CoStar responded Wednesday by calling the allegations “highly misleading” and questioned D.E. Shaw’s motivations, noting the investor holds significant stakes in direct competitors.

“If D. E. Shaw is worried about transparency, it should start with itself,” the company stated. “D.E. Shaw has never disclosed its economic exposure to CoStar Group, or even if it is a net long investor.”

CoStar offered further detail on why it believes D.E. Shaw’s campaign may be driven by conflicts of interest — highlighting the hedge fund’s investments in CoStar competitors.

“Public filings suggest D. E. Shaw owns just 0.22% of CoStar Group’s common stock, but almost 4x that value in CoStar Group competitors who would directly benefit from D. E. Shaw’s push for us to abandon Homes.com and eliminate the fastest growing residential real estate platform in the industry,” the company said.

Debate background

The dispute stems from CoStar’s heavy investment in Homes.com and whether it is creating or impeding long-term value and shareholder wealth.

D.E. Shaw estimates CoStar will have spent more than $3 billion on Homes.com by the end of 2026.

The firm also accused management of stopping the disclosure of key operating metrics — such as net new bookings for Homes.com.

“During the most recent earnings call, when analysts specifically requested segment-level net new bookings data, management declined to provide the information,” D.E. Shaw’s letter said. “Investors took notice: these puzzling moves contributed to a 9% decline in the Company’s stock price the following day — destroying nearly $2 billion of shareholder value.”

CoStar defended its reporting practices Tuesday — saying segment disclosures were realigned from geography-based to product-based segments to better reflect operational structure.

“Our new segment disclosure actually offers more transparency by providing audited revenue, EBITDA, Adjusted EBITDA and margin disclosures for both the Residential and Commercial segments in our recent 10-K, as well as continuing to provide disaggregated revenue disclosures,” the company stated. “Investors should expect similar Homes.com disclosures on our earnings calls that CoStar Group has always provided to stockholders.”

CoStar Q4, full year net income drop

During the referenced Q4 earnings call, CoStar Group CEO Andy Florance highlighted growth across the Homes.com network.

The platform logged more than 2.1 billion visits and averaged 100 million monthly unique visitors in 2025, according to Comscore, while January organic traffic rose 134% year over year.

“We feel we have achieved a good balance between SEM, SEO and direct traffic,” Florance said. “This allows us to optimize SEM for quality traffic and leads, not just pure quantity.”

Florance added that engagement improved — with session duration rising to about four minutes and 30 seconds and bounce rates falling from 63% in January 2025 to 41% in January 2026.

Lead volume increased 48% annually in January, with leads for Homes.com member agents up 187%.

Despite improved metrics for Homes.com, CoStar’s net income fell from $60 million a year ago to $47 million for Q4 2025.

For the full year, as revenue rose 19% annually to $3.25 billion, net income fell to $7 million from $139 million in 2024.

CoStar has argued that abandoning current Homes.com strategy would inflict “irreparable harm” on its platform and investors.

HMDA reporting season has just wrapped as financial institutions were required to submit detailed data from the previous calendar year’s mortgage applications and loans to their regulators by March 2nd. But for compliance professionals at community banks, the work doesn’t stop there. 

HMDA reporting has become less about “checking the box” and more about defending data under scrutiny year-round. Manual review, scattered systems, and last-minute validation place an undue burden on lending and compliance operations.

In this article, we share how automation supports verification and exception handling across the loan lifecycle, keeping your institution prepared and compliant all year long.

Common issues cited in HMDA compliance

Reg C of the Home Mortgage Disclosure Act (HMDA) requires financial institutions to collect specific data points on all applications, originations, and purchases of “covered loans.”

HMDA and fair lending scrutiny has increased in recent years as regulators have placed increased pressure on financial institutions to deliver clean data with leaner teams. As a result, risks tied to post-approval document errors and manual review are growing. The Federal Reserve named HMDA/Reg C violations as the top-reported issue for state member banks in 2024, representing 38% of all cited consumer violations. Furthermore, failing to provide sufficient data for one or more HMDA data fields was the most common issue cited by the FDIC.

