00:02In mortgage lending, property valuation plays a major role in both speed and risk management.
00:08But as lending workflows become more complex, organizations are looking for valuation tools
00:12that do more than just generate a number. That is the intention behind Consolidated Analytics
00:18IVAL AVM, an automated valuation model designed to deliver property value estimates supported
00:24by data, modeling logic, and a broader view of valuation reliability. At its core, an AVM uses
00:31real estate data and statistical algorithms to estimate a property's fair market value.
00:36The goal is consistency, scalability, and efficiency. But in today's market, lenders also need
00:43transparency, audit readiness, and greater confidence in how those values are produced.
00:48This is where IVAL has evolved. IVAL's updates through investments in data,
00:53modeling architecture, and governance have resulted in improved accuracy, hit rate,
00:58and responsiveness across markets. Those enhancements reflect the broader evolution
01:03of modern AVMs. More expansive national data coverage, faster data refresh cycles,
01:08and updated modeling techniques help the platform perform across a wider range of property types
01:13and market conditions. One of the product's most notable differentiators is its implementation
01:18of the MISMO Common Confidence Score. IVAL is positioned as the first AVM to market with
01:25a fully implemented, compliant version of that standard. This matters because confidence scoring
01:30has often varied across providers. By using a standardized and auditable framework,
01:36lenders can better understand the probability that a property's actual market value falls within
01:41a defined range of the AVM estimate. In practical terms, this makes valuation outputs easier to explain,
01:48compare, and govern across products, portfolios, and vendors. But IVAL is designed to go beyond the
01:54estimate itself. In addition to core valuation outputs, the platform also provides several early
02:00stage property indicators intended to support faster decision making. These signals can help lenders
02:06identify whether flood insurance may be required, whether a property is currently listed for sale,
02:11or whether there are signs of distress tied to the asset. That broader view may be especially useful
02:17earlier in the loan process when teams are trying to assess risk quickly and determine next steps
02:23without relying on multiple disconnected tools. From an operational standpoint, the value proposition is
02:29straightforward. A single request returns an estimated value, standardized confidence metrics,
02:35comparable analysis, and property-level intelligence. That can help reduce manual review, shorten cycle
02:42times, and improve throughput while keeping valuation workflows aligned with policy and compliance
02:48expectations. For lenders and risk teams, the compliance angle is significant as well. Standardized
02:55confidence measures and a more transparent methodology can support internal governance, examiner discussions,
03:01and audit documentation in ways that proprietary or opaque scoring methods may not.
03:06iVal goes beyond faster valuations. It reflects a broader shift in mortgage technology, from simple automation
03:14towards more transparent, policy-ready decision support. For organizations looking to expand AVM across the mortgage
03:22lifecycle, the question is no longer just whether a valuation can be delivered quickly. It's whether that
03:29valuation comes with enough clarity, context, and confidence to support real lending decisions.
03:34With standardized confidence scoring, broader property intelligence, and modernized modeling,
03:41iVal is designed to help lenders make earlier, more informed evaluation decisions across an increasingly complex
03:47mortgage environment.
Comments