In-house Financial Services Colombia Company newsroom

Quipu

Risk Management

Informal Colombian small businesses often lack bank accounts and traditional credit histories, so banks cannot verify their creditworthiness and these entrepreneurs struggle to access formal growth financing.

$200,000 prize money
$5 million
50% of whom are women
Its loans range from $100 to $5,000; the average is $300.

Reported impact

Business outcome

Quipu has allocated $5 million, helped more than 26,000 Colombian entrepreneurs access financing, reports that borrowers increase income by 9% after getting a loan, and is beginning to license its scoring technology to other lenders in Colombia.

  • Revenue Growth

Solution

Quipu is an AI-based financing platform built to underwrite informal Colombian microbusinesses that lack conventional banking histories. According to the story, Quipu ingests nontraditional operating signals from each business, including social media activity, inventory information and real-time financial transactions, then processes them with its creditworthiness algorithm to judge present performance and future potential rather than relying on past credit files. The platform has accumulated lending data since 2021, allowing it to return a credit decision within seconds and to tailor loan offers to what each entrepreneur needs. Quipu also extends the experience through Edubot, a WhatsApp tool that acts as "a CFO in your pocket" for day-to-day support. The resulting scores drive Quipu's own lending and are now being licensed to other lenders in Colombia to expand access to capital.

Data flow

Quipu collects nontraditional business signals from sources such as social media, inventory records and real-time financial transactions, processes those inputs with its AI credit-scoring algorithm, and uses the resulting score to make loan decisions within seconds. The same workflow now supports personalized loan offers, Edubot guidance on WhatsApp, and lender-facing scoring technology licensed to partners in Colombia.

Solution architecture

3 components · 2 layers
  1. Compute
    • Quipu Financing platform that ingests alternative business data and runs the AI credit-scoring workflow used to underwrite and personalize loans.
  2. Serving
    • Edubot WhatsApp-based tool that supports entrepreneurs' daily business needs as a "CFO in your pocket."
    • WhatsApp Messaging channel through which Edubot reaches business users.

Architecture clues

  • Alternative-data model uses social media, inventory and real-time financial transactions as scoring inputs.
  • Edubot is delivered as a WhatsApp tool for daily business support.
  • Quipu is shifting from direct underwriting toward licensing its scoring technology to other lenders in Colombia.
  • The creditworthiness algorithm can determine whether a business is credit-worthy within a few seconds.

Evidence from the source

"After a business gets a loan, it increases its income by 9%."
"It uses AI to sort through nontraditional data, including a company’s social media, inventory and real-time financial transactions, to determine whether businesses like Galván’s is creditworthy."
"Quipu was one of five winners of the challenge and is using the $200,000 prize money, along with technical assistance and mentoring, to add a WhatsApp tool called Edubot that supports businesses’ daily needs — Bidart describes it as ‘a CFO in your pocket.’"
"Since its founding in 2021, Quipu has allocated $5 million and helped more than 26,000 Colombian entrepreneurs, 50% of whom are women."
"The company’s algorithm has amassed enough data over the years so that it can determine whether a business is credit-worthy within a few seconds."
Transparency Evidence & methodology 100/100 reference value · 93% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    4 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence93%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency10/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Mastercard

    AI for good empowers small businesses with alternative data | Mastercard Europe

    First-party
    https://www.mastercard.com/europe/en/news-and-trends/stories/2025/ai-for-good-quipu-colombia.html
    Source type
    Company-published story
    Published
    Sep 24, 2025
    Supports
    • Customer
    • Region
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • Publication date
    • evidence quotes

Date evidence

  • Published on source page Sep 24, 2025 · Quipu · First-party
    Open date source
Not separately sourced Industry, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.