Digital Finance - Deloitte United States · 2 Deloitte Client Deloitte end-to-end redaction support...
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Digital Finance Roadshow 2020 Next Generation of Deal Making
Transcript of Digital Finance - Deloitte United States · 2 Deloitte Client Deloitte end-to-end redaction support...
Digital Finance
Roadshow 2020
Next Generation of Deal Making
Deloitte 2020 2
Digital Finance - Next Generation of Deal Making
Topic
Recap Roadshow 2019 – Advanced Text Analytics
Deloitte M&A Radar - A tool to simplify and support the M&A origination process
Org Radar - Visualisation and Intelligent Analytics for Organisational Optimisation by Deloitte
Artificial Intelligence – AI Innovation Services at Deloitte
Digital Finance - Next Generation of Deal Making
Recap Roadshow – Advanced Text Analytics
Deloitte 2020 4
Introduction – what is Smart Contracts?
DocumentsStructuredinformation
Through sophisticated searches over content and metadata, relevant contracts are identified and grouped by work stream
Quality assurance through four-eyes principle followed by in-depth review and analysis as required; export to a structured format
Review & export
Read documents, perform deduplication and OCR, and identify language, document types and faulty files
Relevant fields are defined. In an iterative process, suggestions for the data points are made automatically and manually reviewed, improving quality with every learning cycle
Train & tag
Smart Contracts
Quick review: Locate and structure relevant contracts
Deep analysis: Review contracts and extract relevant
information
Classify & groupPre-process
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Smart Contracts – classical vs. AI-enabled approach
Scanned or digital PDF documents are assembled, structured and reviewed
Relevant data points are identified and reviewed manually
Data is retyped into an excel or similar database
Slow
Expensive
Inconsistent
Assemble and review documents
1,000 Documents
Extract data for analysis
Exported results are quickly validated by dedicated trained reviewers
~4 WEEKS TURNAROUND€€
Documents are uploaded through an automatically processed and structuredinterface and
Provisions are identified, highlighted and extracted in real time, leveraging AI
Fast pace
Reduced cost
Improved accuracy
~20 WEEKS TURNAROUND
€€€€
-
-
-
+
+
+
Classical approach AI-enabled approach
Identify relevant
information
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Key benefits of using Smart Contracts
Accelerated resultsQuickly analyze documents through the optimized interface and automated workflow. Save resources by significantly reducing the time needed to identify, structure, and review contracts
AI-enabled self-learning Documents reviewed by human experts feed into a learning cycle to provide better and more accurate suggestions at consistent quality. Complete with 4-eye reviewing capability, audit trail and overview of data source and origin
Type and structure agnosticSupports over 140 languages and is accurate even with different document types and layouts
Highly scalableA built-in workflow to streamline processing large volumes of documents and a solid review process generate reliable data
Structured outputLeverage formatted and structured data directly in downstream solutions
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Innovative Use Cases for Automated Contract Analysis
Carve-out Contract Separation
• Ensure Day 1 readiness wrt contractual coverage of the carve-out unit
• Know and mitigate financial and contractual risks related to contract assignment
• Minimize one-time and ongoing costs
Ethics Risks in Research
• Identify and structure relevant contracts including historical documents
• Perform automated risk-scoring using metadata, content search and automatic classification
• Find and extract risk-relevant clauses for manual review of high-risk contracts
Redaction of Legal Clauses
• Define sensitive clause types per contract type
• Identify and, if required, review sensitive clauses
• Automatically redact identified clauses via integration with industry-standard redaction tools
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Machine-aided VDR support by Deloitte within a large scale international Carve-out
Globally acting client with more than
7500 employees
“Sub” Carve-outs due to
competitive law requirements
11 countries in scope
Key player in international
petrochemical industry
1,5bn Carve-out with ~2500
employees in scope
Supported by
Analytics
enhanced PMO
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Details / deep dive next slide
Year
Month 1 Month 2 Month 3 Month 4 Month 5
Preparation
a) Initial data collection (~4000 docs)1)
b) Redaction
Q&A phase / expert sessions
Rolling provision, redaction and upload of documents (~1000 docs)1)
Seamless machine-aided redaction process by Deloitte
VDR opens
5 daysInitial data dump
Q&A begins
Data uploaded in VDR1 dNew data provided
1
2
Deloitte
Client
Deloitte end-to-end redaction support
21 3 4
Data uploaded in VDR
Provision of client data to Deloitte Carve-out team
Redaction by Deloitte analytics team
GDPR compliance checks
Preparation of Data for VDR upload
Upload into VDR
1) multiple formats and languages
Deloitte Client Details / deep dive next slide
Deloitte 2020 10
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
T~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Automated redaction process – Deloitte Assisted Redaction (DAR)
Patterns & Lists
• Names• Addresses• E-mails• Keywords• …
Document Set
T~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~~~~~
Sample
> Example list
Input DAR Validation Output
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Key benefits of using DAR – Worthwhile to consider for your next deal?