It’s true that the current administration in Washington has prioritized a deregulation agenda for financial services, signaling that compliance relief is on the way for community financial institutions in 2026. For example, the Consumer Financial Protection Bureau (CFPB) recently announced a slight increase in the minimum asset threshold for HMDA reporting, from $58 million to $59 million.

But this doesn’t mean regulatory oversight is going to decline in 2026. That’s because regulators rely heavily on HMDA data to support a range of examinations and investigations, including CRA evaluations, fair lending exams, and long-term research projects and policy initiatives.

Community banks face several challenges

When HMDA data quality declines, it has downstream effects on safety and soundness, fair lending, and supervisory control. Therefore, any perceived slippage across the industry can be expected to result in pushback from regulatory examiners on governance and controls.

HMDA compliance and reporting presents community banks with a range of challenges. These include ensuring that required data is reported with integrity and accuracy, maintaining comprehensive quality checks throughout lending processes, and having systems in place to prove that these controls and checks are working properly.

When data is disconnected and scattered across multiple areas of the bank, including email inboxes, manual spreadsheets, and paper documents, it’s a recipe for error and inefficiency. Your bank’s credibility with examiners is at risk if all required data is not accurate, organized, and readily available to produce on demand.

4 Ways automation enhances HMDA reporting

As the regulatory landscape continues to evolve, banks must adapt their operations to comply with ever-changing requirements. Automation has emerged as a key catalyst for modernization, helping institutions navigate this challenge efficiently. Here are four ways automation helps ease the compliance burden in HMDA reporting:

1. Reduces risk and rework: HMDA errors love to hide in property location, census tract, and other geographic fields. Automation can help minimize the occurrence of such errors by auto-validating property location inputs through address normalization, demographic data, credit scoring, and consistency checks. By flagging missing or suspicious values at loan origination instead of year-end, automation can minimize rework and reduce risk when it matters most.

2. Supports exception-based workflows: To streamline HMDA reporting, it’s time for banks to shift from full-file checking to exception-based reviews. By focusing only on those files with missing or inconsistent data, compliance departments can effectively reduce the time and manual effort spent on largely redundant review processes. Automated exception-based workflows also enable compliance professionals to initiate compliance reviews more frequently, enhancing data integrity and quality.

3. Creates a single source of truth before submission: Another way to ensure data integrity is by locking down a single, authoritative dataset for HMDA report validation, internal reviews, and final submission. Automation is invaluable in maintaining such a single source of truth and preventing overrides unless an exception reason and evidence are provided.

4. Enhances quality control: Stronger quality control (QC) leads to cleaner data and greater efficiency. This boosts examiner confidence and creates a positive ripple effect across multiple areas of the organization, including compliance and operations. Automation serves as a powerful enhancer of QC by reducing opportunities for data entry errors and manual missteps.

Maintaining compliance in a changing world

In the world of banking compliance, the one constant is change. Community banks must prepare today to meet the requirements of an ever-evolving regulatory landscape that prioritizes data integrity, consumer protection, and institutional safety and soundness. Automation can help banks maintain secure, efficient lending operations—empowering growth in a competitive and dynamic environment.

John Roper is the Chief Revenue Officer at Continuous.
This column does not necessarily reflect the opinion of HousingWire’s editorial department and its owners. To contact the editor responsible for this piece: [email protected].

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Manually updating spreadsheets. Dealing with paper jams in the printer. Remember what office life was like in 2005? If you’re feeling nostalgic, you can find many of the same practices still in place in the investor’s reporting offices of loan servicers today. 

But why haven’t these offices evolved with changing technology? 

It’s partly cultural, but it also reflects how the industry has developed over time. Many of our systems were never designed with data transparency or real-time automation in mind – some servicing platforms even predate the invention of Excel.

When I started in the mortgage industry in the 1990s, data management remained largely manual – we were still using paper ledgers and basic spreadsheets. Excel began gaining traction as companies transitioned from DOS-based to Windows-based systems. At the time, it was revolutionary, giving us far more capability and flexibility than we’d ever had before.

That revolution changed how people worked. Over time, nearly every department learned how to improve their processes, build automation, and quickly solve problems using Excel. These practices became a natural way of working and eventually turned into part of the very culture of investor reporting.

