Mortgage fraud risk hasn’t gone away just because workflows are digital. 

Mortgage lenders still face document fraud, synthetic identities, occupancy misrepresentation, and last-minute liabilities popping up between the mortgage application and closing.

This guide is for mortgage fraud managers, heads of risk and compliance, quality control (QC) leaders, and loan originators evaluating mortgage fraud detection tools.

TL;DR

Here are the top mortgage fraud detection software worth trying in 2026:

1. Addy AI

2. CoreLogic/Cotality

3. First American

4. DataVerify

5. LexisNexis Risk Solutions

6. Point Predictive

7. Ocrolus

8. Xactus

9. Equifax

10. SentiLink

11. CertifID

What Is Mortgage Fraud Detection Software?

Mortgage fraud is still a daily risk for financial institutions and mortgage lenders, which is why fraud detection tools remain essential.

Effective fraud detection spans the full mortgage lending process, from application through closing and post-close quality control.

The goal is to identify fraud schemes, such as identity misuse, document tampering, occupancy misrepresentation, and appraisal inflation, before a loan is approved.

When done well, it protects borrowers and investors, keeps mortgage payments sustainable, and helps prevent mortgage fraud without slowing down operations or your loan-processing workflow.

Most mortgage fraud detection software works alongside your loan origination system (LOS) and supports automated underwriting system (AUS) submissions to Desktop Underwriter (DU) and Loan Product Advisor (LPA).

Why So Many Mortgage Teams Are Looking for Fraud Detection Tools

Margins are thin and repurchase risk is expensive, so financial institutions need to catch problems early, not at post-close. A single bad file can erase the profit from a week of clean loans.

Fraud patterns continue to change as more of the application process moves online. Reviewers now sort through PDFs, payroll data, bank activity, public records, and digital identity signals.

Effective fraud detection tools bring these pieces together and highlight what deserves closer review

Borrowers expect fast loan approval, but speed without control increases risk. Modern platforms reduce false positives, move clean files forward, and give analysts time to focus on higher-risk loans.

Compliance standards are stricter. Clear documentation and audit trails are expected, and teams need systems that explain why decisions were made.

Risk doesn’t stop at application. Closing funds are prime targets for wire and payment fraud. 

That's why many lenders upgrade to fraud detection software that works with their LOS and customer relationship management (CRM) platform.

The goal is to catch fraud early and resolve issues before they turn into losses.

Top 11 Mortgage Fraud Detection Tools for 2026

The tools below help lenders detect and prevent mortgage fraud at different stages of the loan process.

Some focus on identity and risk scoring, while others support document review, loan underwriting, and funding protection.

1. Addy AI: Mortgage Review Assistant

Addy AI works as a specialized teammate for fraud and underwriting teams. It reads what humans read in emails, attachments, and financial statements, highlights what matters, and lays out clear next steps.

That means fewer cycles chasing paperwork, faster decisions, and better documentation when a file needs escalation.

Its artificial intelligence (AI) checks loan files against guidelines, flags discrepancies, and extracts data from bank statements, pay stubs, and tax forms.

This helps teams identify potential mortgage fraud early without slowing down loan approvals.

• Best for: Teams that want AI to review emails, bank statements, and PDFs and flag anomalies for fraud review.

• Core capabilities: Addy AI generates summaries of mortgage loan files, highlights unusual transactions, and extracts document data to support fraud checks.

• Integrations/fit: It works alongside your LOS/CRM, supports day-to-day mortgage processing, and is SOC 2 compliant for enterprise security.

Want to see it in action? Book a demo with Addy AI!

2. CoreLogic/Cotality: LoanSafe Fraud Manager

Image source: cotality.com

LoanSafe functions like a risk radar for each loan file, scoring application signals and pointing reviewers to the highest-impact concerns first.

You get consistent visibility into income, occupancy, identity, collateral, and third-party risk, with clear paths to clear findings or escalate when necessary.

• Best for: Mortgage lenders seeking broad, consortium-driven scoring that covers major fraud domains.

• Core capabilities: Alerts for employment and income inconsistencies, occupancy risk, undisclosed debt, straw-buyer indicators, and valuation concerns.

• Integrations/fit: Common in pre-fund and QC workflows; aligns with standard underwriting and post-close review processes.

3. First American: FraudGuard

Image source: dna.firstham.com

FraudGuard consolidates data and analytics into a single review experience, helping teams spot errors and fraud risk without switching between multiple systems.

Reviewers receive organized findings that make it easier to evaluate identity, property, and application-level risk in one place.

• Best for: Mortgage lenders who want report-driven reviews powered by multiple data sources.

