Private lenders evaluate risk every day. That includes scrutinizing collateral, borrower experience, and the path to repayment. The software handling borrowers’ financial information deserves the same discipline.
AI makes it possible to describe a business process and quickly see a dashboard, borrower portal, or crm tool take shape. For teams trying to eliminate repetitive work, that is an exciting opportunity. It also creates an important decision point: when is an application ready to handle real customer data and real money?
At Sekady, we believe the answer depends on the integrity of the information and the controls supporting each transaction. A convincing demonstration is only the beginning.
When a prototype becomes a business system
“Vibe coding” commonly describes creating software through prompts to an AI tool, often accepting the results without thoroughly reviewing the underlying code. It can make experimentation accessible to people who have never developed software. The risk increases when that experimentation moves into production without qualified engineering and security oversight.
AI can also support disciplined software development. Human ownership, code review, independent testing, and clear approval processes remain essential. The quality of the process around the code determines whether the application is ready for real-world use.
A successful test showing that a borrower can submit a draw does not establish whether another borrower can view it, whether an employee can bypass approval, or whether a compromised account can change payment instructions. Those questions require deliberate testing.
A lending file can contain tax documents, personal guarantees, and vendor banking details. Uploading these records to an unapproved AI service or giving a prototype access to a production database can expand their exposure. That decision deserves the same scrutiny as authorizing a disbursement.
Data integrity protects the decisions behind every dollar
Lending systems must protect confidentiality while preserving data integrity: accurate, complete information with a dependable record of its source and any changes. Protecting confidentiality alone cannot prevent an incorrectly extracted amount from driving a funding decision.
Consider a hypothetical draw application that imports the same invoice twice, assigns an inspection to the wrong project, or allows new bank details to take effect without independent verification. These failures can cause losses even when no outsider steals a file.
AI can compound the problem if its output becomes approved data automatically. An incorrectly extracted invoice amount might flow into budget calculations, borrower reports, and payment instructions. A controlled workflow should preserve the source document, identify who reviewed the information, and record what was ultimately approved.
That history matters when a borrower disputes a balance, an investor questions a disbursement, or a lender needs to reconstruct what happened.
What a breach could cost your business
IBM’s July 2026 release of its Cost of a Data Breach findings reported an average breach cost of $4.99 million globally and $6.3 million in financial services. The study covered 602 organizations. These are averages across participating organizations, not forecasts for an individual private lender or estimates of losses specifically caused by vibe coding.
The financial consequences can include investigation, legal support, system restoration, customer notification, and lost business. For a lender, disruption could also delay draws, divert staff from originations, and strain borrower or capital-provider relationships.
Even a smaller loss deserves attention. As a hypothetical example, a $250,000 uninsured loss would require $1.25 million in additional revenue to offset if 20% of that revenue became operating profit. That calculation excludes any lasting damage to customer relationships.
Insurance should be part of the discussion before deployment. Ask your broker to review coverage for data breaches, business interruption, and fraudulent payments, including limits, exclusions, and conditions. An internally built application should be part of that conversation; having a policy does not establish that every resulting loss is covered.
What lenders should require before going live
Start development with synthetic data. Before introducing real borrower records, approve the tools involved and understand where information is sent, who can access it, how long it is retained, and whether it can be used for model training. These details depend on the provider, product, settings, and contract.
Require qualified technical review. Test permissions across borrower and employee roles, protect credentials, use multifactor authentication, and verify that sensitive information is encrypted in storage and transit. Payment changes and disbursements need explicit approval controls.
Test the situations most likely to expose weaknesses: duplicate invoices, changed bank details, failed integrations, interrupted payments, and attempts to access another borrower’s records. Confirm that the system preserves approval history and that backups can actually be restored.
Assign ongoing ownership. Someone must maintain the application, address newly discovered vulnerabilities, monitor unusual activity, and lead incident response. Security needs ongoing attention throughout the life of the application.
Choosing a vendor with the right controls
When evaluating a vendor, ask them to demonstrate how the application and its data are protected. Being “behind lock and key” should include multifactor authentication, permissions tied to job responsibilities, and controls that prevent unauthorized access to another borrower’s or customer’s records. These protections should extend to the underlying data and connected systems.
Confirm that sensitive data is encrypted in storage and transit, bank-detail changes receive independent verification, and protected audit logs record who accessed, changed, or approved critical information. Ask how the vendor tests security, installs updates, removes departing employees’ access, and limits support personnel’s access.
Review current independent security assessments, including the scope and findings of a SOC 2 report. Ask how backups, incident response, and recovery are tested, and how records are retained, exported, and deleted. Choose a vendor that can demonstrate its practices and explain which controls it operates and which your team must configure or perform.
Sekady’s approach to responsible innovation
Sekady’s work spans construction draw management, inspections, fund control, and payments. Our platform incorporates role-based access and audit trails, and we have invested in an independent SOC 2 audit. Those investments reflect the responsibility that comes with handling financial information and supporting money movement.
We believe AI can help lenders reduce administrative work and improve access to useful information. Its value grows when people can verify the information it produces and remain accountable for the decisions that follow.
A responsible build-or-buy comparison includes engineering oversight, security, ongoing maintenance, and incident response. Lenders should understand those commitments before connecting an application to live data.
The return on technology should include confidence that borrower information is protected, payment decisions are traceable, and the business can keep operating when something goes wrong.