Signal Rules
Learn about configuring Signal Rules
Using Signal Rules
With Signal Rules, you can configure your decision logic directly within the Signal Dashboard using templates from Plaid, then use Dashboard tools to tailor the rules to your own traffic.
Signal Rules can be based on scores (higher scores indicate higher risk), attributes of the transaction, or a combination.
You can set up the following actions for your business to take as a result of a rule:
ACCEPT
and process the transactionREVIEW
the transaction further before processingREROUTE
the customer to another payment method, as the transaction is too risky
You can also create more complex action flows through the use of custom action keys
You can define a single ruleset for all your transactions, or you can build use-case specific rulesets, such as one for an initial deposit during customer onboarding and another for a returning customer depositing funds.
Creating a ruleset
Create rulesets on the Signal Rules Dashboard page. You can create a ruleset from scratch, or Plaid can suggest an initial rule template relevant for your use case by utilizing context collected during your Signal onboarding (such as transaction size).
Rules are evaluated sequentially, from top to bottom, typically ordered by the severity of the rule violation. If data that the rule depends on is not available, the rule will be skipped.
The result
of the first rule that matches will be applied to the transaction and included in the /signal/evaluate
response. You will be required to have a fallback rule that is applied if no other rules match.

Using Signal Rule results
To evaluate a transaction's risk, call /signal/evaluate
and include the required request properties in addition to the ruleset's ruleset_key
, which can be found in the Dashboard, in smaller type under the name of the ruleset.
The more properties you provide when calling /signal/evaluate
, such as the user
or device
fields, the more accurate the results will be. Providing the client_user_id
is also recommended to aid in your debugging process later.
In the response, use the ruleset.result
property to determine the next steps.
Most integrations use the result
to decide between approving a payment for processing (result=APPROVE
), or rerouting the consumer to another payment method (result=REROUTE
). If that's the case with your integration, ensure that your ruleset emits only these two result types.
If your integration is taking more complex actions before deciding whether to process the transaction (for example, sending certain transactions to a manual review queue), use the REVIEW
result type. Remember to report the final decision for these reviewed transactions later.
Signal can never be used as an input to determine a consumer's eligibility to access your services. Signal evaluates the risk of a transaction from a specific bank account and can be used to determine if you should require the user to use a different payment method, according to your risk tolerance.
For existing customers prior to May 2025: Migrating away from the outcome field
Customers who used Signal Rules before May 2025 used the ruleset.outcome
field. This field has been replaced by ruleset.result
. Update your integration to use the new values from the ruleset.result
field:
Outcome (old) | Result (new) |
---|---|
block | REROUTE |
accept | ACCEPT |
review | REVIEW |
For most integrations, that's all you need to change. Once you've updated your integration, inform your account manager.
If you have an advanced use case where you take different actions for transactions with the same result
, you can use the custom_action_key
. For example, to apply a variable hold time, make sure your Signal rules emit an result=ACCEPT
value for all transactions you intend to process. Then, use the custom_action_key
to define a 3-day-hold
for some rules and 5-day-hold
for others. For more details, see Using a custom action key.
Using a custom action key for advanced actions
Some integrations may need more options for handling a transaction than the three choices of accept, review, or reroute. For example, you might want to apply a variable hold time to transactions that were accepted and processed, depending on the level of risk. Or you may want to apply labeling to their transactions to denote a cohort for data analysis purposes. To support more complex actions, check the "Configure advanced options" box on the rule editing screen and specify a custom_action_key
.
You can then create multiple rules with the same result but different custom actions. For example:
If medium risk,
ACCEPT
withcustom_action_key=5-day-hold
If low risk,
ACCEPT
withcustom_action_key=3-day-hold
When calling /signal/evaluate
, use the custom_action_key
in the response to determine the action to take.
Data availability limitations
The amount of consumer-permissioned data available to Signal can vary. Signal attempts to prefetch this data at a regular cadence and will also attempt to fetch fresh data during the /signal/evaluate
call if needed. Most Signal evaluations will return information about the Item's use in the network, the latest balance, historical balance information, or account activity. The full set of data is usually available to Signal within 15 seconds of Plaid Link being completed. However, partial data may be returned if /signal/evaluate
is called before this process completes, the Item has been inactive for a long time, or the financial institution's connectivity to Plaid is degraded or down.
When used with Items that do not have a connection to a financial institution, (i.e., Items created verified using alternative methods such as micro-deposits or Database Auth), Signal can generate risk scores for approximately 30% of these Items, although Items created in this way will have no data in the core_attributes
response property. If Signal can't get data, the scores
property will be null
, and any rules using score
will be skipped (potentially triggering your fallback rule). You will still be billed for the evaluation (unless you have no Signal Ruleset enabled).
Testing Signal Rules in Sandbox
In the Sandbox environment, scores and attributes returned by /signal/evaluate
will be randomly generated. You can influence the score returned by /signal/evaluate
in Sandbox by providing particular values in the amount
request field. Use the values from the following table to control the returned score:
Amount | Score |
---|---|
3.53 | 10 |
12.17 | 60 |
27.53 | 90 |
You can use these hardcoded responses and create simple rules in Sandbox (such as REROUTE if bank_score == 90
) to test various result types.
Debugging transactions
All evaluations can be viewed in realtime on the transactions viewer Dashboard page. Look up your transaction using its client_transaction_id
. You can see its scores, the ruleset's result
, and the data used to build the score.
Debugging rules
You can view all transactions that matched a specific rule by clicking View Performance
in the ...
icon on the rule.


Tuning your rules
After your integration is live, Signal will report metrics such as approval rate, and ACH return rate, in the Signal Dashboard. You will use these Dashboard tools to tune your rule logic, which is a critical step in a successful launch.
You must integrate the /signal/return/report
endpoint to use the Plaid Dashboard performance data features. If you do not report returns, Plaid will not show Signal performance.
Accessing scores and attributes directly via API
Plaid strongly recommends using Signal Rules. However, if you have your own risk management system in which you are using Signal as one of multiple data sources, you might choose to ingest Signal data directly via the API instead instead. If you don't use Signal Rules, Plaid may be limited in the support it can offer you in tuning external logic.
To directly access Signal's scores and data attributes, call /signal/evaluate
. The scores
and core_attributes
properties in the response will contain the raw Signal data you can provide to your model. For a full listing of core_attributes
, see the sample response or contact your Account Manager.
Even if you aren't using Signal Rules, it's still recommended to report decisions and returns in order to use the Signal Performance pane, which helps you find the right score threshold.