<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/ce834b74e31349139bdf6ef22475ad06&quot; frameborder=&quot;0&quot; width=&quot;1152&quot; height=&quot;864&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>864</height><width>1152</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>864</thumbnail_height><thumbnail_width>1152</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/ce834b74e31349139bdf6ef22475ad06-a48581bc51808eaf.gif</thumbnail_url><duration>107.182</duration><title>Automating Bank Statement Income Verification for DSCR Loans 👇</title><description>Hey Jess, I am Kaustub. I have been tracking B line equity and your non QM rollout, and I know the compliance and execution weight of scaling these loans lands on your desk. Right now, processors likely spend hours manually reviewing 40 page PDF bank statements to calculate self employed income for DSCR loans. I run Kiva, and we use custom OCR and ingestion pipelines to categorize business deposits, ignore personal transfers, and deliver a clean verified 12 month income calculation into your origination system with zero manual data entry and no new headcount. Does eliminating this bottleneck align with your automation mandate?</description></oembed>