ACH is a common and accessible way to make payments and transfers; however, transactions can often take three to five business days to settle. With speed at the forefront of consumer expectations—76% of consumers are more likely to use a fintech app when they can sign up and access it instantly—this makes the lengthy hold times often associated with ACH transactions especially glaring during a funding event.

Businesses, however, must protect themselves against potential fraud and associated losses, which can be at odds with consumer expectations. If time truly is money, what happens when time is a barrier to your customers’ dollars—and thus impacts the growth of your business?

At Plaid, we believe you shouldn’t have to choose between risk reduction and a great customer experience. Today, we’re excited to expand the availability of Signal, a machine learning risk engine that allows you to accelerate payments to near-instant experiences—all while reducing risk to your bottom line. Signal has been in use by several Plaid customers for over a year and currently protects nearly $1.5 billion in transactions every month. 

Enhance your risk program to deliver great customer experiences

For each transaction, Signal analyzes over 1,000+ unique risk factors and returns risk scores, tiers, and more than 60 attributes for improved automation and faster, more confident ACH transactions. With increased performance and precision, you can upgrade the user experience and boost conversion rates by unlocking faster or instant access to funds without increasing risk. More importantly, you can more effectively predict and therefore prevent risky and fraudulent transactions from taking place on your platform.

Here are three examples of the impact across our customer base: 

• Grant instant access to funds without impact to the bottom line: After implementing Signal, a popular investment platform was able to give 96% of their new users accelerated access to funds (vs. 0% previously), with nearly no increase to its ACH return rate. This means their new users were able to start investing almost immediately, instead of waiting up to five days for funds to settle, which improves conversion rates and user engagement.

• Enhance existing payment risk and fraud models: A leading pre-paid debit card provider cut their return rates by half within the first month of implementing Signal. By including the unique, real-time attributes to its existing transaction risk model, the neobank was able to further refine its ability to identify risky transactions and reduced their overall return rate by over 80%. 

• Reduce losses without increasing user friction: Companies often address payment risk by adding more verification steps for all users, which can add friction to the user experience and lower conversion rates even for its trusted users. With increased accuracy and precision, Signal allows companies to limit where they need to introduce additional steps and friction. For example, Signal helped a leading digital wallet reduce return losses by 43%, while only introducing additional verification steps to less than 1% of users.

How it works:

Built on Plaid’s leading consumer-permissioned Open Banking platform, Signal enables more precise and dynamic payment flows through predictive scores, tiers, and unique attributes. A quick deep dive into how it works:

Predictive scores & tiers

To simplify ACH return complexity, Signal segments return types into two categories: bank-initiated and customer-initiated returns. Every transaction receives a predictive score and accompanying risk tier (low, medium, or high risk) for each category. 

For low-risk tiers, your business can confidently provide instant access to the funds in question. The ability to quickly filter ACH payments through risk tiers allows most of your transactions—those with little risk—to be made available immediately, removing unnecessary friction for both you and your customers with increased confidence. 

Unique attributes 

Based on over 1,000 risk factors, Signal scores and tiers are accompanied by over 60 predictive insights, known as attributes, which explain the ‘why’ behind each score which is critical to helping you improve the precision and transparency of your existing risk models. Built with configurability in mind, we’ve categorized these attributes as:

• Plaid connection history analyzes account connectivity and its respective frequency in the Plaid Network, which covers over 12,000 financial institutions and more than 7,000 applications. 

• Account usage verifies account status and analyzes how the account is used via trends in balance, transaction types, and other information. 

• Past ACH events identify possible past returns due to unauthorized transactions or insufficient funds from the account that will be debited.

• Identity monitors changes across phone numbers, email addresses, and physical addresses to identify suspicious activity. 

The more accurate and insightful the data, the more precise and performative your fraud program will be. Plaid’s attributes—such as connection history and past ACH events—factor in unique statistics and data points on how accounts interact across the ecosystem. The inherent feedback loop enhances your business’ risk program and makes the overall ACH network safer by creating a connected ecosystem to fight risk and fraud. 

Get started

Join us in making account-to-account money movement smarter, faster, and safer through innovation on both existing and emerging bank payment rails. With Signal, there’s no more need to choose between an exceptional consumer experience and robust risk and fraud management. You can unlock instant ACH, have better-managed return rates and increase acquisition rates through a better user experience. 

If you’re interested in Signal, learn more about it here or reach out to your Plaid Account Manager.