Skyrocketing quantities ~3000 documents in 96 hours
Rapid processing48h during Q&A phase
Highly scalable due to built-in
workflow to streamline processing large volumes of documents
Low costs through reduced manual
effort and efficient use of time and resources
High flexibility facilitates usage in
states of high uncertainty
Automated processing of
complex and inhomogeneous data in various languages
One interface due to of end-to-end
process
Consistent quality through
repetitive and automatically applied redactions and a solid validation process
Superior type and structure agnostic supports nearly all common
data types and delivers accurate and consistent results
CheaperBetter Faster
Deloitte 2020 12
Contacts
Thomas Menzler
Partner
DE - München
Financial AdvisoryOperational Transaction
Services
Michael Dornauer
Senior Manager
DE - München
Financial AdvisoryOperational Transaction
Services
Klara Weiand
Senior Manager
DE - Berlin
Financial AdvisoryAnalytics
Thomas Fritzsche
Partner
DE - Berlin
Financial AdvisoryAnalytics
Maximilian Wevers
Senior Manager
DE - Düsseldorf
Financial AdvisoryAnalytics
Digital Finance - Next Generation of Deal Making
M&A Radar
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… AS A RESULT WE DEVELOPED THE M&A RADAR
OUR CLIENTS OFTEN TELL US…
A tool to simplify and support the M&A origination process
Deloitte M&A Radar
Structured support to identify M&A targets would be a
strong value add
A comprehensive and predictive tool which allows for benchmarking
will significantly enhance our analysis process
We want to be one step ahead of our competitors with information
and insights that are not readily accessible
The M&A Radar is a Deloitte system that combines different data sources, AI, predictive technology etc. into one single tool to empower our clients during the M&A
process and reduce time to market.
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From data to action
Deloitte M&A Radar
DATA01 TRANSFORM02 ANALYSE03 ACTION04
SHORT LIST TARGETASSET LONG LIST
INVESTOR(i.e. competitor)
INDUSTRY
Self-learning AI Engine
M&A Radar
SEtc.
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Selection of successful visits at various clients
Deloitte M&A Radar
Prospective Meetings:
A significant number of additional meetings have been set up
Client: PE with small-cap focus
Discussion points: Follow up of 23companies in the Consumer, Tech,
Services sectors X
Client: PE with large-cap focus
Discussion points: Companies
>€400m revenue analyzed in
various sectors
Client: PE with large-cap focus
Discussion points: Deep dive of
24 companies in various sectors
Great tool - we
should be
using it on a
regular basis!
Feedback from clients
We attempted building
a tool but lacked the
expertise to make the
development viable
It was incredible to be
introduced to so many different
companies I would have
normally not come across
Meeting follow-ups
• Provide short company profiles (1 Pager) for the identified companies• Provide discussion papers (20-30 pages), as applicable• Connect client with relevant Deloitte experts • Provide market overviews • Ongoing monitoring of selected companies by Deloitte BD team; contact client
as soon as company comes to market
Client: PE with small-cap focus
Discussion points: 17 assets
identified and analyzed across all
sectors X
Client: PE with mid-cap focus
Discussion points: Review of 11companies in various sectors
Client: PE with mid-cap focus
Discussion points: Analysis of 13companies in the Consumer sector
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A flexible database and visualization tool with further planned capability expansions
Deloitte M&A Radar Outlook…
UPCOMING UPDATES
Expected upcoming deals (i.e. Opportunity
Newsletter)
Web Scraping (capture loose data)
Analyst reports as well as other company
generated reports
Additional sources (i.e. Pitchbook, Capital IQ etc.)
