Vendor Tools in the Finance Stack and What to Check
Finance teams increasingly rely on vendor tools for AI tasks. Your payables automation might be a vendor’s platform. Your forecasting might use a vendor’s model as a service. Your invoice extraction might use an API from a vendor. Evaluating and selecting these vendor tools is a critical control in itself. The wrong vendor choice can introduce risk that no amount of downstream controls can mitigate.
When evaluating a vendor tool for a financial process, start by understanding what the tool actually does. Vendors often describe their tools in aspirational terms. A tool marketed as “AI-powered invoice automation” might do nothing more than optical character recognition followed by a few hard-coded rules. A tool marketed as “predictive analytics” might be fitting a linear regression to your data. Understanding the actual mechanism helps you assess risk. Request a technical overview. Understand whether the tool is deterministic or probabilistic. Understand where data is processed (cloud or on-premise). Understand whether the vendor trains models on your data or uses pre-trained models.
Testing is essential. Most vendors offer a trial or pilot period. Use it rigorously. Run the tool on a representative sample of your data (for example, 500 invoices if you are evaluating an invoice automation tool). Measure its accuracy. If the vendor claims 99 per cent accuracy, test whether it achieves that on your data, in your formats, with your vendors. Do not accept the vendor’s accuracy numbers; measure independently. Also test edge cases. Send the tool an invoice that is deliberately malformed. Send it an invoice in a format that is unusual but legitimate. Does the tool fail gracefully or does it produce nonsensical output? Does it flag that it is uncertain or does it produce confident output that is wrong?
Contracts matter. The vendor contract should specify data handling practices, liability, performance guarantees and what happens if the vendor breaches those guarantees. Many vendors’ standard contracts are one-sided. They exclude liability for model inaccuracy. They reserve the right to use your data for model training. They offer no performance guarantees. Do not accept these terms without negotiation. Your contract should specify: the accuracy the vendor commits to achieve (or at least, how accuracy will be measured), how often the vendor will maintain and update models, how quickly the vendor will respond if the tool fails, what liability the vendor has for errors and what happens to your data if the vendor is acquired or shut down.
Security and compliance are also contractual. Ensure the contract specifies compliance with relevant standards. If you are regulated by the Financial Conduct Authority, ensure the contract states that the vendor will support your compliance. If you handle GDPR-regulated data, ensure the vendor has committed to GDPR compliance and has appropriate Data Processing Agreements in place. If you operate in sectors that require specific data residency (e.g., UK data cannot leave the UK), ensure the vendor’s infrastructure meets this requirement.
Segregation of duties also applies to vendor selection. If a single team member both evaluates a vendor tool and recommends its adoption, you have a risk. Try to have evaluations reviewed by someone independent. Also ensure that ongoing vendor management is owned by someone other than the person who selected the tool. This reduces the risk that problems are not escalated.
Monitoring vendor performance in production is as important as pre-purchase testing. Build a SLA into the contract and track it. If the vendor committed to 99 per cent accuracy, measure whether they are achieving it. If they are not, that is a contract violation and grounds for remediation or termination. Also monitor for security incidents. If a vendor experiences a data breach, you need to know immediately. Some vendor contracts require vendors to notify you within a specific timeframe (e.g., 24 hours). Ensure these notification commitments are in writing.
Finally, have an exit plan. What happens if you need to stop using a vendor tool? Can you export your data? How long will it take to switch to an alternative? Some vendor tools are sticky: switching costs are high because data is locked in proprietary formats. Before committing to a tool, understand how easily you can leave.