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Articles by Jayendran GS
How upfront income accuracy transforms lending
Mortgage lending has a Day 28 problem. Borrowers engage with lenders on Day Zero. Expectations get set. Loan options get discussed. Confidence gets built. Then income finally receives scrutiny on Day 28—deep in underwriting, after time, money, and operational effort have already been spent. The result? Income surprises kill deals. Borrowers wait, frustrated. Lenders scramble to reposition files. What looked like a strong pipeline on Day Zero quietly erodes by the time income reality sets in.
Changing Market Demands
The Place for Lending Visionaries and Thought Leaders. We take you beyond the latest news and trends to help you grow your lending business.
AI platforms revolutionizing how lenders assess self-employed borrowers
The lending landscape has fundamentally changed. Designed for W-2 employees with predictable pay stubs, traditional lending models no longer work for many of today’s prospective borrowers, particularly those making up the self-employed workforce. Today’s workforce includes approximately 16.5 million self-employed Americans and 57 million gig economy workers (36% of the workforce).
Precision partners: How AI and human expertise are elevating lending excellence
Empowering excellence: The necessary accuracy in lending AI In lending, being approximately right isn’t good enough. A system that’s 99% accurate still means one in every hundred borrowers faces a potentially catastrophic error. This industry breathes on accuracy—it’s the oxygen that sustains trust. This focus on precision distinguishes lending from other AI applications.
Let the Robots Handle Your Menial Work
The world of lending is undergoing a remarkable transformation, and artificial intelligence (AI) is at the forefront of this change. As AI continues to revolutionize the lending landscape, it presents an unparalleled opportunity to streamline traditional processes, enhance risk assessment and broaden access to credit. Despite the numerous benefits, many organizations hesitate to embrace AI in their lending workflow due to a misconception that it will replace lending teams.
Uncovering the True Bottleneck
Streamlining the mortgage underwriting process is among the top priorities for senior-level executives at any lending organization. The current underwriting process is highly manual and has numerous inefficiencies, leading lenders to waste time and money on every loan application. The actual numbers are even more disconcerting. The average time to process a loan application remains at 45 to 60 days, according to ICE Mortgage Technology.
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