Strategic and other M&A active companies
Expanding regions until the tool is global
Additional information / KPIs
Industry etc. expertise and trends
ADDITIONAL DATA EXPANDED SCOPE
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AI POWERED DEAL ANALYSIS
One Global Tool to empower the M&A process and reduce time to market
Deloitte M&A Radar Outlook…
DEAL ORIGINATION
Predictive technology
matching assets to
potential buyersEmpowering
the M&A process
ONEGlobal Tool
TREND IDENTIFICATION
Algorithms analyzing trendsto identify related deal opportunities
BENCHMARKING
Dynamic benchmarking analyses including deal support comparisons
KNOWLEDGE
Customizable access to focused information for origination and deal realization
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Deloitte M&A Radar
Self-learning AI Engine
M&A Radar
SEtc.
Contact us to see how the M&A Radar could work for you
Deloitte 2020 20
Contacts
Sharmeen DreesPhilipp Spyra
Partner
DE - Frankfurt
Financial AdvisoryTransaction Services
Senior Manager
DE - Düsseldorf
Financial AdvisoryC&I Opportunities
Digital Finance - Next Generation of Deal Making
Org Radar - Visualisation and Intelligent Analytics for Organisational Optimisation by Deloitte
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ORG RADAR
A pragmatic, bottom-up, intuitive tool todiscover simplification and cost reduction potentials in your organisation by directly identifying implementable measures “on the fly”.
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Organisational Efficiency & Hygiene – Rationale
Running Cost Improvement - Framework
RADICAL OPTIMISATION OF PERSONNEL COSTS
Non-addressable personnel costs
(e.g., due to scope)
Total personnel costs prior
optimisation
Addressable personnel costs
Gross potential based on
organisational anomalies (tactical)
Gross potential based on broader
organisational improvement (structural)
Adjustment after calibration with top management and functional leaders
Total personnel costs after
optimisation
-€…b
A
TACTICAL
opportunities on badge-ID level
STRUCTURAL
opportunities, e.g., shadow-org.
Deloitte approach for Org. Efficiency & Hygiene
1 2
Radical optimisation of personnel costs requires full transparency of ‘as-is’ situation enabling comprehensive detection of all ‘organisational anomalies’
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Organisational Efficiency & Hygiene – Methodology
Running Cost Improvement – Our Solution: Org Radar
Our innovative methodology and digital accelerators allow new perspectives on organisational structures – a more holistic and specific perspective at the same time
• Visualisation of 10,000+ roles and more within one single chart
• Allows fast + intuitive navigationwithin even complex org. structures (zoom-in & -out within seconds)
• Immediate and objectified view regarding org. hygiene principles
• Possibility to detect thousands of ‘org. anomalies’ and inefficiencies
• Coloring of nodes by HR attributes for multi-dimensional assessment
• Ability to unlock even hidden potentials (shadow organisations)
• and many more…
CONVENTIONAL ‘CARTESIAN’ ORG. CHARTS RADIAL ORGANISATIONAL CHARTS ADVANTAGES OF INNOVATIVE APPROACH
CEO
CEO
L1L2
L3
L4L5
L6L7
L1
L2
L3
∑ ~1,500 roles∑ 50 roles
Highest possible resolutionand big picture at the same time
Limited possibilities forholistic org. hygiene assessment
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Organisational Efficiency & Hygiene – Selected Levers
Running Cost Improvement – Our Solution: Org Radar
We conduct multi-dimensional analyses to create a new level of transparency and unlock even hidden improvement potentials to streamline the organisation
Selected Levers for Organisational Optimisation
Multi-dimensional HR attributes allow fast identification of improvement potential
SPAN OF CONTROL
• Reporting layers
• Managers w/o report
• Functional outliers (incl. sub-functions, job titles)
• Geo outliers
• Salary outliers/compensation schemes
• Management grading
• Low-cost vs. high-cost countries
• Workforce composition
• Etc.
15
20
0
5
10
7
No. of directreports
No. of managers1
• Area corresponds to €...m of fully-loaded personnel costs
• Typically, over 20%+ of roles within large-organisations are flagged after multi-dimensional assessment
• Conversion rate of role elimination opportunities strongly depending on need for action by top management
• Additionally, org. hygiene principles and future design dimensions to be defined along major competing dimensions (i.e., regions, functions, business line/products)
1. Manager defined as role within organisation with at least 1 direct report
25
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Org Radar - intuitive visualisation and intelligent analytics of organisational structures
Summary
Intuitive core visualisation. The radial core visualisation of Org Radar makes discovering anomalies and fragmentation in organisational structures much easier.
