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Detecting Hidden Fraud Risk from Public Data

Hudson Hollister

October 18, 2019

BLOG_Detecting Hidden Fraud Risk from Public Data

Detecting which of the federal government’s millions of contracts1 most likely involve fraud used to require insider access to agencies’ IT systems. Data analytics provides greater efficacy and higher hit rate than traditional investigative methods – and now can even be performed using only public data.

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Be Smarter Than Your Devices: Learn About Big Data

Peter Bruce

October 4, 2019

BLOG_Be Smarter Than Your Devices-Learn About Big Data

When Apple CEO Tim Cook finally unveiled his company’s new Apple Watch in a widely-publicized rollout, most of the press coverage centered on its cost ($349 to start) and whether it would be as popular among consumers as the iPod or iMac. Nitin Indurkhya saw things differently.

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The Case for Government Investment in Analytics

Jane Wiseman

September 20, 2019

BLOG_Government Investment in Analytics

Government stands to gain $1 trillion globally from using data analytics.1 Few government data teams have the resources to document their value, but those that do can show as much as eight-to-one return on their cost. There is significant non-financial benefit as well, as public faith in government may improve when saving time and money is paired with increased transparency and accountability.  

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Determining Federal Grant Recipient Fraud Risk

Wayne Folta

September 6, 2019

BLOG_Determining Federal Grant Recipient Fraud Risk

Elder Research partnered with Excella Consulting to build an end-to-end grant risk estimation solution in the client’s AWS cloud. It used text mining and document classification to extract CPA Findings from audit reports and assign risk scores to federal grant recipients.

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Better NLP Models: OpenAI GPT-2

Peter Bruce

August 23, 2019

BLOG_Better NLP Models - OpenAI GPT-2

I’ve been told that, in conversation, I jump in and finish other people’s sentences for them. Now there’s an app for that: GPT-2 released by OpenAI, founded by Elon Musk. GPT-2 is a natural language program that, given a prompt, will write (mostly) intelligible content. OpenAI's stated mission is “to ensure that artificial general intelligence (AGI) … benefits all of humanity.” Natural Language Processing (NLP) includes applications such as text classification, language creation, answering questions, language translation, and speech recognition.

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Why Machine Learning Is the Coolest Science

Eric Siegel

August 9, 2019

BLOG_Why Machine Learning Is the Coolest Science

The absolutely coolest thing in science and engineering is machine learning, when computers learn from the experience encoded in data. I shall now support that hypothesis.

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Investment Modeling Grounded In Data Science

John Elder, Ph.D.

July 26, 2019

BLOG_Investment Modeling Grounded In Data Science

Elder Research has solved many challenging and previously unsolved technical problems in a wide variety of fields for Government, Commercial and Investment clients, including fraud prevention, insider threat discovery, image recognition, text mining, and oil and gas discovery. But our team got its start with a hedge fund breakthrough (as described briefly in a couple of books1,2), and has remained active in that work, continuing to invent the underlying science necessary to address what is likely the hardest problem of all: accurately anticipating the enormous “ensemble model” of the markets.

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The Persuasion Paradox – How Computers Optimize their Influence on You

Eric Siegel

July 5, 2019

DR. Data Show

How do computers optimize mass persuasion – for marketing, presidential campaigns, and even healthcare? And why is there actually no data that directly records influence or persuasion, considering it’s so important? And what’s the ideal technique for optimizing your dating life and for getting more people to wash their hands in public restrooms? It’s time for Dr. Data’s persuasion paradox “Groundhog Day”-inspired geeksplanation.

Persuasion modeling requires a “deep geek dive” – but it’s as important as it is fascinating.

Note: This article is based on a transcript of The Dr. Data Show episode. View the video here.

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Healthcare Analytics: Exploration vs. Confirmation

Peter Bruce

June 21, 2019

BLOG_Healthcare Analytics_Exploration versus Confirmation

Perhaps the most active application of analytics and data mining is healthcare.  This week we look at one success story, the use of machine learning to predict diabetic retinopathy, one story of disappointment, the use of genetic testing in a puzzling disease, and a basic dichotomy in statistical analysis.

