Reasons to meet Visionet at MBA Annual Convention
by Shamit Vohra
The rapid growth of FinTech companies is causing a disruption in the lending space. Add to that the changing requirements based on millennial borrowers and the ever-changing regulatory requirements and you quickly realize the challenge that mortgage lenders are up against. Most lenders would love to provide a personalized experience to borrowers, and that too in quick time. As a result, most mortgage lenders are looking beyond just cost savings and are striving to create a lasting competitive advantage.
Delivering on these requirements is not an easy task unless your company has skilled resources, automated processes, and the right technology platforms. Working with a leading and reliable end-to-end mortgage service delivery partner can create a long-lasting business impact for mortgage lenders.
Reasons why you should meet Visionet, this MBA Annual,
1) Only company to provide End-to-End solutions for Mortgage
Visionet is proudly one of the very companies to offer end-to-end solutions for the mortgage and related industries. It provides a unique combination of BPM delivery, digital technology solutions, and IT services to its customers. Because of this, several lender clients are happily engaging with Visionet for multiple projects. This not only saves costs but also saves the coordination efforts required with various vendors.
2) Ahead of the game with AI-ML powered OCR loan processing solution
Visionet’s VisiLoanReview, a loan processing solution, is enabled with Artificial intelligence/Machine Learning powered OCR technology to deliver faster loan disbursals.
VisiLoanReview leverages over a decade of product refinement and industry operations with hundreds of long-standing customers. Technologically, it uses the triple-pass methodology to strip and validate content using NLP, OCR, and multiple big data stacks. The AI-based system further trains itself using Machine Learning algorithms to provide progressively accurate results.
3) Speed up your disbursals by 30% & take on more volumes
To reduce loan processing time from weeks to days, you need to automate the processes as much as possible. The initial stages of loan origination are highly paper-oriented and time-consuming, and only process automation can help tackle this challenge. For efficiently processing loan documents, we leverage VisiLoanReview (VLR), Visionet’s loan processing solution enabled with AI/ML-enabled OCR technology. It ensures 30% faster loan processing while maintaining over 98% accuracy. VLR is also integrated with leading Loan origination system such as Encompass by Ellie Mae. The integration with Encompass helps the borrower files to be extracted, worked upon, and made available in Encompass in just 4 hours.
4) Reduce processing costs by 30% & increase your profitability
Lenders need to ensure that they are working with service providers who are focusing on automation and adoption of newer technologies. As the redundancies are taken care of and processes take less time to execute, we get to see great results in terms of reduction in costs. Moreover, the offshoring model with virtual 24*7 operations, with its labor arbitrage helps deliver a 30% reduction in loan processing costs. This directly helps lenders in increasing their profitability.
5) Achieve over 98% accuracy & reduce risks
Automating your processes leveraging technology reduces the chances of errors as human intervention is minimized. Visionet’s VisiLoanReview is enabled with technologies such as Artificial intelligence/Machine Learning which makes sure that you achieve over 98% accuracy and reduce any risks.
Partnering with the right end-to-end mortgage partner can generate several benefits. An increasing number of lenders are leveraging Visionet to achieve scale in operations, reduced costs, improved accuracy, minimize risks, reduce processing time.
It’s time you met with Visionet too. We are at the upcoming MBA Annual Convention, between Oct 27th – 30th, at booth 338. To schedule a meeting with our leadership team, click here