9. FINTECH KEEPS
GROWING
A few of these startups
could take up to 30%
of Mexico’s banking
market in the next
decade, with retail
banks and payment
services becoming
particularly vulnerable.
14. Develop solutions
with global appeal
that can easily
shift country
STARTUP
Use buyer-centric
financing mechanisms
like Supply Chain
Finance to reduce
equity requirements
Explore monetizing
long dated contracts
as an alternative to
raising equity
Figures from the Latin American Private Equity Venture Capital Association (LAVCA) show that VC investments increased from $143m in 2011 to nearly $600m just four years later.
GSMA, which represents the interests of nearly 800 mobile operators worldwide, is forecasting over 100 million new mobile internet subscribers by 2020, up 50% from 2015, a dramatic hike.
“Growth in these countries will see the regional penetration rate expand by more than 12% and an additional 100 million unique subscribers by the end of the decade. The region will grow more quickly over the remainder of the decade than any other region except sub- Saharan Africa.”
LAVCA’s figures for VC funding by country shows that by far the largest number of investments between 2011 and 2015 were made in Brazil, followed by Mexico, together accounting for over 70% of the total.
Supply Chain Finance allows carriers to extend payment terms all the way up to 270 days to free up cash. A simple idea that thanks to a cloud-based platform could now be deployed quickly, making it available to thousands of suppliers of all sizes.
GraphPath is the first Knowledge Graph-as-a-service that allows organizations to evolve from Big Data to Big Knowledge through the creation and management of large-scale enterprise knowledge graphs.
Simplification
GraphPath simplifies the adoption of graph computing, business intelligence and machine learning technologies across enterprises that are looking to quickly expand their ability to extract strategic value from large and complex datasets.
Big Visuals
The GraphPath solution allows companies to semantically organize all of their raw data, which may currently be inefficiently distributed across different data silos throughout their organization, into a single ontology that facilitates searching and analyzing their knowledge, as well as, deploying automated machine learning workflows, all in a collaborative and visually-engaging manner.
Applied Data
It could be applied to the data from cell towers and the data generated by the system when phones connect to it.
From the users’ perspective, it may include their billing history, app usage, call log, roaming charges, and more.
And lastly, it may also include sentiment data collected from social media networks that is generated around geo-fenced areas, such as a high-value cell tower clusters around the downtown area of a city, to compare against the network data and the user data.
That means you could get a list of cell towers in a region with the highest percentage of drop calls where the user sentiment is 20% worse than competitors, for instance.