Better leverages ElevenAgents to build Betsy, reducing mortgage origination costs by 41% and doubling lead-to-lock conversion
Mortgage origination requires state-licensed consultants whose time is scarce and expensive, with most of that time consumed by repetitive qualification calls, outbound dialing, and follow-ups. Most financial institutions cannot deploy AI meaningfully because eligibility, pricing, and servicing data sit across fragmented LOS, CRM, and internal tools.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Outbound or inbound call initiated
Betsy places outbound and receives inbound phone calls with borrowers.
Tools used
ElevenAgentsElevenLabsTinmanSpeech to TextLLMText to Speech
Outcome
Betsy automates 35.5% of mortgage inquiries end to end, saves loan officers over 1,666 hours monthly, reduced average cost to originate by 41%, and doubled lead-to-lock conversion in 2025, while handling nearly 100,000 monthly calls.
What failed first
Better's initial voice offering used a Speech to Speech model but lacked the naturalness, low latency, control, and reliability needed for high-volume financial services conversations.