Intelligent analytics. The analytics capabilities of Org Radar allow our clients to unveil simplification and cost reduction potentials in their organisation.
Flexibility and fully interactive drill-down capability. Org Radar offers various filtering and drill-down options that can be easily adapted to our client’s preferences.
Identification of implementable measures “on the fly”. Redundant layers, hanging managers, outliers in span of control or salary bands, functional and geographical fragmentation.
Versatile dashboards. Analyse the distribution of organisational levels across departments, compare functional units across regions and explore high/low cost country exposure.
Deloitte 2020 27
Contacts
Thomas Rotter Dr. Alexander SticklerDr. Philipp Kinzler
Partner
DE - München
Financial AdvisoryRestructuring Services
Senior Manager
DE - München
Financial AdvisoryRestructuring Services
Manager
DE - Frankfurt
Financial AdvisoryFA Analytics
Headline Verdana BoldDigital Finance - Next Generat ion of Deal MakingThink big - Start small - Scale fast: Startups as Driver of AI Innovation
FA – Roadshow 2020
Digital Finance - Next Generation of Deal Making
What can startups do for you? AI Innovation Services at Deloitte
Deloitte 2020 29
Technological change is increasing rapidly, creating a continuous dynamic with far-reaching changes.
Technological cycles
• Computers in
offices
• Mini computers
• Word processing
• Spreadsheets
• Computers for
home use
T E C H N O L O G YC O R E
T E C H N O L O G YE N A B L E M E N T
T E C H N O L O G YC O L L A B O R A T I O N
T E C H N O L O G YE N G A G E M E N T
D I G I T A L
E X P O N E N T I A L
• Mainframe-
computers
• Comprehensive
distribution of
computers
• Network computing
• Relational databases
• Client-server
applications
• Internet revolution
• “Browser Wars”
• Customer loyalty
• Intranet
applications
• Broadband internet
• Smartphones
• Tablets
• Cloud computing
• Big data analytics
• Social media
• Wearables
• Sensing
• Home automation
• Smart car
• Cryptocurrency
• Quantum computer
• 3D printing
19701980
19902000
2010
2020
Deloitte 2020 30
The last ten years of IT have been about changing the way people work. The next ten years of IT will be about tranforming your business.
Aaron Levie, CEO of Box
Deloitte 2020 31
AI is the ability of computers or machines to perform tasks that are typicallythought of as requiring human judgement or intelligence
Types of AI Specific domains and applications of AI
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What can AI do for you?
Make the same decisions faster
e.g., improve customer experience by responding real-time while they are shopping online, or assess transaction risks in real-time.
Make better decisions
e.g., connect the shop floor to the ‘top floor’ with business intelligence and data visualization to build preventative approaches for equipment maintenance.
Make the same decisions cheaper
e.g., combine data from inside and outside your organization to add richness and granularity to better understand your customers or business performance.
Make innovations in products and services
e.g., provide location-based services to maintenance managers using connected devices, equipment and other physical assets in the ‘Internet of Things’.
Deloitte 2020 33
Ethical, moral and
legal concerns
Limited availability of AI experts in the market
High costs of expertise and technologies
However, many corporates face obstacles when developing AI themselves
Integration in existing
processes and systems
No trust in AI
Deloitte 2020 34
BERLIN
Sectors: FinTech, Artificial Intelligence, Big
Data/Analytics, Internet of Things, Blockchain
Venture Capital: $2.9bn / Startups: 1 200
SILICON VALLEY
Sectors: FinTech, Artificial Intelligence, Big
Data/Analytics, Life Sciences, Adv. Manufacturing &
Robotics, AdTech Gaming
Venture Capital: $39bn / Startups: 10 200
TEL-AVIV
Sectors: Cybersecurity, Artificial Intelligence, Big
Data/Analytics, Life Sciences, Manufacturing &
Robotics
Venture Capital: $0.9bn / Startups: 700
Venture Capital
No. of Startups
Ecosystems
Also, AI is happening everywhere fast… and sometimes even better
Deloitte 2020 35
Increased complexity and decentralization require new innovation processes
Deloitte 2020 36
We decode every single AI startup funding and founding in Europe to anticipate where markets are heading so you can make informed decisions
We guide you through.
WE ANALYSE & DECODEAI innovation signals to build better assets
for our clients, the market and Deloitte.
Every time someone founds a new venture, this
entrepreneur is placing a bet on a future.
Every time someone invests into a startup, this investor
is buying a stake of the future.
