by Douglas Merrill, Jessica Jackley, Paul Leonard and Ryan Gilbert
Technology and mathematics are transforming consumer lending. Historically, it has been nearly impossible for people with bad credit to get loans. Yet, these are often the people who need it most - to buy groceries or pay bills.
Until now, lenders determined who should get loans through a simple underwriting function based on a small amount of credit data. When this data is missing or wrong, banks deny the loan, leaving people to payday loans or pawn shops - very expensive options that put people further in debt.
Millions of people are being denied credit because underwriting hasn’t evolved. Why use only a handful of variables when we have vast amounts of data provided by the customer, the Internet, and social media? All data is credit data and we should use it all to make better underwriting decisions.
Analyzing vast amounts of data, however, requires complex machine learning more akin to search engines than your corner bank. The future of financial services is to become more like a recommendation engine, and less like a place where you stand in line to deposit checks.
The panelists will discuss how to use large-scale data analysis to re-invent underwriting and replace today’s antiquated methods. Better underwriting will open up good credit to people who don't have a lot of good options and materially improve the financial lives of the people who need it most.
LEVEL: Intermediate
by Jeremiah Akin and Michael Castellon
The expectation of transparency is creating demand for government agencies to develop new ways to communicate complex data and trends to the public in easy-to-access and easy-to-understand formats.
Some agencies are turning to Google Maps and KML data to visualize raw information online and on mobile devices. Delivering data in more easily understandable formats not only boosts trust and confidence between government agencies and their publics, but also streamlines workloads among Data, Web, Editorial, and Customer Service teams.
The Texas Comptroller is the state’s chief revenue officer, tax collector, and treasurer. The agency uses public-facing maps to communicate data and economic trends across the state, editorial coverage, and to promote initiatives such as its Unclaimed Property initiative, which works to reunite taxpayers with about $2 billion in unclaimed money and property.
This discussion will focus on how agencies and other organizations can use free or inexpensive tools to deliver data to the public in both traditional online formats and mobile platforms, and how workflows can be arranged so that data visualization can be managed and administered by non-technical staff. We will also discuss how maps can be used internally to enhance strategic efforts.
LEVEL: Intermediate
by Adam Rabinowitz, Ana Boa-Ventura, Irene Ros, Nicholas Rabinowitz and Ryan Shaw
Displaying geography alone is easy: interactive maps are more and more a part of our everyday lives. Displaying time alone is easy: we are all familiar with charts and animations that show the passage of time. It is increasingly common to display time and space together in a single visual interface as well, but this combination has raised a number of new questions. There are few conventions or standards for geotemporal visualization, and we are still discovering which approaches are most effective for which datasets. Focusing particularly on historical data, this panel will explore issues in the modeling and visualization of geotemporal information, presenting existing approaches and discussing new trends.
LEVEL: Intermediate