Top 10 Mortgage Chatbots: Use Cases & Examples
Banks that keep customers happy grow deposits 85% faster than their competitors. Loan processing directly affects how satisfied clients feel about their bank1 . Chatbots can handle mortgage-related tasks around the clock, simulating what mortgage brokers typically do.
We examine 10 vendors and their practical applications, as well as United Wholesale Mortgage’s implementation.
Top 10 mortgage chatbots
Vendor | Average Rating | Mortgage Specific Feature | Low/ No-code Bot Builder |
|---|---|---|---|
4.8 | Lead-gen & FAQ bot templates that can be implemented | ✅ | |
4.4 | Financial-services pack with real-time chat translation | ✅ | |
Makerobos | 4.9 | “Mortgage Lenders Chatbot” template: borrower intake & application routing | ✅ |
Capacity | 4.7 | AI automation platform for mortgage origination, servicing, QA, internal workflow automation | ✅ |
TARS | 4.6 | Finance/mortgage application templates for lead capture & pre-qualification | ✅ |
Haptik | 4.5 | Mortgage-focused platform with EMI calculators, loan-status tracking, multilingual support (130 + languages), pre-built workflows for origination & servicing | ✅ |
ServisBOT | 4.4 | “AI Agents” for mortgage servicing, origination, compliance & voice/chat | ✅ |
nCino Mortgage Suite | 4.5 | Gen-AI co-pilot Banking Advisor | ❌ |
BNTouch MAIA | 4.3 | Embedded gen-AI Q&A chatbot | ❌ |
Botsplash | 4.3 | Omnichannel chat and multi-agent hand-offs | ✅ |
*Apart from our sponsors, the table is sorted by rating score.
What Mortgage Chatbots Actually Do
These AI systems handle loan-related conversations through text or voice. They’re built to perform tasks that mortgage professionals typically handle. Banks deploy them across their website, mobile app, and messaging platforms like WhatsApp to create consistent customer interactions.
The technology falls under the broader umbrella of conversational banking, where financial institutions automate client communications.
Top 5 mortgage chatbot use cases
1. Document Collection
Mortgage lenders operate under strict regulations worldwide. When someone applies for a loan, they need to prove their identity with Social Security and tax ID numbers, show they can afford the payments through income and wealth documents, and sign agreements detailing payment terms and interest rates.
Before chatbots, customers visited offices with stacks of paper documents that brokers manually digitized. Neither side found this efficient.
Now banks pull information digitally through chatbots, connecting to data aggregators and third-party sources. Customers upload images, PDFs, and other formats directly. Lenders can track everything for compliance and auditing without handling physical paperwork.
2. Document Verification
Once documents arrive, chatbots organize them by category: personal information, financial data, and loan purpose details. Using natural language processing, they pull out specific data points: applicant names, salary figures, and employer information.
When something’s missing or doesn’t match up, the bot flags it immediately. This catches fraudulent applications early and tells applicants whether their documentation is complete. If everything checks out, the bot confirms the application is ready to process.
3. Mortgage Policy Recommendations
Brokers typically help clients find suitable mortgage products. Chatbots now function as mortgage calculators, refinance calculators, and affordability tools.
They gather details about financial goals (like lowering monthly payments), income levels, existing mortgage balance, and property value and location. Based on this information, they suggest appropriate mortgage or refinance options.
4. Lead generation
First-time homebuyers often feel uncertain about choosing a lender. Experienced buyers already know what they’re looking for. Chatbots analyze conversations to identify where prospects are in their decision-making process.
They can handle far more simultaneous conversations than human agents, collecting customer data at scale.
5. Payment Deferment Requests
During economic downturns, customers may need to delay mortgage payments temporarily. Government policies and lender programs sometimes allow this, but processing large volumes of deferment requests strains operations.
Chatbots collect the necessary documentation from customers seeking payment deferments, automating what would otherwise require significant staff time during crisis periods.
Real Example: United Wholesale Mortgage’s ChatUWM
United Wholesale Mortgage launched ChatUWM in May 2024. The tool sits inside their broker portal and serves over 13,000 independent mortgage brokers who sell UWM loans2 .
Instead of scrolling through PDFs or calling support, brokers type questions about guidelines, pricing, and eligibility. The LLM-powered search returns answers from the lender’s knowledge base in seconds3 .
An October 2024 update added document analysis. Brokers can drag and drop loan documents, pay stubs, appraisal reports, and tax returns in PDF format. They ask questions in plain language: “What seller credits are shown on page 3?” or “Does this borrower have sufficient reserves?” The bot reads the document and provides answers with links to the relevant pages.
Within five months, UWM tracked 25,000 external users generating over 400,000 prompts, averaging 3,000 daily4 . Brokers report they can quote products faster. UWM markets it as reducing guideline lookups “from minutes to seconds.”
Why are mortgage chatbots important now?
Mortgage chatbots have shifted from optional to necessary infrastructure for lenders facing three pressures:
- Thin profit margins: Independent mortgage banks lost $1,056 per loan in 2023, then made $443 per loan in 2024, with Q1 2025 showing a slight profit decline. With margins measured in basis points, reducing processing time directly affects the bottom line5 .
- Digital expectations: Only 9% of American consumers prefer branch visits, while 55% use mobile banking apps as their primary channel. A 2025 Veterans United poll found 32% of homebuyers use AI tools, and 22% specifically use them to compare mortgage lenders6 . Chatbots meet the “instant-response” expectation without maintaining 24/7 call centers.
- Workforce efficiency: Despite 2023 layoffs, two-thirds of lenders listed “talent management and cost-cutting” as top 2024 priorities. IBM’s 2024 benchmark shows AI chatbots can cut customer service expenses by up to 30%7 .
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Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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