understanding the past, present, and future economic ... · knowledge for action equifax (nyse:efx)...

KNOWLED GE FOR ACT ION

Understanding the Past, Present, and Future Economic Behaviors of Customers for Financial Products Over TimeData at a Glance:Data are collected from a major Information Service Company and capture the financial activity of over 2 million consumers:

• Consumer Credit Histories• Collections/Bankruptcy Filings• Consumer Attributes• Tax Liens• File Inquiries

WEBINAR WILL BEGIN SHORTLY

Submit your proposal by Tuesday, May 31st, 2016. Learn more at http://wcai.wharton.upenn.edu/research

Presentation recording and slide deck will be made available via wcai.wharton.upenn.edu by Monday, May 16th, 2016


A WCAI Research Opportunity

May 13th, 2016

Understanding the Past, Present, and Future Economic Behaviors

of Customers for Financial Products Over Time


Introductions

3TRANSFORMING BUSINESS THROUGH CUSTOMER DATA

Debbie ShapiroAssociate Research Director, WCAI

Brandon KrakowskyResearch Director, WCAI

Colleen O’NeillExecutive Director, WCAI

Elea FeitSenior Fellow, WCAIAssistant Professor of Marketing, Drexel University

Pinaki GhoshSr. Director Enterprise Data & AnalyticsData Sponsor

Peter MaynardSVP, Enterprise AnalyticsData Sponsor

Trevis LitherlandSenior Data ScientistData Sponsor

Piyush PatelData AnalystData Sponsor

Karen DealAnalytics Program ManagerData Sponsor


Agenda

TRANSFORMING BUSINESS THROUGH CUSTOMER DATA 4

1. Equifax Introduction2. Credit data story/consumer life cycle3. Data walk through4. Use case/research areas walk through5. Demo of the environment6. On-boarding, environment/insights and publishing


Equifax(NYSE:EFX)isa$2.6B/year($13.2Bmarketcap) globalinformation solutionscompany&memberoftheS&P500withaheritagedatingback116years.

CANADAConsumer #1Commercial#2

UNITEDKINGDOMConsumer #2Commercial#3

CHILE #1ARGENTINA #1

BRAZILCommercial#2Consumer #2

IBERIASpainConsumer#1PortugalConsumer#1

LATAMREGIONPeru #1Uruguay #1ElSalvador #1Honduras #1Ecuador #1

INDIAConsumer#2

RUSSIAConsumer#1

UNITEDSTATESConsumer #1Commercial#3

AustraliaConsumer#1

5

EquifaxisaGlobalInformationCompany


Tobethegloballeaderininformationsolutionsthatcreatesunparalleledinsights tosolvecustomerchallenges.

Equifaxmaintainsdataonmorethan600millionconsumers,81millionbusinessesworldwide,&220millionemployeefiles.

6

UniquelyEFX

EFXVision&Data


Top

2MortgageGSE’s

7

EFXMarketPosition

Top

4Wireless,broadband,andpayTVproviders

12ofthetop15banksandFI’s

#1AutoLender


EFXData&Analytics

Customized High Value

DecisioningSolutions+ + =

Data Analytics Technology CustomerSolutions

Broad-Based and Unique Data

Assets

Value-added Analytical Insights

Software that Integrates Data &

Insights

Sourceandintegratestructuredandunstructureddatafromanyindustry,anywhereintheworldandproactively

deliveractionableinsightvaluedbycustomers

8


Credit Data Story and Consumer Life Cycle


Update • Segmentation • Scores and models • Insights• Estimated

performance • Based on

frequently updated data feedback.

Dynamic insight

• Segment population according to all relevant insights.

• Provide estimated performance to determine actions.

Decision strategies

• Down payment and terms insights impacting pricing,

• Vehicle value insights over loan period,

• When will delinquency occur?

• Projected loss given the vehicle

• Next vehicle purchase

Scores & Triggers: multi-

source data

• Credit Risk score,• Bankruptcy risk

score• Lead score

Scores & Triggers: single

source data

• Delinquency status and history,

• Balances,• Number of

accounts

Attributes

• Credit accounts, • Marketing Data• Utility Data• Payment Data

Data

Marketing Intelligence

Customer Prospecting

Customer Acquisition

Customer Management

Debt Management

Equifax has solutions across the Consumer Lending Life-cycle


A Few Operational Notes

This webinar is intended for researchers & scholars. It should not be published or presented without permission from WCAI.