Deloitte 2020 37
GERMAN AI MOONSHOTS
VISIBLE ON THE HORIZON?
DOMESTIC FUNDING STILL
ON A LOWER LEVEL
35% of German AI startups generate revenues < €1 million
40% of the startups surveyed expect growth rates of >50%
65% of the startups surveyed operate scalable business models
BUT, HIGH GROWTH
RATES
1.2bnOver the past ten years, German AI startups have raised venture capital of €1.2 billion.
<20%Of this, however, the proportion of German venture capital was less than 20%.
80%of AI ventures in Germany have collected a maximum of one seed round.
45%of all German AI startups have < 10 employees.
1/17Only 1 out of 17 Ventures that are part of the AI Unicorn Leaderboard are born in Europe (Graphcore).
>60%more AI startups in Germany, compared to the previous year.
50%of the sampled startups claimed to be working on AI solely for marketing purposes.
AI is becoming a strategically important sector for Europe and it will continue to be a driver for winning innovation strategies
AI Startup Market Intelligence
Deloitte 2020 38
2020 German AI StartupLandscape
AI TECH STACK
500+STARTUPS
BUSINESS INTELLIGENCE & CONSULTING
DOMAINS
Agriculture
Automotive, Travel & Mobility
180+ 80+ ENTERPRISE FUNCTION 200+
40+
Business Intelligence & Consulting
Research & Development
Consumer Products & Retail
Defense & Security
Fintech / Insurtech
Life Science & Healthcare
Human ResourcesInfrastructure, Real Estate & Home Living
Multi-Functional
Processes & Automation
Manufacturing & Logistics
Communication
LegaltechMedia, Sales & Marketing
Infrastructure, Real Estate & Home Living
Consumer Products & Retail
Life Science & Healthcare
Defense & Security
Agriculture
Fintech / Insurtech
Automotive, Travel & Mobility
Manufacturing & Logistics
Processes & Automation
Business Intelligence & Consulting
Research & Development
Human Resources
Media, Sales & Marketing Legaltech
Communication
Multi-FunctionalEven an advanced
model with a narrow scope will have a
hiccup or two, usually.
There are already a few AI startups that are actually building their own platform,
interfaces and networks, but what does that tell us?
The horsepower required to build the model varies greatly depending on what kind of AI is being
leveraged.
The dirty secret of AI is that the lion´s
share of work usually revolves around
finding the right data and getting it into
shape.
Based on our research, there is a large gap between startups who have achieved some mastery of AI Tech and the rest who have not
Finding AI startups is not hard… but understanding their real value proposition requires expertise
Deloitte 2020 39
Collaboration in global Deloittenetwork, data ingestion by crawling engine and additional APIs
Data cleansing, data enrichment and real-time update of relevant information, e.g., description, website and funding
Pre-classification by domain community, complete mandatory fields
Startup self-assessment
Deloitte Due Diligence Light (Commercial and AI Tech) based on proven and uniform approach
Project-specific Due Diligence (Red Flag and confirmatory report)
We get in touch with the founder team directly and put the venture and their AI algorithms to the acid test
Discover AI startups, emerging technologies and winning business models
RELIABLE
DATA
DOMAIN
INSIGHTS
#1 DEEP TECH
LEADER
SAFETY &
SECURITY
THOUGHT
LEADERSHIP
Deloitte 2020 40
We support you in ideation, screening, scouting and application of Artificial Intelligence
End-to-end AI innovation service offering
AI START AI CHALLENGE AI SCOUTING AI INTEGRATION
AI NEW GROWTH
FACTORY
Based on your specific problem and pain points, we identify AI use cases and winning AI innovation strategies for your company with our Design Thinking coaches and product designer.
Find the best idea for your AI challenge on our collaborative innovation platform. We offer access to a large network of AI startups, experts, researchers and industry partners.
Find the best partner in our curated AI startup portfolio with our AI Scouts, who have a direct contact with relevant startups.
Implement the AI solutions in your productive environment with our experts in all relevant domains.
Develop completely new AI technologies and startups as contract work with us.We invent, develop, test and scale-up the necessary structures to establish the young venture quickly and successfully on the market.
IDEATE SCREEN, SCOUT & MATCH APPLY
Deloitte 2020 41
Enhancing Credit Risk Assessment
Natural Language Processing (NLP)
Automatic analysis of company reports to assess credit risks and allow improved investment decisions
SituationInternal credit risk assessment is carried out manually.
