Process Street
Process Street is an AI-enhanced compliance and operations platform designed to help teams systemize execution and prove compliance. …
Process Street is an AI-enhanced compliance and operations platform designed to help teams systemize execution and prove compliance. It enables businesses to create intelligent workflows, automate recurring tasks, and maintain regulatory standards, boosting efficiency and reducing errors.
About Auditing
AI Auditing tools are specialized software that automates the examination of systems, data, and algorithms to ensure accuracy, security, and compliance. As a critical function within the broader Compliance framework, these tools use machine learning and data analysis to scrutinize vast datasets, identifying anomalies, vulnerabilities, and risks more effectively than manual methods. Their primary value is in providing continuous, objective, and comprehensive verification, helping organizations maintain regulatory adherence and operational integrity. They are particularly powerful for complex tasks like smart contract analysis and AI model fairness checks.
Core Features
- Automated Anomaly Detection: Continuously analyzes transactional data to identify unusual patterns, potential fraud, or non-compliant activities in real-time.
- Smart Contract Vulnerability Scanning: Systematically inspects blockchain smart contract code for common security flaws, logical errors, and potential exploits.
- AI Model Bias Assessment: Evaluates machine learning models for fairness, checking for biases related to protected attributes like gender or ethnicity.
- Regulatory Compliance Verification: Automatically cross-references internal processes and data against specific regulatory frameworks (e.g., GDPR, SOX, HIPAA) to flag discrepancies.
- Automated Evidence & Report Generation: Compiles detailed audit trails, evidence logs, and comprehensive reports to streamline compliance documentation and stakeholder reviews.
Use Cases
These tools are essential for financial institutions automating internal controls testing, technology companies auditing their AI algorithms for ethical compliance, and Web3 projects securing their decentralized applications. They are primarily used by internal and external auditors, compliance officers, risk managers, and security analysts.
How to Choose
When selecting an AI Auditing tool, evaluate its specific focus area (e.g., financial, smart contract, AI model). Consider its integration capabilities with your existing systems (like ERPs or data lakes), the transparency of its analytical methods (explainability), and its support for the industry-specific regulations you must adhere to.
AuditingUse Cases
Automating Financial Statement Audits
An external audit firm is tasked with auditing a large corporation's financial statements. Instead of relying solely on manual sampling, auditors use an AI Auditing tool to analyze 100% of the company's transactional data. The tool automatically flags high-risk transactions, identifies duplicate payments, and detects anomalies in revenue recognition patterns that deviate from historical norms. This allows the audit team to focus their investigation on the most critical areas, significantly increasing the accuracy and efficiency of the audit process while providing a higher level of assurance.
Securing DeFi Smart Contracts Before Launch
A Web3 development team is preparing to launch a new decentralized finance (DeFi) protocol. Before deployment on the mainnet, they use an AI-powered smart contract auditing tool. The tool performs a static and dynamic analysis of the Solidity code, automatically identifying common vulnerabilities such as reentrancy attacks, integer overflows, and improper access controls. It provides a detailed report with risk scores and code-level recommendations for remediation. This automated pre-launch audit helps the team fix critical security flaws, protecting user funds and enhancing the protocol's trustworthiness from day one.
Auditing AI Hiring Tools for Fairness and Bias
An HR department implements a new AI tool to screen resumes and shortlist candidates. To ensure ethical and legal compliance, the company's risk management team uses an AI Auditing tool specifically designed for model fairness. The tool analyzes the hiring tool's historical decisions against candidate demographics (e.g., gender, ethnicity). It generates a fairness report, highlighting if the model disproportionately favors or penalizes certain groups. This objective audit provides documented evidence of due diligence and helps the company mitigate risks of discrimination and reputational damage.
Continuous GDPR Compliance Monitoring
A European e-commerce company needs to ensure ongoing compliance with GDPR. Their compliance officer uses an AI Auditing tool that integrates with their customer database and marketing platforms. The tool continuously scans for data processing activities, verifying that user consent is properly recorded and respected. It automatically flags instances where data is held longer than necessary (violating data minimization principles) or used for purposes not covered by the consent agreement. This proactive monitoring allows the company to correct compliance issues in real-time, avoiding potential fines and building customer trust.
Verifying Supply Chain Ethical Standards
A global apparel brand needs to audit its suppliers for compliance with fair labor and ethical sourcing standards. An AI Auditing tool is used to analyze supplier contracts, payroll records, and shipping manifests. By applying Natural Language Processing (NLP), the tool can cross-reference clauses in contracts with actual payment data to flag potential underpayment issues. It also analyzes shipping patterns to detect signs of unauthorized subcontracting. This automated approach provides a scalable way to monitor a complex global supply chain, ensuring the brand upholds its corporate social responsibility commitments.
Automating Internal Controls Testing for SOX
The internal audit team of a publicly-traded company is responsible for Sarbanes-Oxley (SOX) compliance. They use an AI Auditing tool to automate the testing of key internal controls. The tool connects to the company's ERP system and continuously monitors user access rights, segregation of duties, and transaction approval workflows. It automatically generates exception reports for any control failures, such as an employee approving their own expense report. This shifts the audit process from periodic manual testing to continuous automated monitoring, providing stronger assurance and reducing the cost of compliance.