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Data is Not Oil. It is Land.

Will Goodrum, Ph.D.

June 7, 2019

Blog_Data is Not Oil, It Is Land-1

It has become common to talk about data being the new oil. But a recent piece from WIRED magazine points out problems with this analogy. Primarily, you must extract oil for it to be valuable and that is the hard part. Framing data as oil is not illuminating for executives trying to value their data assets. Oil is valuable, marketable, and tradable. Without significant effort, data is not. Data has more in common with land that may contain oil deposits than it does with oil.

Framing data as a real asset may help executives understand its value.

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Tiger vs. Jack – Asking the Right Questions

Daniel Brannock

May 24, 2019

BLOG_Tiger vs. Jack – Asking the Right Questions-1

One of the most fundamental contributions we can make as consultants is to help our clients ask the right questions of their data. We’re often asked to help solve problems that turn out to be too broadly or too narrowly defined—or are not aligned with achieving business goals or eliminating pain points.

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A Deep Dive into Deep Learning

Peter Bruce

May 10, 2019

BLOG_A Deep Dive into Deep Learning

On Wednesday, March 27, the 2018 Turing Award in computing was given to Yoshua Bengio, Geoffrey Hinton and Yann LeCun for their work on deep learning. Deep learning by complex neural networks lies behind the applications that are finally bringing artificial intelligence out of the realm of science fiction into reality. Voice recognition allows you to talk to your robot devices. Image recognition is the key to self-driving cars. But what, exactly, is deep learning?

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Discovering The Efficacy Of A New Drug

John Elder, Ph.D.

April 26, 2019

BLOG_Discovering The Efficacy Of A New Drug

The company had invested hundreds of millions of dollars investigating a new potential drug to treat a mental ailment, and they had zeroed in on a compound that showed promise but the compound was not passing the statistical tests required by the FDA. Elder Research was hired to examine the data and determine the drug’s viability. 

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What's Brewing at Predictive Analytics World

Paul Derstine

April 12, 2019

 BLOG_Predictive Analytics World-Las Vegas

Join us in Las Vegas on June 16-20 for the largest Predictive Analytics World event to date, Mega-PAW, with seven tracks of sessions covering the commercial deployment of machine learning across industry sectors. The only conference of its kind, Predictive Analytics World delivers vendor-neutral sessions across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, manufacturing, high technology, insurance, non-profits, publishing, and retail.

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Automating Network Entity Detection

Ryan McGibony

April 5, 2019

BLOG_Automating Data Pipelines and Network Entity Detection

Elder Research developed an automated data pipeline to cleanse data and feed a data visualization tool used to identify and explore document preparer network relationships. The solution enabled the client to automate significant portions of work, make data-driven decisions, prioritize resources, and gain new business value from the data.

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Can Data Analytics Really Deliver 1300% ROI?

Paul Derstine

March 29, 2019

BLOG_Can Data Analytics Really Deliver 1300 ROI

With the right business problem, data, and applied techniques predictive analytics can deliver exceptional return on investment (ROI) by, for example, assessing and managing risk, detecting and preventing fraud, optimizing workflow and business processes, and prioritizing resources.  Predictive analytics provides business leaders with data-driven insight to determine which customers to contact for marketing, which tax returns to audit, which debtors to approve for increased credit limits, which patients to clinically screen, which customers are likely to leave, which persons of interest to investigate, and which equipment to inspect for impending failure.

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Do We Have the Right Data?

Jeff Deal

March 22, 2019

BLOG_Do We Have the Right Data

In our experience the mistake of “waiting for perfect data” probably kills more projects than any other. Here’s a typical scenario:

The project starts out well. The management team defines the goals, calculates the potential return on investment, develops a project plan, gets a budget approved, assembles the team, and launches the project. The trouble starts with a desire to make sure that the data is in “good” condition. 

