Domestic Tax Conference28 April 2016 | New York City

11th Annual

Big data analytics – Impact on tax management

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Disclaimer

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This presentation is © 2016 Ernst & Young LLP. All rights reserved. No part of this document may be reproduced, transmitted or otherwise distributed in any form or by any means, electronic or mechanical, including by photocopying, facsimile transmission, recording, rekeying, or using any information storage and retrieval system, without written permission from Ernst & Young LLP. Any reproduction, transmission or distribution of this form or any of the material herein is prohibited and is in violation of US and international law. Ernst & Young LLP expressly disclaims any liability in connection with use of this presentation or its contents by any third party.

Views expressed in this presentation are those of the speakers and do not necessarily represent the views of Ernst & Young LLP.

This presentation is provided solely for the purpose of enhancing knowledge on tax matters. It does not provide tax advice to any taxpayer because it does not take into account any specific taxpayer’s facts and circumstances.

These slides are for educational purposes only and are not intended, and should not be relied upon, as accounting advice.

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Today’s presenters

Michelle WalligExecutive Director, Ernst & Young LLP

Ross ChristenExecutive Director, Ernst & Young LLP

Emilio Amalfitano Executive Director, Ernst & Young LLP

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Agenda

Pleasant disruptionNew foundations in tax data management► Guiding principles► A new approachEnterprise tax data management and analytics► Component layers of a big data solution► Iterative approach based on value, needs

and efficiency► Core feature functionality and how it relates

to taxPanel discussion

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Pleasant disruption

Michelle Wallig

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Why now?

Disruptive technology has evolved:► Same technologies Google and Facebook use now

available to tax► Search multiple sources of data, PDFs, emails, code

and regulations, etc.► Ability to absorb new sources of data rapidlyBenefits to tax:► Availability of detailed data to the tax organization:

► Transactional detail, prior tax returns, exemption certificates

► Extendable to audit, planning, and all parts of the organization

► More efficient integration of acquisitions and dispositions

► Reduced risk due to centralized data and master data governance

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Defining tax data reporting and analytics

Load tax process software

Prepare work papers

Review transactions

Respond to audits

Analyze accounts

Discover business trends

Monitor risks

Track tax positions

Track and manage effective tax rate and cash tax rate

Monitor transfer pricing

Tax-influenced business decisionsData analytics often describes

many different activities:

Agile tax data management is scalable, supports the entire tax function and facilitates

business decisions.

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Big dataFour Vs in tax data management

Four Vs of big data > Volume Velocity Variety Veracity

Direct ► General ledger (GL) documents

► Journal entry (JE) adjustments

► Provision ► Dozens of source systems

► Hundreds of GLs► Work papers

► Reconciliation of GLs to transactions

Controversy ► Multiyear transaction detail

► Accounts payable (AP)/accounts receivable (AR)

► Access to data > 3–10 years old

► Dozens of source systems

► Hundreds of GLs► Work papers

► Accuracy to the tax return

International ► Supply chain (order to cash)

► Operational data

► Country to corporate level data access

► Foreign exchange (FX)► Corporate structures► Country laws

► FX issues► Currency conversion

issues

Indirect ► Sales tax► Value-added tax (VAT)

► Point of sale transactions

► FX► Exceptions

(e.g., import VAT, output VAT)

► Data quality issues in transaction data

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Benefits of a big data solution

Tax functions Benefits

Direct ► One view of all GLs, documents, adjustments from all sources► Ease of reconciliation between provision, return, uncertain tax positions (FIN 48), Foreign Account Tax

Compliance Act (FATCA), country-by-country (CbC) reporting

Controversy ► Access to archived data across multiple years, all transactions from AR/AP including work papers, GLs► Bridgeable between audited financials and source data

International ► Reconcile statutory to generally accepted accounting principles (GAAP)/International Financial Reporting Standards (IFRS) to tax including FX impacts

► Transparent legal entity ownership, transfer pricing, customs, base erosion and profit shifting (BEPS)

Indirect ► Efficient surfacing of exceptions, data quality issues, return filings, absorption of acquisitions► Potential to access all transactions across the enterprise

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Role of data in effective tax operations

► Tax functions are the heaviest users of enterprise data.

► Tax processes and technology depend on high-quality, tax relevant, enterprise data.

► The quality and, therefore, the value delivered by tax operations are directly impacted by the data flowing into tax processes and enabling technology.

► Tax “owns” no data and has little influence over the systems and processes that record transactions.

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Tax value case for stronger tax data management

What would you do with 20% to 40% more time from your department professionals?

How much tax time is spent managing data manually?

Do you have the right data skills in or available to your

department?

Which tax positions could be enhanced with better data?

Are current controls addressing the inherent risks of “bad data”?

Which audit adjustments could have been better or completely

avoided with better data?

