Automate Your Tenant Credit and Background Check Workflow
Automate credit and background checks by connecting your PMS to screening APIs with a custom script. This script parses applicant data, runs checks, and returns a unified report into your system.
Syntora specializes in designing and building custom automation systems for property management firms to streamline tenant screening workflows. We develop tailored solutions that integrate Property Management Systems with various screening APIs, ensuring data validation and efficient processing. This allows firms to automate complex background and credit checks, presenting summarized findings directly within their existing platforms.
The scope of such an integration depends on which Property Management System (PMS) and which screening providers are in use. Integrating a modern PMS like AppFolio with a standard API like Checkr's is often straightforward. Connecting a legacy system such as Yardi Voyager to multiple state-level background check portals, however, requires more complex data mapping and custom integration work. Syntora provides the expertise to design and build these custom workflow automation systems.
What Problem Does This Solve?
Most property managers start with manual data entry. A leasing agent copies an applicant's name, DOB, and SSN from an online application or PDF into their PMS. Then they copy that same data into a separate portal like TransUnion SmartMove, run the check, download a PDF, and upload it back into the PMS. A single typo in an SSN forces the entire process to restart, wasting 20 minutes.
Built-in PMS screening tools solve the data entry problem but create new ones. You are locked into their chosen screening provider, often at a 30-50% price markup over going direct to the API. More importantly, their decision logic is rigid. You cannot implement custom rules, like ignoring medical debt collections or automatically approving applicants with a co-signer who meets separate criteria. The pass/fail logic is a black box.
This rigidity is a critical failure. A firm managing properties in two different states with different tenant laws cannot apply separate screening criteria. The built-in tool uses one set of rules for all properties, forcing agents to manually review every 'fail' result to check for state-specific context, which defeats the purpose of the automation.
How Would Syntora Approach This?
Syntora approaches tenant screening automation as a custom engineering engagement, starting with a detailed discovery phase to understand your specific PMS, application data structure, and preferred screening providers. We would identify the precise data fields required for mapping from your digital application to the necessary inputs for various screening APIs, such as Checkr or TransUnion. Pydantic would be used for strict data validation, which helps prevent common errors like invalid SSN or address formats from causing failed API calls.
The core of the solution would be a custom Python service, built with FastAPI for efficient API handling and deployed on serverless infrastructure like AWS Lambda. This architecture ensures scalability and cost-effectiveness. The system would be designed to trigger automatically when an application is marked 'Ready for Screening' in your PMS, using webhooks or a scheduled polling mechanism. Utilizing httpx, the service would make concurrent, asynchronous API calls to multiple credit, criminal, and eviction history providers, aiming for rapid data retrieval and parsing.
A custom rules engine, written in plain Python, would then assess the combined data according to your specific criteria. For instance, logic could be developed to automatically flag an eviction filing within a defined period or to adjust credit score requirements based on application type, like student housing with a qualified guarantor. We have experience using the Claude API for generating plain-English summaries of complex documents, and this same pattern applies to distilling findings from screening reports, making them more accessible for leasing agents.
The final output—typically including a risk flag (e.g., Pass/Fail/Review), an AI-generated summary, and links to source documents—would be written back to custom fields within your PMS. This custom system would be architected for reliability, including detailed logging with tools like structlog and automated alerts for any critical API failures, sent to a designated channel. A typical engagement for a system of this complexity would involve a build timeline of 6-10 weeks, with the client needing to provide API access credentials, data field definitions, and business logic for the rules engine. The deliverables would include the deployed, custom-built system, source code, and comprehensive documentation.
What Are the Key Benefits?
Screening Time Drops From 30 Minutes to 90 Seconds
Eliminate manual data entry and report downloads. A complete credit, criminal, and eviction check is initiated, processed, and logged in your PMS in under two minutes.
Pay Direct API Costs, Not PMS Markups
Integrate directly with screening providers like Checkr. You pay their standard API rates, avoiding the 30-50% upcharge common with built-in PMS screening solutions.
You Get the Full Python Codebase
We deliver the complete source code and deployment scripts in your company's GitHub repository. You have full ownership and can modify the system in the future.
Real-Time Failure Alerts in Slack
If a screening provider's API is down or returns an error, the system automatically sends a notification to your Slack channel with the applicant ID for immediate manual review.
Works With Yardi, AppFolio, and Buildium
We build connectors for your specific PMS. The workflow pushes data back into the native tenant file, so your team does not need to learn another piece of software.
What Does the Process Look Like?
Week 1: System Audit & API Access
You grant us read-only API keys to your PMS and screening provider accounts. We deliver a data mapping document confirming all required fields and business logic.
Week 2: Core Workflow Development
We build the core data validation and API integration logic in Python. You receive a link to a private GitHub repository to observe progress and review code.
Week 3: Integration and Testing
We connect the workflow to a staging version of your PMS. Your team tests the end-to-end process with 10-15 sample applications to verify results and logic.
Week 4: Deployment and Handoff
We deploy the system to production. After a two-week monitoring period, we deliver a final runbook with full documentation, architecture diagrams, and troubleshooting steps.
Frequently Asked Questions
- How much does a custom screening workflow cost?
- Pricing depends on the number of systems to integrate and the complexity of your screening rules. A simple connection between a modern PMS and one screening API is a smaller project than one connecting a legacy system to multiple state and national databases. We scope every project on a fixed-fee basis after a discovery call.
- What happens if a screening provider's API is down?
- The system automatically retries the API call three times with exponential backoff over a 5-minute period. If all retries fail, it flags the application in your PMS with a 'Manual Review Required' status and sends a detailed alert to Slack. Your agents are never blocked and know exactly which applications need attention.
- How is this different from my PMS's built-in screening tool?
- Built-in tools lock you into their chosen vendor, often at a high markup, and use inflexible, one-size-fits-all rules. A custom system lets you use any provider, pay direct API costs, and implement nuanced logic (e.g., different rules for different properties or states). You control the process instead of conforming to the software.
- How is sensitive applicant data handled?
- We do not store personally identifiable information (PII) like SSNs or DOBs. The serverless function processes the data in memory, passes it to the screening API, and then writes the results to your PMS. All data is encrypted in transit using TLS 1.3. The system is designed for minimal data custody, creating a more secure workflow.
- Can this system handle different rules for different properties?
- Yes. The business logic is written in Python, allowing for complex conditional rules. We can define different screening criteria based on property type, state regulations, or even specific unit requirements. This ensures your screening process is compliant and consistent across your entire portfolio, no matter how diverse.
- What if we change our screening criteria later?
- Since you own the code, you can modify the rules engine at any time. The runbook we provide includes instructions for making common changes. For clients without a developer on staff, we offer a flat-rate monthly support plan that covers modifications to business logic, API updates, and ongoing monitoring.
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