Questions about our research program or for press inquiries:

[email protected]

To get access to the data, research teams must submit a proposal to WCAI and the sponsor for approval. More details at the end of this presentation.

10TRANSFORMING BUSINESS THROUGH CUSTOMER DATA


Data Sneak Peek…


• Credit File: 1- 3% randomly selected consumers full credit file

• Attributes: Advanced Decisioning Attributes • Monthly snapshots from 2010/01 to 2015/12

2010/01

2010/02

2015/12


Credit File Example

Credit Accounts(aka Trade lines)

Credit Inquiries

Public RecordsCollections

John Doe 123-45-6789

12

KNOWLED GE FOR ACT ION 13

Advanced Decisioning Attributes | Equifax

Text

Advanced Decisioning Attributes

Attribute Processing

John Doe 123-45-6789


Example of Advanced Decisioning Attributes


John Doe123-45-6789

14

Trades

Past Due

Balance

• Number Trades• Number of Auto Trades• Number Bankcard Trades• Number Department Store Trades• Number Installment Trades• Number Revolving Trades

• Total Past Due Amount• Total Past Due Amount Bankcard Trades w/Update w/in 3 Months• Total Past Due Amount Installment Trades w/Update w/in 3 Months• Total Past Due Amount Retail Trades w/Update w/in 3 Months• Total Past Due Amount Revolving Trades w/Update w/in 3 Months• Total Past Due Amount Trades w/Update w/in 3 Months

• Percent Balance to High Credit Open Bankcard Trades w/Update w/in 3 Months• Percent Balance to High Credit Open Department Store Trades w/Update w/in 3 Months• Percent Balance to High Credit Open Revolving Trades w/Update w/in 3 Months• Percent Balance to High Credit Open Retail Trades w/Update w/in 3 Months• Percent Balance to Total Loan Amount Open Auto Trades w/Update w/in 3 Months• Percent Balance to Total Loan Amount Open Installment Trades w/Update w/in 3 Months


Conceptual Entity-Relationship Diagram

15


Example Trades Table

Table Name Column Description

Trades

C_ENTITYID A unique consumer id assigned to the consumer record by the source system.Archive The date the archive was created in the source system.Date Reported The date the account was reported to Equifax from the data provider.Date Opened The date the account was opened or first established with the credit grantor.High Credit The highest amount of credit ever extended to this consumer on this account.Credit Limit The maximum amount of credit that can be extended to the consumer on this account.Balance The amount still owed on the account.

Past Due Amount The amount that has not been paid within the agreed upon time frame per the specified terms or payment period of the contract.

Portfolio Type The credit or loan type of the instrument used to grant credit to the consumer.

Rate/Status Code This field contains either a numeric rate or a non-numeric status code for the most current month the account was reported.

Account Designator (ECOA)A code that indicates the consumer's relationship and payment responsibility for the account.

30 Day Counters The number of times the account has been reported as 30 days late60 Day Counters The number of times the account has been reported as 60 days late90+ Day Counters The number of times the account has been reported as 90 days latePrevious High Rate1 The most recent previous high rate.Previous High Date 1 The account reported date for the most recent Previous High Rate being reported.

Previous High Rate 2 The 2nd most recent previous high rate.

The trade table contains consumer trades information.

16 16

KNOWLED GE FOR ACT ION TRANSFORMING BUSINESS THROUGH CUSTOMER DATA 17

QUESTIONS


Possible Research Areas

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• Continuous updating approaches for risk score analytics

• Are there general-purpose approaches to detecting anomalous consumer behavior that could be used to detect fraud and reporting errors?

• Is it possible to completely automate the process of translating information from raw credit files into attributes/scores without human intervention?

• How can we precisely denote the level of certainty of a consumer’s credit score?

• Something not on this list!

TRANSFORMING BUSINESS THROUGH CUSTOMER DATA


Research Area 1

Continuous Updating Approaches for Risk Score Analytics


Data Snapshots

Month 1 Month 2 Month 3 Month 4 Month 5

• Massive changes in the macro-economy cause scoring models to become outdated quickly

• We are interested in methods for automatically updating credit scoring models

• Preference towards Bayesian approaches


Research Area 2

General-Purpose Approaches for Detecting Anomalies


• Anomalies in consumer behavior can be fraud cases, but other possibilities abound, e.g., unusual payment patterns in credit file, etc.


