INTRODUCTION
There is a curious
story unfolding in the technology environment today. While dramatic advances
are being made in emerging spaces such as 5G communication, artificial intelligence
(AI), virtual reality (VR) and augmented reality (AR), these tectonic shifts
are erupting at dizzying speeds, triggering confusion at individual levels.
Paradigm shifts, game-changing breakthroughs and once-in-a-lifetime events are
now converging in the same time frame, adding to the hype on the timeline for
benefits.
The developments
bring to mind an oft-repeated quote of Microsoft founder Bill Gates: ‘We always
overestimate the change that will occur in the next two years and underestimate
the change that will occur in the next ten.’
Admittedly, there are barriers and impediments such as concerns about
privacy and data security, combined with natural reluctance and resistance to
change, that will slow the progress. However, public interest in transparency
and accountability is likely to settle the competing objectives of transparency
and confidentiality with appropriate regulatory restrictions on the use,
storage and transfer of data.
While the debate
about the pace at which the quantum leaps in technology will develop and how
quickly they will affect the tax professions continues, there is no doubt that
markets are already moving: preparing for and indeed expecting to see progress
and adoption of these technologies and these changes.
META-TRENDS IN TECHNOLOGY IMPACTING TAX
PROFESSION
In any case,
regardless of the current experience, developments in various technologies will
continue to be transformational, influencing both professional and personal
lives. The following are the five meta-trends in technology that will
materially affect the tax profession in the future:
(1) Data – big data
sets, massively improved performance and memory capacity at scale;
(2) Process automation –
robotic process automation and integration of financial and other systems;
(3) Decision-making –
AI augmenting compliance and consulting capabilities;
(4) Democratisation of knowledge – publicly available and easily accessible knowledge and
information: A ‘Google for tax rules’;
(5) Open networks –
talent sourcing, crowd problem-solving and sharing eco-systems.
These patterns will
characterise the way tax regulators change and how organisations must react.
These patterns are, likewise, open doors for organisations and may frame the
establishment of any digital tax strategy and associated transformation.
(1) DATA
The phenomenon of
‘big data’ is having a dramatic impact on the way tax work is undertaken. The
increasing processing power and capacity of machines removes any limitation on
the amount of data that can be analysed.
The granularity of
data that is usable; the way transactions are recorded and accessed; real-time
reporting; and unlimited time-periods for data retention and storage will
transform the application of tax rules regulation. Instead of data sampling,
estimating and extrapolating, the professionals will be working with precise
and complete data sets. Very soon, the businesses will be at a point where the
details of all transactions can be quickly and easily classified and
investigated for tax purposes.
Besides, the way
transactions are effected will change with greater digital impact on
transactions and dealings between taxpayers and tax authorities and judicial
bodies. For example, the Income-Tax Department has already started deploying
data-mining and data analytics by linking various big data from internal as
well as external sources such as Statement of Financial Transaction (SFT), data
received from Investigation Wing, information received under Automatic Exchange
of Information (AEOI), FATCA, Ministry of Corporate Affairs and GSTN to identify
persons / entities who have undertaken high-value financial transactions but
have not filed their returns. Several tax administrations around the world have
started providing pre-filled returns and automating various tax compliances
based on comprehensive and accurate third-party data available with them.
In some territories, tax authorities already
require full accounts payable (AP) and receivable (AR) ledgers (with
invoice-level detail) and subsequent periodic trial balance financial ledgers
to be submitted. These countries include Brazil, Poland, France and Spain
(where AP and AR ledger details are required to be provided within four days of
the invoice issuance). India, too, will join this club once e-invoicing is
rolled out.
The Organisation
for Economic Co-operation and Development (OECD) in its report on ‘Advanced
Analytics for Better Tax Administration – Putting Data to Work (2016)’
highlights that several tax administrations (including Ireland, Malaysia, the
Netherlands, New Zealand and Singapore), in addition to building statistical
models to predict VAT fraud or error, are carrying out Social Network Analysis
(SNA) to help detect VAT carousel fraud (a VAT carousel is a complex form of
missing-trader fraud which exploits the VAT-free treatment of cross-jurisdictional
sales) and other group-level risks. SNA helps administrations to identify risky
groups in situations where individual-level assessments may fail to detect
anything of concern. It identifies links between individuals (for instance, through
company directorships, joint bank accounts, or shared telephone numbers) and
assembles connected individuals into easily visualised networks. Case-workers
can then browse these networks to profile individual risks. Equally, the
networks can be scored for risk using either a rules-based assessment or a
statistical model trained on historical data. This report also provides an
overview of the application of advanced analytics by various tax
administrations for:
(i) audit case selection,
(ii) filing and payment compliance,
(iii) taxpayer
service,
(iv) policy
evaluation,
(v) taxpayer segmentation.