Are tax and treasury working from the same data set to make cash management decisions?

Which corporate initiatives would help tax move closer to being a data-driven function?

Would better tax data management allow more effective

use of shared service centers (SSCs)?

Which planning positions would be enhanced with more relevant data?

Have you “passed” on planning opportunities due to data concerns?

Efficiency

Effectiveness

Control

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Tax software vendor tools at a glance

Key features► Big Data Management Console (in memory, columnar store, massively

parallel processing)► New Analytics User Interface for visualizations, reporting and analysis,

and predictive analytics► Global Reporting, Entity Management and Charting ► Hundreds of Finance specific Excel add ins► Tight integration with SAP core modules – FI/CO, Business

Warehouse, Business Objects

Key features► Improved tools for data management and analytics based on IBM stack► Integration with open data sources such as Twitter

SAP HANA IBM Watson analytics

Key features► Cloud based data architectures (HDFS)► Advanced programming languages (Pig, Hive)► Scalable, flexible, affordable (OpEx vs. CapEx)► Structured data and unstructured docs in data lakes► Leverages capabilities of numerous applications and reporting and

analytics tools from legacy (Excel) to new visualization tools (Tableau, Spotfire, Qlik) and statistical tools (R)

Key features► Data management with ability to import data from hundreds of sources

and export data to multiple tax applications► Supports multiple FX and accounting ledgers► Stores current and historical financial data► Gathers transaction data from multiple ERP and e-commerce platforms► Reporting and analytics tool using Cognos, Tableau

Hadoop/open source Vertex enterprise

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New foundations in tax data management

Ross Christen

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Guiding principlesTax data management

Centralized tax data management

Tax data is treated as an asset of value

Solution is driven by the vision and enabled by tools

Tax data is accessible by tax professionals

Data-driven tax measurements and decisions

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Tax data dilemmaTraditional tax data flow (income tax)

Traditional tax data flow considerations:► General ledger is “general.”► Trial balance is only the starting point.► Tax calculations are based on detail.► Finance/accounting is in the business of summarizing

information, yet tax reverts to them for more data.► Finance/accounting reverts to operations and

source systems.

Gen

eral

ledg

er

Accounting/finance

Tax

Disallowances

Accelerations

Intercompany

Credits

Reporting

Operations

Sell

Buy

Invest

Make

1

2

4

5

5

3

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The many-to-many relationship between transaction data and tax domain needs

Business transactionsSell

Buy

Invest

MakePlan

and

fore

cast

Rec

ord

and

repo

rt

Income tax

Provision

Sales/use tax

Forecasting

Sales/use ProvisionTransfer pricingGlobal trade US

federal

VAT ForecastsState incomeEffective operating

model

Credits and incentives

Common interface to data

Modular tax discovery and analytics suites

Tax domains

Tax data management

solution

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q

Enterprise tax data management and analytics

Emilio Amalfitano

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This is what tax data management used to look like …

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Enterprise tax data management road map

Align Acquire Conform Store Supply

Tax data and document repository(on-premise or hosted solution)

Co/outsource/in-house solutions and processes

Managed tax service support

Tax data management Key performance indicators, overviews and collaboration

Tax processsolutions

Security, quality, controls, retention and traceability

Tax search

Process views

Workflow, calendar, andstatus reporting

Global provision and forecast

Country-levelcompliance

Tax planning Supply chain reporting and analysis

Tax audit management

VAT suite

Sales/use suiteTransfer pricing suiteEffective tax rate suite

Cash tax suiteForecasting suite

Credits and incentives suiteIncome tax suiteStatutory reporting suite

Acquire and

conformSupply

Tax data analytics

AlignSystems of record

Other source data

Enterprise resource

planning (ERP)

Transaction tax engine

Other TBD

Social media content

Big data Store► Financial► Nonfinancial► Industry content► Benchmarks► Social media

Analyst benchmarks

Audit adjustments

Court cases

ProvisionGlobal

compen-sation

Statutory reporting

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Old vs. new paradigm

Solution Pros Cons

Traditional data warehouse (DW)

► Rigid standardized data model► Strict data standards► Manages structured data ► Technology/resource availability

► Data mapping intense (total cost of ownership and expense)

► Slowest time to market► Difficulty in handling unstructured

data requirements

Tax data management services

► Agile-based approach for rapid prototyping and development

► Faster time to market► Data extract and reporting similar to

traditional data warehouse approach► Reduced reliance on data modeling► Provides a discovery component► Managed service or in-house

► Data marts still needed like traditional DW► Technology resources not as

readily available

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Panel discussion – stories from the field

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In summary, the technology evolution happening today has opened many opportunities for tax departments to work more effectively, efficiently and with greater control of their data.

Domestic Tax Conference28 April 2016 | New York City

11th Annual