Detect fraud in real-time with Swiftask and BigML
Swiftask connects your transactional data to BigML. Your AI agents analyze every operation instantly and block risks before they happen.
Result:
Secure your revenue and protect your reputation with proactive, automated detection.
AI Agents
bigml
Connector bigml · Secure OAuth 2.0
Transactional fraud is costly and moves too fast
Manual fraud detection is obsolete. Fraudsters exploit human slowness and fragmented data. If your business waits for human review to validate a transaction, you are already vulnerable.
Main negative impacts:
Slow response times
By the time an alert is handled by a human, the financial damage is already done.
High false positives
Rigid manual rules block legitimate customers, directly impacting your revenue.
High management costs
Dedicating teams to manually analyze every transaction is a financial and operational drain.
Swiftask automates the bridge between your systems and BigML's predictive models. The AI evaluates every transaction in milliseconds, enabling instant decision-making.
BEFORE / AFTER
What changes with Swiftask
Before Swiftask + BigML
A suspicious transaction arrives. It sits in a manual queue. A team must verify it, compare it with history, and decide. Often, fraud is detected too late, after funds are lost.
With Swiftask + BigML
As soon as a transaction is initiated, Swiftask sends the data to BigML. The predictive model returns a risk score. If the score exceeds the threshold, the agent automatically blocks the operation and alerts the security team.
Deploy your detection agent in 4 steps
1
STEP 1 : Train your model on BigML
Use BigML to create a robust classification model based on your historical transaction data.
2
STEP 2 : Configure the agent in Swiftask
Create a dedicated Swiftask surveillance agent configured to query your BigML model for every event.
3
STEP 3 : Define action thresholds
Set the rules: if fraud score > X, block; if between Y and Z, send an alert.
4
STEP 4 : Automate and monitor
Activate the workflow. Every transaction is now filtered by AI without human intervention.
Predictive analysis capabilities
The agent examines behavioral patterns, geolocation, amount, and frequency to correlate this data with BigML models.
- Target connector: The agent performs the right actions in bigml based on event context.
- Automated actions: Real-time scoring, automatic blocking, Slack/Teams notification, incident ticket creation, blacklist updates.
- Native governance: Every decision is logged to ensure compliance and allow for continuous model improvement.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-bigml@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Strategic security advantages
Execution speed
Instant transaction analysis, reducing response time to milliseconds.
Increased precision
Machine learning drastically reduces false positives compared to manual rules.
Full scalability
Handle thousands of transactions per minute without increasing staff.
Unified governance
Track every blocking decision for your compliance audits.
No-code accessibility
Business teams manage security rules without relying on the IT department.
Data security and integrity
Swiftask applies enterprise-grade security standards for your bigml automations.
- Encrypted data flow: Data exchanged between Swiftask and BigML is encrypted end-to-end.
- Strict access control: Granular management of rights on models and automation workflows.
- Compliance ensured: Full audit trail of all decisions made by the AI agent.
- Technology independence: Swiftask adapts to any BigML model, you retain full ownership of your strategy.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Improve your key metrics
| Metric | Before | After |
|---|---|---|
| Detection time | Hours/Days | Milliseconds |
| Fraud rate | High (manual) | Drastically reduced |
| False positives | Frequent | Minimized by AI |
| Operational load | Dedicated team | Management by exception |
Take action with bigml
Secure your revenue and protect your reputation with proactive, automated detection.