• Core capabilities: Identity and property checks, loan application risk analytics, and clear review narratives.

• Integrations/fit: It's used in both retail and wholesale pipelines. Many lenders pair it with verification and QC programs.

4. DataVerify’s DRIVE: Fraud & Risk Mitigation

Image source: dataverify.com

DRIVE serves as an orchestration layer for alerts, variance checks, and audit notes, so teams can manage findings in one place.

Instead of tracking red flags in multiple systems, reviewers see inconsistencies, documentation gaps, and risk indicators within a centralized workflow.

• Best for: Teams that want to standardize alerting, documentation, and evidence capture within a single platform.

• Core capabilities: Configurable rules, automated data comparisons, property risk modules, and support for undisclosed debt monitoring.

• Integrations/fit: DRIVE connects with common LOS setups and supports flexible routing and user permissions to match internal review processes.

5. LexisNexis Risk Solutions: Mortgage Fraud Solutions

Image source: risk.lexisnexis.com

LexisNexis brings identity, device, property, and business intelligence into the mortgage flow, giving reviewers context that raw documents often miss.

The platform's relationship insights help teams understand why a file appears risky and where to focus their investigation.

• Best for: Lenders that need lifecycle screening supported by strong identity and property data.

• Core capabilities: Identity and device intelligence, relationship mapping, valuation analytics, and property risk insights.

• Integrations/fit: Used from application through servicing and supports targeted reviews and deeper investigations when risk indicators appear.

6. Point Predictive: MortgagePass

Image source: pointpredictive.com

MortgagePass screens applications at intake, scoring risk based on consortium patterns and learned behaviors. High-risk files receive early attention, while lower-risk files move faster through underwriting.

This early triage helps lenders spot red flags sooner, prevent fraud, and reduce costs before issues move further down the pipeline.

• Best for: Flagging the riskiest applications as early as possible.

• Core capabilities: Risk scoring with explanations and alerts; tuning to reduce unnecessary stipulations.

• Integrations/fit: Plugs into origination systems and is designed to triage the pipeline at the start of underwriting.

7. Ocrolus: Detect

Image source: ocrolus.com

Ocrolus focuses on the documents themselves, extracting structured data and checking for manipulation or tampering signals. Reviewers see what changed, where it changed, and why it matters to the decision.

It verifies income and assets from uploaded files, which helps lenders prevent fraud without manual review.

• Best for: Document fraud detection and faster verification of financial statements.

• Core capabilities: Document authenticity checks, tamper detection, and reliable data extraction.

• Integrations/fit: Inserts into document review workflows within mortgage and related lending processes.

8. Xactus: Fraud Report X

Image source: xactus.com

Fraud Report X packages risk checks into a clear review experience, with flags that guide analysts from finding to resolution.

It supports both upfront screening and post-close quality control, helping teams identify red flags early and stay compliant with internal and investor standards.

• Best for: Teams that want consistent pre- and post-close reviews with clear next steps.

• Core capabilities: Customizable fraud and error flags, guided alert clearing, and reviewer notes.

• Integrations/fit: Aligns with processing and QC procedures and supports case tracking within existing workflows.

9. Equifax: Undisclosed Debt Monitoring (UDM)

Image source: equifax.com

Equifax handles UDM by monitoring the application-to-closing period and alerting you when new tradelines or credit inquiries appear. This protects your debt-to-income assumptions and reduces last-minute rework that can delay a clear-to-close.

Continuous monitoring helps lenders catch undisclosed debt before funding, which can protect loan quality.

• Best for: Mortgage lenders who need continuous credit monitoring to prevent fraud and reduce credit risk before closing.

• Core capabilities: Daily checks for new inquiries and tradelines with actionable alerts when material credit changes occur.

• Integrations/fit: Runs as a standalone solution or within common LOS ecosystems and is easy to include in pre-close checks.

10. SentiLink: Synthetic/Identity Risk

Image source: sentilink.com

SentiLink evaluates whether an identity looks real, manipulated, or synthetic, then explains the drivers so analysts can make fast, confident calls. It’s especially useful when thin-file or mismatched data slows manual review.

The platform uses advanced analytics and identity intelligence to highlight patterns that may signal elevated risk.

• Best for: Screening identity and synthetic-ID risk at the application.

• Core capabilities: Risk scores with context, tools that aid investigation and decision-making.

• Integrations/fit: Offers application programming interface (API) and web app options, and is widely used by banks and credit unions.

11. CertifID: Wire/Closing Protection

Image source: certifid.com

CertifID secures the money movement side of a transaction, verifying parties and wiring details before funds are sent. This added layer of verification helps lenders and settlement teams reduce exposure to wire fraud at closing.

