big data Archives - Lend Academy

Data is everywhere. The world generates some 2.5 quintillion bytes of data every day. Some people have said we are drowning in data and that may well be true. But we are starting to get better at making sense of massive amounts of data. Which brings me to the point of this article. Data science is going to become, if it hasn’t already, the most important skill in fintech.

Before we go any further we should define what we mean by data science. There is no standard definition but I like how NYU describes it:

At its core, data science involves using automated methods to analyze massive amounts of data and to extract knowledge from them.

Extracting knowledge is the key point here. We may be drowning in data but a skilled data scientist will be able to extract the useful parts of this data and discard all the noise. With so much data available today in all industries, particularly in finance, those companies that can extract useful and actionable knowledge will be the winners.

Chris Skinner penned this interesting piece last week claiming the critical importance of data in banking:

Data is the new air, and the banks that breathe the best will win. In other words, banks that really get data analytics, and can apply machine learning to gain deep customer insights are the ones that will survive.

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The average American checks their phone 47 times a day according to this study by Deloitte. The number is much higher (82) if you are in the 18-24 year old age bracket. We keep our lives on our phones and so it has become the most essential piece of technology we own.

With all that usage comes a treasure trove of data. Now, this also brings with it a host of privacy issues but that is not the focus for this article. What I am talking about here is smartphone data and how companies can leverage this to expand access to credit. This particularly applies to the underbanked consumers in this country and more importantly in developing countries.

For many consumers their access to credit is limited because they have little or no credit footprint. They may operate primarily with cash, have no credit score and are therefore unable to qualify for a loan from most lenders. Their credit needs are often more urgent than the mid-prime and prime consumer but because lenders have little or no data they have difficulty in obtaining credit.

This problem is particularly acute in the developing world. Here, most people are outside the traditional financial system, if there even is one, and do not have access to credit. But that is changing as companies like Kiva, Lenddo (listen to Episode 91 of the Lend Academy Podcast), Branch and Juvo (see this session at LendIt USA 2017) are helping consumers get access to credit, often for the first time.

What lenders are finding out is that even when there is no credit data available the data that is inside a consumer’s smartphone can be very predictive of creditworthiness. I think Lenddo (they are a technology provider, not a lender) is doing some of the best work in the space as they have a great deal of experience in many different countries using data contained in smartphones to score consumers. In this country LendUp and Elevate are also doing good work and I like Oakam in the UK.

Underwriting is All About Data

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Data Science is Becoming the Most Important Skill in Fintech

The explosion in data has made the data scientist an essential part of all fintech companies

Smartphone Data is the Key to Expanding Access to Credit

Every smartphone owner produces a huge amount of data and companies are now using some of this data to underwrite loans.

Underwriting is All About Data

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