Fast forward 15 to 20 years, and many of the same people who relied on those methods are now industry leaders who’ve passed that knowledge and mindset to the next generation, ensuring that spreadsheets remain embedded in our operational DNA. 

The comfort of visibility and the cost of overreliance 

There’s also an element of trust in play. People feel more comfortable with what they can see and verify, even if it’s inefficient. A spreadsheet, after all, gives users full visibility into their data. 

But that transparency can be deceptive. We’ve all seen how a small formula error affecting just a fraction of a percent can become a costly problem when applied to thousands of rows of data. Some spreadsheets have become so complex that, even though you can technically trace each formula, they exceed our ability to truly understand them.

The challenge is helping organizations recognize that automation doesn’t mean losing control. It means transferring control, shifting from manual processes with limited data integrity and capability to systems that ensure accuracy, visibility, and simplicity. True automation doesn’t obscure the data; it clarifies it, freeing teams to focus on what truly matters.

While Excel still provides some level of scalability, it only scratches the surface of what’s possible with modern, managed systems.

Why outdated workflows persist

So, what keeps these legacy workflows alive? In my experience, the biggest culprits are data fragmentation, limited system interoperability, and dispersed systems of record. 

Servicing data lives across multiple platforms – core servicing, accounting, cash management, investor data, and client-specific reporting templates – but these systems don’t communicate cleanly, or sometimes even at all. Even when technology vendors promise automation, their solutions can often sit on top of inconsistent data. As a result, teams still end up manually reconciling the results.

There’s also an understandable resistance to risk. In investor reporting, even a small error can have regulatory or reputational consequences. Many organizations choose certainty over efficiency, at least until they see that modern automation can deliver both.

And then there’s a cost. Excel is affordable, and most servicers don’t recognize the hidden cost of poor quality in investor reporting. Many servicers still view investor reporting as a purely external obligation – a compliance deliverable, not a strategic asset. But that mindset overlooks a major opportunity. 

By harnessing the power of all the data collected through investor reporting, servicers can uncover valuable insights to improve upstream and downstream operations, from loss mitigation and foreclosure to cash management and loan boarding. The ROI becomes clear when organizations view investor reporting as an internal catalyst for improvement, not just an external requirement.

Using AI to replace manual processes

Servicers can employ expert systems enhanced by AI that ingest and analyze hundreds of reports from the servicing platform, investor records, and other related data sources in parallel. These systems use comprehensive reconciliation, triangulation, and data validation to detect even the smallest anomalies, effectively flagging issues that often go unnoticed or require significant manual rework when identified by traditional processes.

Unlike tools that automate only surface-level tasks, these new expert systems that are enhanced by AI use advanced, rules-based decisioning to automatically resolve nearly 80% of exceptions and edits. Reporting analysts can therefore shift their focus to more complex or high-value research, knowing that the data remains clean, reliable, and aligned across systems.  AI driven insights suggest potential research paths based on the patterns they’ve detected. This guidance not only increases efficiency but also leads to more consistent and accurate conclusions.

Quality results require quality data

High-quality automation starts with high-quality data. Too often, organizations invest in new systems without addressing underlying data issues. And that’s where breakdowns occur.

Automated platforms should strengthen, not replace, human oversight. A well-designed system helps identify and resolve inconsistencies by triangulating information across multiple data sources. While that adds some initial effort, it creates a critical feedback loop: operational teams can pinpoint and correct data issues or improve processes at the source, driving greater efficiency and accuracy over time.

As the underlying data becomes more reliable, automation delivers even better results. Cleaner data produces clearer feedback, and clearer feedback further improves data quality, creating a positive cycle that compounds over time.

This ripple effect goes well beyond investor reporting. Servicers can leverage such feedback to drive operational excellence across the broader organization. As data integrity improves, the entire servicing operation benefits.

How automated systems can earn trust 

Ultimately, automation succeeds or fails on one factor: trust.

Once data is consistent and validated, organizations can more confidently introduce automation. While a system can technically operate on bad data, trust in its outputs will erode quickly when the results aren’t reliable.

