Kiva is an international non-profit organisation, which aims to connect lenders with people who don’t have access to the capital that they need to run their businesses, go to school or access clean energy.
The non-profit estimates that there are about 1.2 billion to 2 billion people who currently don’t have this access, and it crowdfunds that money in order to help these people get their businesses to the next stage, with the overarching effect of alleviating poverty.
Currently, Kiva’s non-profit marketplace supplies over $1.16bn in loan capital in more than 85 countries, and facilitates 32,395 transactions every day. Since it launched in San Francisco in 2005, the organisation has crowd-funded more than a million loans, and has over a million lenders worldwide.
With these users and data – as much as many traditional banks – the organisation needs technology that can enable it to successfully manage, secure and analyse information.
Kiva CTO Kevin O’Brien explains that the organisation had tried making the most of its data for a number of years with failed initiatives.
“A long while ago we were using software that was more suited to larger enterprises and so didn’t work for us at all, then we looked at moving into something more modern and opted for a hosted offering but after about six months and spending a lot of effort getting familiar with the product. it didn’t work for us,” he explains.
“So we began exploring other options and trialled [data warehouse provider] Snowflake Computing using [Amazon] Redshift, and it was clear we would be able to make significant savings, which was important for us as our donors always expect us to use cost-effective solutions,” he adds.
But it wasn’t just the cost that was of benefit to Kiva; the use of Snowflake has allowed the company to democratise access to data.
“Whereas before some of the products we were using were complex and we only had one or two people that could interact with the system, now using Snowflake and Looker, we can open the data up to the entire company, and control access appropriately,” O’Brien explains.
“This means that we can technically teach people very quickly if they want to use the data themselves, rather than having to ask someone technical to do it for them – and that’s important as they can make decisions faster and do innovative things with the data – but can also get support and guidance from data scientists if they need it,” he adds.
Snowflake, Looker and Redshift form part of a sophisticated data sharing system which Kiva is using to make credit history portable and recognisable to regional and national banks, so refugees and other transient populations are more able to get credit, and land on their feet.
“One reason why we haven’t seen larger amounts of capital moving from regional and international banks into some of these regions is because a lot of these borrowers don’t have a customer vicinity that banks are familiar with, such as money laundering checks,” O’Brien says.
Kiva is currently working on a blockchain service for digital identity and credit history. The idea is that refugees that Kiva works with who have used finances and services to make a difference in their communities, can take this history with them even when they get out of a refugee camp. Currently they’re having to start from scratch again, with no evidence of the work they’ve already accomplished.
“If we could set up a system that makes the checks required a lot less extensive than the standardised way of doing it, then banks who require this information would start to put more capital into these institutions and borrowers,” says O’Brien.
“Today we lack the digital information to gain a risk profile as a lot of this information is still on paper, but we’re working on getting digital credit history that allows us to give a risk profile associated with some of these borrowers – if we can enable that, then we’ll see more money moving into their hands as well,” he adds.
The non-profit has made huge strides with data management in general; it can now provide consistent and reliable data reporting across 400 trustees and field partners to better source entrepreneurs, screen borrowers, post loan requests, disburse loans and collect payments. It has received more funding as a result of the better access to data, and has improved its lending strategy as non-profits can vet borrowers more effectively by understanding their online network.
The next stage, O’Brien suggests, is to team up with its partners and create a repository of data which can be opened up for analysis by researchers and students.
“They can then hopefully provide some suggestions on how we can better help get people out of poverty,” he states.