Research Area 3

Automating the Translation of Raw Credit Information into Attributes/Scores


• We are interested in machine-learning approaches to determining the right variables from consumer event data for calculating credit scores


Research Area 4

Confidence Measures for Risk Assessment


• How can we precisely denote the level of certainty/uncertainty of a consumer’s credit score?

• We are particularly interested in consumers with high income but thinner credit files, recent immigrants vs. long-term residents, etc.


QUESTIONS

KNOWLED GE FOR ACT ION 24

Data

Attributes

Scores

Triggers

DecisionStrategies

DynamicInsight

INSIGHTSUNIVERSITYDATAPANELENVIRONMENT

AttributeNavigator

VisualAnalytics

ModelDevelopment

(R,Python)

ModelIntegration

Tool

Metadata D ataand Model Governance Secu ri ty

ConnexusKeying

AttributeNavigatorExecution Engine

ZementisModelExecution Engine–PMML

Data I ngestion,S tandardizationandHy giene(ETL+ Data Pump+ Hadoop-basedTechnologies )

BigDataStore(Offline)

Governance

InsightsWorkbench

EquifaxData Customer Data Third-party Data

RulesEngine–DecisionPolicy

CAPABILITIES§ StorepetabytesofdatainHadoopclusters

§ Processbillionsofrecordsinminutes

§ Bringtogetherdifferentdatasourceswithinasingleenvironment

§ HighPerformanceAnalyticaltoolstorunmultiplemodels

§ Visualizationtoolstohelpunderstanddata fasterandpivot,asnecessary

HighPerformanceComputing– UniversityDataPanel


Environment Demo…


VDI Login Screen VDI Storefront Apps


Software Tools

• R and RStudio (Open Source version)

• SQL – HIVE and Impala as part of Cloudera Eco system

• HUE – To access Job browser, File Browser and Meta data

• MS Excel

• MS Word

• Google Chrome Browser

• Firefox Browser

• Python



User On-Boarding Process


• Unique opportunity to access credit risk data

• Three-tier process for on-boarding academic researchers1. Proposal Submission (and acceptance)2. Background Check3. Access to the data granted by Equifax

• Data cannot be downloaded from Equifax’s secure environment.

• Equifax will review requests to extract results in order to ensure that only results (and not the data itself) leaves the secure environment.

• The process protects all consumers, including you!


QUESTIONS


Proposal Format

29

Proposals should be in PDF format, no more than 2,000 words, and include the following information:• Title• Author(s) name, title, affiliation and e-mail address: Please designate a corresponding author.• Summary information: a single “slide” that visually summarizes team & project.• Abstract• Introduction: Describe expected contribution(s), covering both the academic and practical aspects. Please

keep it concise, and cite relevant work as necessary to explain your academic contribution. There is no need to include a lengthy literature review.

• Detailed project proposal: Please include enough detail that we can assess the feasibility & merit of the proposed approach. For example, modeling projects should include at least a sketch of the model. In addition, include a rough estimate of how long the project will take. Also include the business relevance of your research and the impact for the sponsor as well.

• Data Needs: Bulleted list of data required or requested for analysis not explicitly mentioned during this webinar. While we can’t guarantee the inclusion of these items, we are happy to investigate the availability.

• Biographies: Include up to a paragraph-long biography highlighting what each team member will contribute to the project.

• Tools: List the software tools you plan to use for your research



Proposal Submission Process

30

• Read more about the proposal format and Submit Proposals here:http://wcai.wharton.upenn.edu/for-researchers/get-the-data/

No later than Tuesday, May 31st, 2016, @ Midnight US Eastern

– Proposals will only be accepted online

– A single PDF combining the written portion and the single slide

• Proposals will be evaluated both on academic contribution and potential to significantly improve the research sponsor’s marketing practice by the proposal review committee:

Eric Bradlow (WCAI), Pete Fader (WCAI), Elea Feit (Drexel University), Brian Dalessandro (NYU), Jane Dokko (U.S. Treasury) and

representatives from the Corporate Sponsor of this dataset

• Contact [email protected], if you have questions prior to submitting your proposal.



Other WCAI Opportunities for Researchers

31

If you registered for this webinar, you will receive regular announcements regarding:

• Upcoming Research Opportunities:

- Identifying & Maintaining Great Financial Advisors

Also find us at:

• SSRN Research Paper series: http://www.ssrn.com/link/Wharton-Cust-Analytics-Initiative-RES.html

• Sign up for updates: http://wcai.wharton.upenn.edu/newsletter/


understanding the past, present, and future economic ... · knowledge for action equifax (nyse:efx)...

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