Despite Bitcoin's future taking the majority of the top stories in finance, multiple fintech companies are experiencing noteworthy growth and tackling today's critical issues from fraud detection, streamlining loan approval, to going beyond standard credit score decisioning in underwriting loans.  There are 7 of the Forbes Fintech50 right here in the SF Bay Area (from San Francisco down to Menlo Park), changing the way we do business in 2018: 

Veem (San Francisco) - -  Businesses are able to send / receive payments worldwide with various methods (Swift network, 3rd-party processor, or blockchain) depending on what's most efficient;   reducing wire-transfer fees and foreign currency bank rates.

Blend (San Francisco) - -  Focused on improving and efficiently speeding up the mortgage process through cloud based software.  Blend allows borrowers to upload and link all their requested documents (bank / tax statements, w2s, etc.), which saves essential time going back and forth between bank and borrower.

LendingHome (San Francisco) - - Focuses on online lending of bridge loans (for fixing & flipping houses), and has broadened to individual mortgages with a growing footprint of 25 states.  

Ayasdi (Menlo Park) - - machine learning being used used by big banks for analysis in uncovering risks and structuring of potential money laundering.

Feedzai (San Mateo, CA) - - Focuses on machine learning analysis of unstructured data (from emails, contact center calls, chat bots, etc.) and transaction data to combat fraud and reduce losses.

Guideline (San Mateo, CA) - - Helps small companies connect payroll vendors with 401(k) plan administration and benefits, only charging a setup fee and annual fee per employee to maintain compliant records and reporting. 

Upstart (San Carlos) - - Instead of traditional credit scoring models, Upstart uses other data and metrics (e.g. education, employment) to underwrite and offer loans. Its own system based on algorithms approves over 45% of loans on its own (no review by an underwriter) at low defaults.