The New York fintech that decided a person's phone - not their paperwork - could prove they deserve a loan, and built the software to make lenders believe it.
First Access logo mark. The company operates from 85 Broad Street in Lower Manhattan, a few blocks from Wall Street, while its customers lend in some of the world's most under-banked regions.
In most of the world, a loan application still begins with a question that has no good answer: what is this person's credit history? For billions of people the honest reply is "there isn't one." No mortgage on file, no store card, no decade of statements for an algorithm to chew on. First Access was built around the conviction that the absence of a paper trail is not the same as the absence of information - and that the missing information was already sitting in plain sight.
Founded in New York in 2011 by a team drawn from microfinance, mobile payments and analytics, First Access started by turning mobile phone behavior into a credit signal. How someone topped up airtime, how money moved in and out of a mobile wallet, the rhythm of small transactions - patterns that, taken together, said something reliable about whether a first-time borrower would repay. The company has analyzed more than 50 billion mobile transactions in the years since, a dataset assembled specifically to answer the questions traditional bureaus could not.
Today the company describes itself plainly as "a tech partner that meets you where you are." Its platform lets a lending institution launch a custom loan-origination product and decision engine to reach small businesses and consumers, then automate the parts of underwriting that should be automatic while leaving room for human judgment on the parts that shouldn't. What began as a scorecard has become a full operating layer for lenders.
First Access does not lend money itself. Its customers are the institutions that do - microfinance institutions, banks and digital lenders working across Sub-Saharan Africa, Asia and Latin America. These are organizations whose branch officers often make decisions in places with patchy connectivity and thin formal records, which is why the platform's mobile apps are built to work offline and sync later.
The customer's problem is concrete and expensive. Evaluating a borrower by hand is slow, inconsistent and costly, and every day a loan sits in review is a day the borrower goes without capital and the lender goes without a performing asset. One branch manager described the change bluntly: loans that used to take four to six days now take one.
The core problem is exclusion by default. Traditional credit scoring rejects the applicant it cannot read, and in emerging markets that is most of the market. First Access reframes the gap as a data problem: collect signals from multiple sources, run them against a lender's existing policies and scorecards, and produce a decision the institution can act on.
The economics are what make it stick. By automating low-risk approvals and standardizing the rest, the platform reported cutting a lender's cost to evaluate a borrower by roughly 65% and underwriting time by as much as 80%. That turns lending to the underserved from an act of goodwill into a business that pencils out.
Enabling more reliable, real-time predictions about the creditworthiness of people who have never been a part of the formal financial system.— First Access, on the FINCA collaboration
First Access grew from a single scorecard into a modular platform. A lender can adopt the pieces it needs and launch a tailored credit product in roughly two weeks.
Collects data from multiple sources and processes it against a lender's existing credit policies, scorecards and algorithms - originally built on mobile and alternative data to score thin-file and unbanked applicants.
Mobile and web application interfaces with data collection and management tools, plus offline-capable mobile apps for the field. Launch a custom credit application in about two weeks.
A configurable scoring and decision engine that automates low-risk approvals and routes edge cases to a human - balancing speed with judgment instead of choosing one.
Credit-focused CRM plus business intelligence that lets lenders mine their own portfolios and recalibrate their models with machine learning as they grow.
Plenty of well-known names - Tala, Branch, JUMO - built their own consumer lending apps on top of alternative data. First Access took a different seat at the table. Rather than compete with lenders, it hands them the machinery and lets each institution keep its own credit policies, scorecards and relationships.
That "meet you where you are" posture shows up in the engineering: offline-first mobile apps for low-connectivity regions, a configurable engine instead of one universal score, and analytics that turn a lender's growing portfolio into its own best training data. Against loan-management vendors like Mambu or Musoni, the differentiator is the decisioning brain; against consumer-lending fintechs, it's the B2B, institution-first model.
First Access licenses its origination, scoring and decision-engine platform to lending institutions, configured to each client's credit rules. Revenue comes from the software relationship rather than from interest on loans, which keeps the company's incentives aligned with helping lenders decide well and cheaply rather than with any single borrower's outcome.
In the stack of financial inclusion, First Access sits at the decision point - between the raw data of an applicant and the yes-or-no of a loan. It occupies the space where alternative-data credit modeling meets institutional lending software, a niche that matters most precisely where formal credit bureaus are weakest.
Came out of the microfinance field convinced capital was reaching the wrong people. Named to Fast Company's 100 Most Creative People (2016). Studied at Kenyon College and Columbia SIPA.
Leads the modeling work that turns alternative data into credit signals - the analytics engine behind the scorecards.
A microfinance and mobile-money veteran who helped shape the company's direction from the board.
Veterans of microfinance, mobile payments and analytics launch the company to score creditworthiness from alternative data.
A partnership with FINCA scales alternative credit scoring across six African countries; CEO Nicole Van Der Tuin is named among Fast Company's 100 Most Creative People in Business.
Bamboo Capital Partners leads a $7M round, with The Social Entrepreneurs' Fund and Impact Engine participating, funding product, sales and client-success teams.
First Access broadens from scoring into a full loan-origination and decision-engine platform with CRM and analytics.
Launch your custom loan origination and decision engine to reach small businesses and consumers anywhere.— First Access
Search these sources for CEO interviews and platform walkthroughs.
It gives lending institutions in emerging markets a configurable software platform to originate loans, score applicants and automate credit decisions - including borrowers with no formal credit history.
It was founded in 2011 in New York by Nicole Van Der Tuin (CEO), Rohit Acharya (Chief Data Scientist) and Duncan Goldie-Scot.
It analyzes alternative data - such as mobile phone usage and transaction patterns - along with a lender's own portfolio data, running it against configurable scorecards and machine-learning models.
Roughly $9.25M in total, including a $7M Series A in November 2017 led by Bamboo Capital Partners, with The Social Entrepreneurs' Fund and Impact Engine participating.
It is headquartered in New York and serves lenders across Sub-Saharan Africa, Asia and Latin America, including a multi-country deployment with FINCA.