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Description
Monsoon utilizes advanced machine learning-based underwriting models to uncover ongoing trends that allow for the prediction of future repayment behaviors based on extensive borrower data, which includes credit bureau information, bank statements, demographics, location data, and, when available, alternative data sources. These identified trends are distinct for each lender, reflecting their specific methods in borrower sourcing, underwriting processes, and collection strategies. The machine learning system continuously “learns” from the historical portfolio and application-level data of each lender, integrating this with repayment data for every borrower within that portfolio. Monsoon CreditTech’s innovative technology is currently employed by 24 lenders who operate across diverse portfolios in both Retail and MSME lending sectors. In the Retail lending space, various loan products are supported, including Consumer Durable loans, Personal loans, loans for Four or Two-Wheelers, Home loans, and Credit Cards, thus catering to a wide array of borrower needs and financial situations. This adaptability in product offerings allows lenders to better serve their clientele while minimizing risk and optimizing repayment efficiency.
Description
A specialized CRM and customer engagement solution designed to foster growth and build loyalty among contemporary lenders and financial organizations. As housing prices reach unprecedented heights, interest rates climb, and inventory remains scarce, many borrowers find themselves uncertain about how to realize their aspirations of homeownership. Even with a notable decline in mortgage applications, owning a home remains a crucial investment in the United States. In a conversation with Global Markets Reporter Jill Malandrino, Joe Welu, the Founder and CEO of Total Expert, discussed strategies for lenders to maintain engagement with prospective homebuyers and support their dreams of owning a home. The Total Expert platform is meticulously crafted to cater to the specific requirements of lending and financial institutions, ensuring that digital interactions are as impactful as traditional face-to-face experiences while emphasizing scalable personalization. This approach not only enhances customer relationships but also positions lenders to effectively navigate the complexities of today's housing market.
API Access
Has API
API Access
Has API
Integrations
Capacity
Cyclr
Denim Social
Facebook
Insider One
LinkedIn
X (Twitter)
Integrations
Capacity
Cyclr
Denim Social
Facebook
Insider One
LinkedIn
X (Twitter)
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$69 per user per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Monsoon CreditTech Technologies
Website
monsoonfintech.com/products/
Vendor Details
Company Name
Total Expert
Website
totalexpertinc.com
Product Features
Insurance Underwriting and Rating
Broker / Agent Portal
Carrier Upload
Commercial Lines
Comparative Insurance Rating
Customer Portal
For Casualty Insurance
For Health / Medical Insurance
For Life Insurance
For Personal Insurance
Multi-State
Multiple Line Rating
Loan Origination
Amortization Schedule
Audit Trail
Closing Documents
Compliance Management
Customer Database
Digital Signature
Document Management
Fee Management
Loan Processing
Online Application
Product Features
Real Estate Agency
Calendar Management
Client / Property Matching
Client Database
Commission Management
Contact Management
Contract Management
Email Marketing
Flyer / Catalog Printing
Lead Management
Listing Management
Property Database
Website Management