• Best for: Protecting payoff and closing funds from wire fraud and helping teams combat fraud at the funding stage.

• Core capabilities: Party and account verification, secure instructions, and incident response playbooks.

• Integrations/fit: Used by title and settlement teams, lenders, and law firms, with clear handoffs near closing.

Choosing the Right Fraud Prevention Tool by Scenario

Every mortgage team operates differently, so the right fraud detection tool depends on your workflow and risk profile.

• Retail vs. wholesale: In wholesale channels, prioritize broker diligence signals, occupancy checks, and relationship mapping. In retail, focus on document authenticity, income reasonability, and fraud prevention that reduces back-and-forth with borrowers.

• Small credit unions vs. enterprise banks: Smaller teams need strong default settings, AI-assisted summaries, and low admin overhead. Enterprises often want granular thresholds, custom routing, and analytics that evaluate trends within high-volume transactions.

• Docs-heavy vs. digital flows: If your pipeline is PDF-heavy (bank statements, paystubs), emphasize document AI and detect fraud capabilities in unstructured data. In digital-first flows, lean into device/identity intelligence and synthetic identity fraud patterns.

• Origination vs. servicing/post-close QC: Origination teams prioritize early detection and speed. Servicing and QC teams benefit from historical data analysis and tools that reduce repurchase exposure.

De-risk your pipeline and strengthen decisions from application to funding. Book a demo with Addy AI today!

Implementation Tips That Cut False Positives (and Hours of Rework)

Implementation quality influences results as much as the tool itself. Clear rollout steps reduce confusion and improve performance.

• Baseline your key performance indicators (KPIs): Track false-positive rate, true-positive catch rate, average time-to-first-touch, and case resolution time before deployment.

• Pilot in 30 days: Start with one or two channels, such as retail purchase and third-party origination (TPO). Enable AI summaries to give reviewers faster context during file review.

• Tune thresholds weekly: Adjust high-volume alerts up or down based on precision and recall. Keep a changelog so the audit retains context.

• Triage by impact: Prioritize alerts linked to repurchase risk, income misrepresentation, occupancy issues, or multiple loans before lower-impact findings.

• Operationalize SAR readiness: Standardize evidence capture, narrative templates, and handoff timing so you’re not scrambling if a case crosses the threshold for a suspicious activity report (SAR).

Careful execution helps mortgage teams prevent fraud without overwhelming reviewers.

Strengthen Mortgage Fraud Detection With Addy AI

Addy AI helps mortgage teams detect fraudulent activity earlier in the loan process. It reviews emails, attachments, and financial documents the same way a processor or underwriter would, then highlights inconsistencies that deserve a closer look.

Addy AI helps teams catch issues before they turn into costly problems, such as early payment default.

Document AI cross-verifies information between applications, income documents, and financial statements to confirm the data matches throughout the file.

Minor discrepancies in assets and employment details can signal a bigger risk. Addy AI brings those details forward so teams can investigate quickly and document decisions clearly.

Addy AI integrates with your LOS, CRM, and point-of-sale (POS), along with common productivity tools your team already uses. It’s SOC 2 Type 1 compliant and meets enterprise security standards.

If you want reliable fraud signals and faster file reviews, book a demo with Addy AI today!

FAQs About Mortgage Fraud Detection Tools

How to detect mortgage fraud?

Mortgage fraud is detected by identifying inconsistencies in a loan application before borrowers obtain mortgages under false information. 

Lenders review income documents, assets, credit activity, and identity details to flag suspicious patterns.

What is the best fraud detection tool?

There isn’t one single best fraud detection tool for every lender. Some lenders need document-focused fraud detection, while others prioritize identity or credit monitoring.

Many teams combine tools, including platforms like Addy AI, to strengthen coverage without slowing approvals.

What tools do banks use for fraud?

Banks use a combination of identity verification platforms, credit monitoring systems, document analysis tools, and wire fraud protection services. Larger institutions often layer multiple systems to monitor risk throughout the loan lifecycle.

In the mortgage industry, these tools may include automated document review solutions such as Addy AI, along with third-party identity and credit risk providers.

What are the four types of mortgage fraud?

The four common types of mortgage fraud are income fraud, occupancy fraud, identity fraud, and appraisal fraud. Income fraud involves overstating earnings or assets.

Occupancy fraud occurs when a borrower falsely claims a property will be owner-occupied. Identity fraud includes stolen or synthetic identities, and appraisal fraud involves misrepresenting a property’s value.