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Transaction Classification Aids Credit Risk Assessment

Carlos Blancarte

March 15, 2019

BLOG_Transaction Classification Aids Credit Risk Assessment

A significant transformation is currently underway in the lending market. Banks are competing to provide lending decisions in a single day, with a vastly simplified customer experience as their primary way of growing market share. The key technology allowing this transformation is being able to accurately automate the credit decision; that is, to use advanced analytics to estimate a customer’s probability of default, affordability, and financial position to make the credit decision quickly.

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RADR: A Powerful Visual Risk Analytics Tool

Victor Diloreto

March 8, 2019

BLOG_RADR-A Powerful Visual Risk Analytics Tool

The Risk Assessment Data Repository (RADR) is a powerful risk analytics platform used to enhance productivity in the investigation of fraud, waste and abuse. This server-based, data analytics product  fuses data from multiple sources, with sophisticated predictive and machine learning risk modeling, and an intuitive visual interface. RADR enables proactive identification of risk—namely fraud, waste, and abuse behaviors—and simplifies the investigative process. RADR provides visualizations for risk propensity and their related data so that managers, auditors, investigators, and analysts can easily access data on high-risk items and focus on the highest ROI cases.

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Data Engineering with Discipline

Victor Diloreto

March 1, 2019

BLOG_Data Engineering with Discipline

As a data science consultancy, we frequently run into difficult data infrastructure challenges at our clients across multiple industries. To solve a business problem or get decision-making insights from data, we often must start by helping to clean up and organize the data architecture so we can build data science and machine learning (ML) models. This process of getting the data ready for the application of the science is called data engineering.

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5 Key Reasons Why Analytics Projects Fail

Peter Bruce

February 22, 2019

BLOG_5 Key Reasons Why Analytics Projects Fail

With the news full of so many successes in the fields of analytics, machine learning and artificial intelligence, it is easy to lose sight of the high failure rate of analytics projects.  McKinsey just came out with a report that only 8% of big companies (revenue > $ 1 billion) have successfully scaled and integrated analytics throughout the organization. In some ways, the very notable successes of analytics and data science contribute to the high failure rate, as ill-prepared organizations flock to implement projects.  There are various reasons for failure, and all are instructive.

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The Problem with Random Stratified Partitioning

Mike Thurber

February 15, 2019



BLOG_The Problem with Random Stratified Partitioning-1

When an organization invests in data science, they need to have confidence that the predictive models will be robust; that is, actually work when applied to future cases. However, this critical requirement is too often poorly addressed. Schoolbook answers are partly to blame. Consider this innocuous quote from Investopedia:

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Fraud, Anomaly Detection, and the Interplay of Supervised and Unsupervised Learning

Peter Bruce

February 8, 2019

 BLOG_Fraud, Anomaly Detection, and the Interplay of Supervised and Unsupervised Learning-2

Mike Thurber, Lead Data Scientist and fraud specialist at Elder Research, presented Elder Research's fraud detection methodology at Predictive Analytics World for Government last year. Consider the scenario of detecting fraudulent insurance claims, such as the audacious "accidental" death scheme in the 1944 noir film Double Indemnity.

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Group Optimization – An Application of the Nash Equilibrium

Michael Lieberman

February 1, 2019

BLOG_Group Optimization_Nash Equilibrium

The Nash Equilibrium—see A Beautiful Mind—in economics and game theory is defined as a stable state of a system involving multiple participants, where no one can gain by a change of strategy if the strategies of the others remain unchanged. More simply, it is a maximized state where no other players will agree if one player changes her position. In terms of economics or business, it is the most equitable, though not always the most obvious, solution to a multi-party conflict.

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The Data Speak: The World Is Getting Better

Peter Bruce

January 25, 2019

Blog_Data Doesn't Lie

In the visualization below, which line do you think represents the United Nation’s forecast for the number of children in the world in the year 2100?

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