ChainAware API provides blockchain fraud detection, wallet risk scoring, rug pull analysis and segmentation services through secure authenticated endpoints.
The "Fraud Check Wallet" endpoint is designed to assess the risk of fraudulent activity associated with a specific digital wallet based on various parameters such as transaction history, user behavior, and authentication metrics. By submitting wallet identifiers and relevant transaction data for analysis, the endpoint processes this information against predefined risk models and algorithms to generate a comprehensive fraud risk score along with detailed insights indicating potential red flags. This functionality is crucial for financial institutions, e-commerce platforms, and digital wallet providers aiming to enhance security measures, mitigate losses from fraud, and ensure a safer transactional environment for users by implementing proactive fraud detection and prevention strategies.
Fraud Check Wallet - Endpoint Features
| Object | Description |
|---|---|
request_body |
[Required] |
Request Body |
[Required] Json |
{"error":"Address not provided!"}
curl --location --request POST 'https://zylalabs.com/api/11894/chainaware+ai+api/22599/fraud+check+wallet' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw ''
The "Fraud Audit Wallet" endpoint is designed to facilitate the detection and analysis of potentially fraudulent activities associated with user wallets within a financial system. This endpoint processes transactional data and user activity logs to identify anomalies or patterns indicative of fraud, such as unusual transaction volumes or suspicious origin locations. Upon invocation, it returns a structured report containing flagged transactions, risk scores, and suggested actions for mitigating identified threats. This endpoint is particularly useful for compliance teams and fraud analysts aiming to enhance security measures, conduct thorough audits, or integrate findings into larger fraud prevention systems within financial institutions or e-commerce platforms.
{"error":"Address not provided!"}
curl --location --request POST 'https://zylalabs.com/api/11894/chainaware+ai+api/22600/fraud+audit+wallet' --header 'Authorization: Bearer YOUR_API_KEY'
The "Rug Pull Check" endpoint is designed to analyze and assess the potential risk of a cryptocurrency project engaging in a rug pull, a type of scam where developers abandon a project and take investors' funds. This endpoint processes various inputs, such as the project's smart contract address, transaction history, and relevant on-chain data to identify red flags, such as sudden liquidity withdrawal or a lack of user engagement. The response includes a comprehensive risk assessment score, a detailed report outlining identified issues, and actionable insights that can help investors make informed decisions. Potential use cases for this endpoint include enabling investors to conduct due diligence before investing in new cryptocurrencies, assisting developers in improving project transparency, and providing researchers with data for analyzing market safety trends.
{"error":"Address not provided!"}
curl --location --request POST 'https://zylalabs.com/api/11894/chainaware+ai+api/22601/rug+pull+check' --header 'Authorization: Bearer YOUR_API_KEY'
The "Wallet Segmentation" endpoint is designed to categorize users' digital wallet activities into distinct segments based on various criteria such as transaction frequency, transaction volume, and user demographics. This data-driven approach facilitates personalized user experiences by allowing businesses to tailor marketing strategies and financial products to specific user groups. The endpoint processes incoming transaction data and returns insights, including segmented user lists and statistical summaries that reflect the behavior of each segment, enabling targeted campaigns, enhanced user engagement, and improved retention rates. Potential use cases include optimizing promotional offerings for high-value customers, understanding trends in user spending habits, and identifying opportunities for cross-selling financial services.
{"error":"Address not provided!"}
curl --location --request POST 'https://zylalabs.com/api/11894/chainaware+ai+api/22602/wallet+segmentation' --header 'Authorization: Bearer YOUR_API_KEY'
The "User Credit Score" endpoint is designed to retrieve and manage the credit score information associated with a particular user within a financial application. It serves the primary purpose of providing users with their current credit score, which can be crucial for assessing their financial health and making informed decisions regarding loans, credit cards, and other financial products. The endpoint processes user authentication parameters to ensure secure access and returns relevant data including the credit score value, score range, and detailed credit report factors that influence the score. Potential use cases include enabling users to monitor changes in their credit scores over time, receive personalized financial recommendations based on their credit standing, and facilitate application processes for credit-related services by allowing seamless risk assessment by financial institutions.
{"error":"Address not provided!"}
curl --location --request POST 'https://zylalabs.com/api/11894/chainaware+ai+api/22603/user+credit+score' --header 'Authorization: Bearer YOUR_API_KEY'
| Header | Description |
|---|---|
Authorization
|
[Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed. |
No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.
Each endpoint returns structured data relevant to its function. For example, the Fraud Check Wallet returns a fraud risk score and insights on potential red flags, while the Rug Pull Check provides a risk assessment score and a report on identified issues.
Key fields in the response data typically include error messages, risk scores, flagged transactions, and detailed reports. For instance, the Fraud Audit Wallet may return flagged transactions along with their risk scores.
Parameters vary by endpoint. For example, the Fraud Check Wallet requires wallet identifiers and transaction data, while the Rug Pull Check needs a project's smart contract address and transaction history for analysis.
Response data is organized in JSON format, typically containing key-value pairs. For example, an error response might look like `{"error":"Address not provided!"}`, while a successful response includes risk scores and detailed reports.
The data sources include on-chain transaction data, user behavior metrics, and external fraud detection models. This multi-source approach enhances the accuracy and reliability of the fraud detection and risk assessment processes.
Typical use cases include enhancing security measures for financial institutions, conducting audits for compliance teams, and enabling investors to assess the risk of cryptocurrency projects before investing.
Users can customize requests by providing specific parameters relevant to their needs, such as transaction history for the Fraud Check Wallet or demographic criteria for Wallet Segmentation, allowing tailored insights.
Data accuracy is maintained through continuous updates from reliable blockchain sources, regular audits of the algorithms used, and validation against known fraud patterns to ensure the integrity of risk assessments.
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