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M-Kopa: History, Companies, Products & Art
M-Kopa (M for mobile, kopa is Swahili for borrow, stylized as M-KOPA) is a UK-headquartered emerging market fintech platform that provides affordable smartphones and digital financial services. M-Kopa was launched commercially in 2012 and is headquartered in London. The company is currently operating in Kenya, Nigeria, Ghana, Uganda and South Africa.
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M-Kopa topic overview
The analysis highlights History, Companies, Products and Art as prominent areas in the source structure around M-Kopa.
Related topics
17
Source areas
4
Connected nodes
21
Extracted relationships
66
Concept neighborhoods
7
Bridge connections
21
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
History · 12 topics
Overview · 3 topics
Awards · 1 topics
Business model and products · 1 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Founded
2011
Founders
Nick Hughes, Chad Larson, Jesse Moore
Industry
Fintech
Headquarters
London, United Kingdom
Areas served
Kenya, Uganda, Nigeria, Ghana, South Africa
Products
Smartphones & financial services
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How M-Kopa connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around M-Kopa shows recurring relationship patterns in the source. For example, M-Kopa → Africa, Africa's Fastest Growing Companies, Award, Best Mobile Innovation, Bloomberg New Energy Finance, Boldness, Business Awards, Cleantech, Companies Changing, Emerging Markets, Excellence, Fast Company, Financial Times, Financial Times Arcelor Mittal, Fortune, Global Mobile Awards, In, In February, In March, June Another extracted example is M-Kopa → Backing, Blue Haven Initiative, Chad Larson, Generation Investment Management, Hughes, In, Larson, LGT Venture Philanthropy, Liechtenstein, M-Pesa, MBA, Moore, Nairobi, Oxford University, Princely Family, Richard Branson, Signal Point Partners, Vodafone. Use these groups to spot repeated connection types before inspecting the individual relationships.
M-Kopa
Top relations
related to Awards· 31
M-Kopa → Africa, Africa's Fastest Growing Companies, Award, Best Mobile Innovation, Bloomberg New Energy Finance, Boldness, Business Awards, Cleantech, Companies Changing, Emerging Markets, Excellence, Fast Company, Financial Times, Financial Times Arcelor Mittal, Fortune, Global Mobile Awards, In, In February, In March, June
related to history· 18
M-Kopa → Backing, Blue Haven Initiative, Chad Larson, Generation Investment Management, Hughes, In, Larson, LGT Venture Philanthropy, Liechtenstein, M-Pesa, MBA, Moore, Nairobi, Oxford University, Princely Family, Richard Branson, Signal Point Partners, Vodafone
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 66 structured relationships around M-Kopa. Examples in this analysis include M-Kopa → Areas served → Kenya, Uganda, Nigeria, Ghana, South Africa and M-Kopa → Founded → 2011. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
M-Kopa
Areas served
Kenya, Uganda, Nigeria, Ghana, South Africa
1.00
infobox
M-Kopa
Founded
2011
1.00
infobox
M-Kopa
Founders
Nick Hughes, Chad Larson, Jesse Moore
1.00
infobox
M-Kopa
Headquarters
London, United Kingdom
1.00
infobox
M-Kopa
Industry
Fintech
1.00
infobox
M-Kopa
Products
Smartphones & financial services
1.00
infobox
M-Kopa
Type
Private company
1.00
infobox
M-Kopa
Website
Official website
1.00
infobox
M-Kopa
related to Awards
Bloomberg New Energy Finance
0.60
section
M-Kopa
related to Awards
Award
0.60
section
M-Kopa
related to Awards
Financial Times
0.60
section
M-Kopa
related to Awards
Technology
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around M-Kopa bring nearby vocabulary together. In this analysis, examples include Financial, Africa and Services. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
M-Kopa
Financial
Africa
Services
Companies
Affordable
February
Awards
Smartphones
Mobile
Company
Fintech
London
m-kopa
Financial
Africa
Services
Companies
Affordable
February
Awards
Smartphones
Mobile
Company
Fintech
London
financial times
Smartphones
Services
Awards
M-kopa
Fintech
Model
Products
Company
Ghana
Hughes
Larson
London
awards
Financial
Fintech
Ghana
Hughes
Larson
London
Model
South
February
Nigeria
Products
M-kopa
london
Ghana
Hughes
Larson
Model
South
Nigeria
Products
Awards
Moore
Smartphones
Uganda
Africa
business model and products
Smartphones
Services
Hughes
Larson
South
Nigeria
Products
Awards
Moore
Uganda
Also
credit bureaus
Digital
February
Million
Customers
Payments
Financial
M-kopa
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For M-Kopa, one of the stronger structural bridges in this analysis connects M-Kopa with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
M-Kopa
Nodes22
Edges21
Triples66
Avg. degree1.91
Density0.090909
Components1
Source & methodology
TTTA analyzes the structure around M-Kopa to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Companies, Products & Art, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
