AI-Powered Mortgage Tool Development
Budget: $30 – $250 USD
Customer Oriented (Mortgage) Matching & Evaluation Tool
Transforming Mortgage Exploration with AI
We need to develop an AI powered conversational chatbot designed to redefine initial stage home financing. Powered by a Large Language Model (LLM), this application moves
beyond static forms, emails exchanges, and phone calls to directly interact with users to deliver instant, personalized mortgage pre-qualification. The system provides a truly
document-free experience, allowing users to explore their options and receive results without the hassle of uploading or submitting any supporting paperwork. The chatbot
guides users conversationally, asking a few essential questions about their financial health. The application analyzes this user-data in real time to generate tailored mortgage
rates and options. All recommendations are highly relevant and specific, with responses that vary dynamically based on the user's unique profile, ensuring a user-centric
experience. Chatbot provides a quick, accurate, and hassle-free path for prospective borrowers to understand their eligibility and potential rates, setting a new standard for
early mortgage insights and simplifying the first critical step toward securing a loan.
1 User or Client (person seeking a home mortgage loan) clicks a link or types URL to open a
chat bot.
Action : underlying domain host/website is invoked via mobile or laptop ?
2 Bot greets the user, and states "Welcome to Company name" - custom based on the host
3 Bot asks personal information from the user like name, mobile number and email
Action: Create /update a new user (as applicable).
4 Bot asks the user to enter the code they received in their email
Action: Authenticate the email
5 Bot asks the user to enter the code they received on the phone via text
Action: Authenticate the phone number
6 Bot requests the user to share their financial information:
* Employment status
* Credit Score (if available)
* List of assets (cash, stocks/bonds)
* Debts ( existing morgage. loans etc)
Action: Bot will ask question one at a time
7 User provides the information - by typing (is not required to provide any docs)
Action: User specific data is stored into a database.(this phase we will capture structured data only)
8 Bot provides the financial options available based on information provided -
for e.g: Based on your income and credit score, you likely qualify for several loan options.
Would you like to see current interest rates or apply now?”
Action: AI-Platform* will leverage existing business rules to provide the results
9 User can add additional information. For eg: other financial team is giving me better rates
or something that the user states as a comparison
Action: This information should be persisted such that the loan officer can look it up using
the user's email when the user reaches out to the loan officer
Bot will provide loan officer contact information to let the user reach out to the mortage team
10 Before session ends, bot prompts the user to check email for seeing the consolidated
financial profile and the financial products recommended
All the user interaction data should be persisted
AI Pipeline - high level dev details
Underlying AI LLM to be selected * - Open AI or Google
Chatbot to receive user query* - via text, web or messaging interface
Input is processed* - use NLP to understand user context and extract the financial details provided
Criteria mapping & Validation* - map user provided information with required data. (essentially ensure user has provided sufficient data to determine eligibility)
Response generation* - user data to be fed into a hueristic based decision engine that will provide options for financial products.
Output Delivery * - present the response through the chat interface
Hueristic Engine
Define eligibility rules* - gather standard businness criteria, convert into simple rules and identify exceptions
Design input schema* - ensure the engine receives and normalizes the data
Create a scoring or weighting logic* - determine user eligiblity
Results with reasons* - engine provides a "user" specific result (integrate with the AI pipeline)
Transforming Mortgage Exploration with AI
We need to develop an AI powered conversational chatbot designed to redefine initial stage home financing. Powered by a Large Language Model (LLM), this application moves
beyond static forms, emails exchanges, and phone calls to directly interact with users to deliver instant, personalized mortgage pre-qualification. The system provides a truly
document-free experience, allowing users to explore their options and receive results without the hassle of uploading or submitting any supporting paperwork. The chatbot
guides users conversationally, asking a few essential questions about their financial health. The application analyzes this user-data in real time to generate tailored mortgage
rates and options. All recommendations are highly relevant and specific, with responses that vary dynamically based on the user's unique profile, ensuring a user-centric
experience. Chatbot provides a quick, accurate, and hassle-free path for prospective borrowers to understand their eligibility and potential rates, setting a new standard for
early mortgage insights and simplifying the first critical step toward securing a loan.
1 User or Client (person seeking a home mortgage loan) clicks a link or types URL to open a
chat bot.
Action : underlying domain host/website is invoked via mobile or laptop ?
2 Bot greets the user, and states "Welcome to Company name" - custom based on the host
3 Bot asks personal information from the user like name, mobile number and email
Action: Create /update a new user (as applicable).
4 Bot asks the user to enter the code they received in their email
Action: Authenticate the email
5 Bot asks the user to enter the code they received on the phone via text
Action: Authenticate the phone number
6 Bot requests the user to share their financial information:
* Employment status
* Credit Score (if available)
* List of assets (cash, stocks/bonds)
* Debts ( existing morgage. loans etc)
Action: Bot will ask question one at a time
7 User provides the information - by typing (is not required to provide any docs)
Action: User specific data is stored into a database.(this phase we will capture structured data only)
8 Bot provides the financial options available based on information provided -
for e.g: Based on your income and credit score, you likely qualify for several loan options.
Would you like to see current interest rates or apply now?”
Action: AI-Platform* will leverage existing business rules to provide the results
9 User can add additional information. For eg: other financial team is giving me better rates
or something that the user states as a comparison
Action: This information should be persisted such that the loan officer can look it up using
the user's email when the user reaches out to the loan officer
Bot will provide loan officer contact information to let the user reach out to the mortage team
10 Before session ends, bot prompts the user to check email for seeing the consolidated
financial profile and the financial products recommended
All the user interaction data should be persisted
AI Pipeline - high level dev details
Underlying AI LLM to be selected * - Open AI or Google
Chatbot to receive user query* - via text, web or messaging interface
Input is processed* - use NLP to understand user context and extract the financial details provided
Criteria mapping & Validation* - map user provided information with required data. (essentially ensure user has provided sufficient data to determine eligibility)
Response generation* - user data to be fed into a hueristic based decision engine that will provide options for financial products.
Output Delivery * - present the response through the chat interface
Hueristic Engine
Define eligibility rules* - gather standard businness criteria, convert into simple rules and identify exceptions
Design input schema* - ensure the engine receives and normalizes the data
Create a scoring or weighting logic* - determine user eligiblity
Results with reasons* - engine provides a "user" specific result (integrate with the AI pipeline)