ProblemMore available data and regulatory requirements increase efforts for individual analysts.
Solution A product concept aiding the analyst by automating
core steps of fixed-income analysis steps.
The text mining approaches include different levels of text granularity – word, topic, text.
Process automation and machine-learning-improved methods secure competitiveness.
Word Embedding
Keyword Extraction
Machine Learning Topic Modelling
Term-Frequency Analysis
Sentiment Analysis
What methods were used?
Deloitte 2020 42
Developed and validated a new business model, incorporated and ramped-up a new FinTech company, built and launched Scorable, an AI-based SaaS credit risk assessment tool
Impactwww.scorable.comBuilding the AI FinTech Scorable
Initial idea
Ampega Asset Management identified the opportunity for an AI-based credit risk assessment tool as an offering for 3rd party users
Built and launched product
Conducted user tests with early adopter clients and developed several prototypes before publicly launching Scorable’s first release
Ramped up venture
Incorporated and operationally ramped up the new company, hired a team of 30+ people and developed Scorable’s brand identity
Developed venture concept
Evaluated market need and business case, developed a product concept and validated the idea’s technical feasibility to secure funding
Deloitte 2020 43
Automated information extraction from documents to reduce repetitive tasks
Optical Character Recognition (OCR) and Computer Vision (CV)
SituationStructured and scanned documents were processed individually and by hand. The information needed to be registered and cross-checked with a data base to validate the corresponding client information and initiate necessary action.
ProblemRepetitive task that consumed time.
Solution Standardization of incoming documents and
preprocessing scans by CV techniques.
Information extraction with OCR and object detection.
50% faster and leaner processes.
Confidential and document specific parser(75% confidence rate). Machine Learning
Object Detection
OCR Feature Extraction
Productive Docker Solution
What methods were used?
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Impact of digital tools on your company’s mostrecent transactions
M&A Digital Accelerators
35 %
40 %
51 %
53 %
HOW HAS THE USE OF DIGITAL TOOLS AND ACCELERATORS
IMPACTED YOUR COMPANY’S MOST RECENT TRANSACTIONS ?
Provided additional insights to our model
Minimized risks and uncertainties through
more analysis in the diligence phase
Helped plan for post-close
operations / integrations
Increased speed to close
“Sellers are sharing more data.
With the right digital tools and
techniques to analyse that data,
buyers get significantly better
information than was
previously possible with a team
of people pounding away on
spreadsheets.”
ANDY WILSON
PARTNER, M&A SERVICES
DELOITTE & TOUCHE LLP
Deloitte 2020 45
AI Use Case landscape for the deal lifecycle
PRE - DEAL DEAL EXECUTION POST-CLOSING
• Automated combined financials
(for MergeCo)
• Automated Carve-Out Financials
• Automated due diligence process with
natural language processing and
generation
• Real time target screening, market
sensing and deal matching with
sentiment analytics
• Leverage AI to generate standardized
& fit for purpose Day 1 Planning and
Blueprinting deliverables
• Assisted VDR document classifier, data
extraction (e.g., table miner) and
analysis (financial, HR, IT, Legal, Ops)
• Automated synergy initiative identification
• Continuous environment scanning
and competitive game boarding
• Intelligent bots to automate manual
Command Center and PMO activities
• Harness and master data with
natural language processing
• Advanced valuation & modelling
analytics (peer group analysis,
benchmarking, WACC derivation, …)
• Automated financial benchmarking in
the peer group
• Machine Reading Comprehension for
Bidder Engagement in Question
Answering
• Virtualizing Blueprinting &
Walk the Walls with Augmented Reality
• Cultural readiness assessment using NLP+
++
Deloitte 2020 46
We screen and scout AI startups to boost digital transformation of your business model and to start winning growth stories based on credibility and trust.
We anticipate disruption relevant for your business model and support you from ideation to integration, of course, also in the event of AI incubation and co-creation.
Become a central point of our European AI ecosystem and discover AI domain insights.
Connect with us
Deloitte 2020 47
Contacts
Jan Hasse
Senior Manager
DE - Köln
Financial AdvisoryAnalytics
Oliver Salzmann
Partner
DE - Düsseldorf
Financial AdvisoryAnalytics
Deloitte 2020 48
You need further information about our Financial Advisory Events?
Nadine Schönlau
Senior
DE - Düsseldorf
Financial AdvisoryC&I Eventmanagement
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