Fraud and risk teams: changing rules with your own hands
In fraud prevention, the winner is the one who adapts fastest. TruvaLI empowers risk experts to write rules directly: drafts are generated from your own natural language, tested in simulation, and deployed to production upon approval.
Fraud and risk teams operate in the narrow margin between preventing losses and avoiding customer friction. Both mistakes carry a cost, and both are measurable: a missed fraud event is a direct loss, while a falsely declined legitimate customer is lost revenue.
Why is response time critical?
Fraud patterns are never static. When one loophole closes, a new one opens within weeks, and the person who spots it is usually on your team. The challenge is not identifying the threat, but translating that insight into the system.
When the rule writer and the risk expert are different people, every change enters a request queue, making response times dependent on backlog length. With TruvaLI, you write the control in your own words to generate a draft rule, which never goes live without approval. Learn more on the writing rules with prompts page.
What are rules built on?
| Building block | Function |
|---|---|
| Aggregation windows | A customer's transaction count, sum, and average over a specific period |
| Non-financial event | Logins, device changes, document uploads, setting modifications |
| Relationship network | Accounts linked through shared device, IP, card, address, or email patterns |
| Score contribution | Rules contributing to an overall score rather than triggering a direct decision |
| Rule ownership | The owner of the rule, whether it is private or shared, and who it is shared with |
| Execution order | The sequence in which rules are evaluated |
A rule's outcome does not always have to be a hard block. Contributing to a score, adding an alert reason, or simply flagging the transaction are also valid outcomes. This allows you to monitor aggressive rules before deploying them to production.
Can the impact of a change be seen in advance?
Yes, and it should be. A new rule is run against historical transaction traffic, measuring how many transactions it would block, how many alerts it would generate, and how many of those actually turn out to be fraud, all before going live. Replaying it against a specific day shows exactly what the outcome would have been in that day's traffic.
Without this measurement, threshold discussions remain purely subjective. With it, you can discuss exactly how many customers will be affected by raising a threshold by a single point. The rule simulation and backtesting page explains this in detail.
Deriving rules from past cases
The best source for a rule is a fraud event that has already occurred. The signal pattern within the case can be extracted and converted into a rule, ensuring the same path cannot be exploited twice. This keeps institutional knowledge within the organization, rather than with individuals. Learn more on the generating rules from past cases page.
Speed is a requirement, not a feature
Fraud checks operate directly within the transaction flow. An evaluation that does not return fast enough to make a decision provides the right answer only after the funds have left, which has no practical value. How these evaluations are structured is detailed on the fraud detection and real-time risk scoring pages.
Scenarios
Specific patterns are covered on dedicated pages: account takeover, bonus abuse and multi-accounting, and chargeback and payment fraud.
Common questions
- What is the biggest bottleneck for fraud teams?
- It is not identifying the threat, but translating that insight into the system. When the rule writer and the risk expert are different people, every change enters a request queue.
- Is technical knowledge required to write rules?
- No. You write the control in your own words to generate a draft rule, which never goes live without approval.
- Does a rule always have to block a transaction?
- No. Contributing to a score, adding an alert reason, or simply flagging the transaction are also valid outcomes. This allows you to monitor aggressive rules before deploying them to production.
- Can non-financial events be included in rules?
- Yes. Events without monetary values, such as logins, device changes, document uploads, and setting modifications, are also used in rules.
- How is the impact of a new rule measured?
- The rule is run against historical transaction traffic, showing how many transactions it would block, how many alerts it would generate, and how many of those actually turn out to be fraud, all before going live.
- Can tests be run against a specific day?
- Yes. The rule can be replayed against that day's traffic to see exactly what the outcome would have been.
- Can rules be generated from past cases?
- Yes. The signal pattern within the case can be extracted and converted into a rule, keeping institutional knowledge within the organization rather than with individuals.
- Can the execution order of rules be controlled?
- Yes. The sequence in which rules are evaluated can be defined, and the rule's owner and sharing permissions are also recorded.