email address when creating an account. This information enables active verification, such as validating phone numbers and cross-referencing data against other sources. However, meeting compliance and regulatory requirements at the account creation stage isn’t enough. Limiting user risk includes understanding account changes and monitoring risk over time.

This verification can be carried out either manually, where human intervention is involved, or automatically. Plaid's Identity Verification achieves this by verifying the information needed to reduce user fraud risk without causing friction in the onboarding process. 

Plaid Protect takes it even further by leveraging network-based fraud intelligence to flag risky identity information in real time, surfacing suspicious transaction patterns and account changes. Consortium reports in Protect share fraud signals throughout the Plaid Network, helping facilitate detection at the moment of onboarding.

Bank account verification

Account verification involves confirming the authenticity and validity of a customer's financial account information to reduce payment risk. By verifying account details, businesses can better assess the associated risks, such as the risk of transaction return or risk of erroneous or fraudulent payments. 

However, building a robust internal identity-matching algorithm requires time and extensive developer resources. Also, adding fraud checks at this step often increases user friction and churn.

Plaid Identity is used to verify that a customer’s information matches the account ownership information on file with the financial institution. By using Plaid’s matching algorithm (which is just as good as a trained human reviewer), businesses can better identify data mismatches while ensuring true account owners are not misclassified. 

Organizations should also keep an eye out for fraudsters who might exploit the system by changing previously authenticated payout information or using stolen account information for fraudulent purchases. Ongoing verification processes can mitigate this risk. Verifying new information, analyzing customer behavior patterns, and conducting active checks at periodic intervals can ensure the legitimacy of account ownership. For instance, if a customer wants to change their phone number several months down the line, the account can be reverified to reassess the risk. 

Transaction risk scoring

Transaction risk detection is the process of analyzing financial transactions in real-time to identify fraudulent, suspicious, or otherwise risky payments. Risk is detected through transaction attributes, such as amounts, time, date, sender, receiver, and transaction patterns. 

Analyzing these details allows businesses to reduce risks related to account takeover, money laundering, fraud, and regulatory non-compliance. For example, monitoring transaction amounts can identify unusually high-value transactions that may indicate fraud or money laundering attempts. Analyzing the time and date of transactions can reveal potentially suspicious behavior—a customer trying to empty their account at 3 a.m. local time may be a red flag. Furthermore, scrutinizing the sender and receiver information can help detect unauthorized transactions. 

To enhance transaction risk management at scale, businesses can leverage machine learning solutions. Plaid Signal is a machine-learning risk engine that predicts ACH return risks and is trained on data across thousands of financial institutions and millions of transactions. It learns the behavioral fingerprints of legitimate payments and flags deviations in real time, producing a score that reflects the full context of the transaction.

For example, for low-risk transactions, you can make funds available immediately to a customer so they can start making the most of your app. For high-risk transactions, you can put additional checks in place.

Going one step further: Fully offload risk to a partner

For those who want to offload risk to a partner, Plaid offers Guaranteed Payments, which assumes 100% of the risk of approved ACH payments. Using the power of Plaid’s proprietary AI-powered ACH risk platform and real-time fraud intelligence system, Plaid makes smarter ACH decisions on your behalf. If it’s approved by Plaid, it’s fully covered.

How Plaid helps manage payment risk 

Plaid covers all three layers of the risk management process in one integrated platform built on financial data. Identity Verification confirms who your users are at onboarding, while Protect scores fraud risk via network intelligence. Signal applies ML-based risk scoring to ACH payments, enabling dynamic flows that reduce friction and add controls where risk is real.

Learn more about how Plaid helps businesses reduce payment risk and fraud, optimize the payment process, and keep customer information safe.