Trust is earned through transparency, traceability, and performance. Teams need clear visibility into the data used, every processing step taken, and the reasoning behind each result. Over time, consistent efficiency gains, auditability, and alignment with user judgment reinforce confidence – making automation not just accepted but relied upon.

Modernization isn’t about abandoning the tools that got us here; it’s about evolving how we use them. Spreadsheets gave this industry its first taste of digital empowerment. But the same trust and visibility that made Excel revolutionary have also made it difficult to move away from.

As we enter a new era of intelligent automation, the mindset shift is already underway. Automation isn’t about taking control from people. It’s about giving them better tools. Tools that ensure accuracy, improve oversight, and free them to focus on higher-value work.

When we can see automation as an extension of our expertise rather than a threat to it, that’s when real progress begins. By eliminating spreadsheet-based exception management and reducing reliance on end-user computing tools, expert systems become foundational solutions, strengthening current workflows while positioning organizations for more advanced AI adoption in the future.

Jeff Choi is the COO at PMSI.
This column does not necessarily reflect the opinion of HousingWire’s editorial department and its owners. To contact the editor responsible for this piece: [email protected].

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California’s SB 1157 has made a significant impact on the lives of tenants in subsidized housing developments. This groundbreaking state-specific law mandates that landlords who own or operate such properties offer their tenants the option to have their rental payments reported to credit bureaus.

For the past two years since the law went into effect, residents of these housing developments have had the opportunity to opt into rent reporting annually. While this initiative is state-specific for now, it could very well become a federal requirement in the near future.

Rent payments are often one of the most substantial monthly expenses for individuals, typically accounting for 30% to 40% of their income. Despite this financial commitment, traditionally, renters have not seen their timely payments contribute to their credit history.

Unlike homeowners who build their credit with mortgage payments, renters have been left without this avenue to enhance their credit profiles.

Recognizing the vital role of rent payments in individual financial success, Fannie Mae and Freddie Mac have recently started considering these monthly expenses as part of borrowers’ credit histories. This development has paved the way for private sector solutions.

The feature facilitates secure online rent payments that can be automatically reported to a credit bureau, bridging the gap for consumers who could not directly report on-time rent payments.

Building a credit history through rent payments can significantly impact loan approvals, especially for those with limited credit history, facilitating this process and empowering renters to achieve their financial goals, whether it’s securing a loan, purchasing a vehicle, or buying a home.

Rent payment reporting also has the important potential to level the playing field and address racial disparities in the housing market. Historical inequities have often limited access to credit for communities of color, with discriminatory practices leaving people of color with no choice but to often explore riskier alternatives. This has resulted in lower credit scores on average for people of color, according to research by the Urban Institute Initiative.

To combat these persistent inequities, there have been efforts to include alternative data sources like rental payment history in credit scoring. Rental payments have also been shown to be strong predictors of mortgage performance, but the majority of rent payments are not reported to credit bureaus and are thus traditionally not reflected in credit scores.

Incorporating rental payment data into mortgage underwriting has the potential to ultimately expand access to homeownership, thereby reducing the gap between black and white households. Both private companies and the federal government have taken steps to advance the use of rental payment data, but there is more work to be done.

Policymakers and regulators can consider a number of steps to create more equity in this space, including:

Incentivizing rent reporting:

According to the Urban Institute Initiative, fewer than 5% of renter households have their rental payment history on file with the major credit reporting agencies, and these data primarily come from missed, rather than on-time, payments. Regulators and policymakers can change the incentive structure to encourage rent reporting. 

Encouraging lenders to accept consumer-permissioned data:

The primary barrier to increasing the use of consumer-permissioned data is lender uncertainty, exacerbated by a lack of data standardization. Rental payment history can vary, depending on factors such as utility inclusion and multiple household contributions. Updating regulatory guidance to clarify expectations would make lenders more comfortable with extending mortgage financing to a wider range of households.

More consistent rent payment reporting can help pave the way for a more inclusive financial future, regardless of their race or economic background. It’s time to give credit where credit is due and make rent payment reporting a standard practice.

Michael Lucarelli is the CEO and Co-Founder of RentSpree.

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