In October, the LightBox Fundamentals team met with 30 banks over a three-day seminar to discuss how AI and data automation are reshaping appraisal workflows and decision-making.
The group included Chief Appraisers, Appraisal Directors, Senior Reviewers, and several major appraisal firms — a cross-section of the professionals shaping valuation policy at the largest lending institutions.
While the group discussed many aspects of AI, one key theme emerged: AI extraction is only half the story. The real challenge — and opportunity — is how banks can better connect, validate, and apply appraisal data across their organizations.
Participants explored how to:
- Extract appraisal data more efficiently to eliminate duplicate entries and manual data transfers into internal systems or data lakes.
- Cross-check data consistency from project to project, such as comparing comps, cap rates, and expense ratios across similar 400-unit Class B apartment complexes in the Charlotte MSA.
- “Hydrate” other parts of the bank — credit, origination, risk management, CECL, regulatory compliance — so every team works from the same, trusted playbook.
The discussion was thoughtful and candid. Many banks shared how they’re already experimenting with AI, though all agreed there’s no one-size-fits-all approach to integrating it into existing appraisal and credit operations.
New Revelations
During our session, the LightBox team emphasized that AI and large language model extraction are only the tip of the iceberg when building a truly end-to-end solution — one that not only drives efficiency but also satisfies regulatory expectations.
We asked attendees to imagine two airport experiences.
At Airport A, a traveler lands, collects luggage, orders an Uber indoors (staying warm or cool depending on the weather), and walks 30 feet to the car when it arrives. At Airport B, the traveler waits for a shuttle, rides to an offsite lot, and then waits again outside for an Uber (sweating or freezing depending upon the location). In both cases, the traveler used Uber — but only one experience was seamless.
The point: both workflows use the same technology, but only one was designed with the entire journey in mind. The same holds true for AI.
A basic extraction tool can pull data from appraisals, but it leaves users dragging and dropping files, checking for “AI hallucinations,” and manually distributing results across the bank. It gets the job done, but it’s inefficient and time-consuming — for both the builder and the user.
By contrast, a well-engineered process builds trust through automation, accuracy, and minimal human effort. That’s where LightBox has focused its energy.
The LightBox Way
It became clear through these discussions that AI represents only about 50% of the effort. The other 50% lies in the process — designing an experience that’s seamless, accurate, and regulator-ready.
By the time LightBox went commercial in Q3 2025, the team had built a “conveyor belt” that automatically picks up appraisals from RIMS and Collateral360 as they’re submitted. No drag-and-drop. No tracking what’s been processed.
For banks procuring appraisals outside of LightBox platforms, we offer multiple ways to feed appraisals into our system to make the solution platform-agnostic and fully scalable.
Each document is first verified to confirm it’s an appraisal (not a Phase I ESA or a loan document). Then, extracted fields are tested against a set of guardrails to ensure accuracy and defensibility. Examples below:
- Property Class must be valid
- EGI minus Expenses must equal NOI
- Occupancy can’t exceed 100%
Any data falling outside those guardrails is flagged for human review. We’ve built dedicated teams whose sole responsibility is to investigate outliers quickly to ensure no appraisal sits idle and that banks receive the highest-quality, regulator-defensible data.
Once cleared, the data is delivered to clients via Excel Add-In or API, making it easy to integrate into credit, risk, and decisioning systems.
In short, we’ve designed the process to be as seamless and reliable as the traveler’s experience at Airport A.
Beyond Extraction
As AI continues to evolve, our biggest realization has been that attention to process —not just the algorithm — determines success.
It’s what separates banks that use AI responsibly, accurately, and at scale from those for whom it’s simply a faster version of Google.
In today’s market, many AI providers are long on promises but short on process — lacking the staffing, validation, and customer support needed to truly earn client trust. LightBox has taken the opposite approach, investing heavily in the people, governance, and model oversight that make its solutions regulator-ready and reliable. Our models have been in training for nearly two years and now consistently achieve 95%+ accuracy. Claims of “instant training” or “100% accuracy” may sound appealing, but institutions know to look deeper — to ask how data is validated, how results are reviewed, and who stands behind them.
As appraisal data becomes more central to lending decisions, ensuring that data is clean, consistent, and accessible will be key to achieving every bank’s larger goals of:
- Running a more efficient operation.
- Making better, faster credit decisions.
- Keeping regulators confident in every step of the process.
AI can read the document. But only a complete, well-built process can make the journey effortless.
For more on how banks are turning appraisal data into portfolio-level intelligence, read our latest whitepaper, Unlocking Appraisal Intelligence for Portfolio-Level Insight.