(2) PROCESS AUTOMATION
In the past data
collection has often been ad hoc and laborious. It typically requires
analysis and rework of data to classify for tax purposes. Businesses have
worked on structuring their data and recording it in their financial and other
systems, and more recently have adopted technologies such as robotic process
automation to streamline collection processes.
Today, multiple tax
compliance solutions help in generating accurate tax returns by leveraging data
collected as part of core business functions. In future, this is likely to
change dramatically. Increasingly, the classification of transactions will be
automated using machine learning applications that perform text-based search
and apply preset rules, learning from previous analysis to predict the
appropriate tax treatment.
AI will do the job
without needing to rely on upfront recording in structured accounting ledgers
or after-the-event manual review and allocation in spreadsheets. Combined with
the increase in the extent of data to work with, these cognitive technologies
will produce a much higher degree of accurate tax classification for all
transactions and business events that taxpayers undertake.
(3) DECISION-MAKING
AI will have a
similarly dramatic impact on the application of tax judgement. These same
cognitive technologies improving data classification will enhance the
professional’s decision-making capabilities: machine learning, pattern
matching, fuzzy logic and natural language processing will allow complex tax
analysis to be undertaken by technology. These developments pose a significant
opportunity to reduce time and effort, improve quality and accuracy and
ultimately to raise the bar of what can be achieved.
A leading firm has
developed a tax-related application for large organisations with complex tax
affairs in the area of classifying expenses for correct treatment in the
corporate or indirect tax returns. This application goes beyond rules-based
solutions, using ‘human eye matching’ (fuzzy) and artificial intelligence,
where the tool ‘learns’ from the user’s tax decisions. The tool can rapidly
analyse complete sets of data, eliminating the risk of both human error and
sampling. In addition to its versatility which allows it to cater to a variety
of compliance-related needs, this tool offers a fully documented process that
reports on the decisions made and tax positions taken. Software features allow
the reviewer to focus on the most important or contentious decisions, which can
be manually overridden if the reviewer is uncomfortable with the machine’s
decision. Time savings are realised immediately as analyses that would
otherwise be done manually have been automated, while the evolving rule set can
be rolled forward to future years which builds further efficiency over time.
All in all, the tool makes a considerable contribution to effective tax risk
management at a time when tax authorities are bringing increased pressure to
bear on taxpayers.
In the US, there
is now a system that can predict the outcome of the US Supreme Court decisions
as accurately as leading legal scholars. It ‘knows’ or ‘understands’ nothing
about the law. Instead, it makes a prediction based on 200 years of case data,
each one described by up to 240 variables (the nature of the case, the justices
involved and so on).
The eighth edition
of the OECD’s Tax Administration Series Report (2019) provides insight into how
several tax administrations have adopted the use of behavioural insights and
analytics to better understand how and why taxpayers act and to use these
insights to design practical policies and interventions. It cites the example
of the Inland Revenue Authority of Singapore (IRAS) and how it complemented the
use of Business Intelligence (BI) with analytics to encourage taxpayers to pay
their overdue taxes as early as possible. IRAS built predictive models to
identify taxpayers with high payment compliance risk, before incorporating
uplift modelling to select and contact taxpayers who were more likely to
respond to interventions, i.e., outbound calls which enabled IRAS to focus its
compliance efforts on the high-risk taxpayer group and to apply BI
interventions strategically to achieve greater impact and efficacy.
(4) DEMOCRATISATION OF KNOWLEDGE
Some 15 years ago,
an in-house US tax team might have approached an adviser and asked what the tax
rate was in, say, India. The adviser would have looked it up and maybe checked
with its local contacts in India and then written back with the answer – for
which he would have charged a time-based fee. Today this seems very unlikely.
Unless there are some severe complications, the in-house tax team would have
direct access to this information through a variety of online sources. This
trend will continue and, over the next five years, practitioners will get ever
more sophisticated access to information and knowledge of the tax rules and
regulations to which they are subject. Besides, increasing transparency and
access to information and knowledge will have implications for global tax
policy and will change the interaction between authorities and taxpayers.
(5) OPEN NETWORKS
Online work
platforms have grown significantly in many areas of the economy. Labour
platforms such as Guru.com with some 1.5 million people, Upwork.com and
Mechanical Turk (mturk.com) are creating widespread networks of freelancers
available for task-based work. Tax teams are no longer entirely based on
traditional or full-time employees.
However,
crowd-sourcing or open talent models in the tax market seem further off when
compared to the use in IT, graphic design and finance. This situation is likely
to change over the next three to five years as three distinct developments in
tax converge. The tax professionals will require new skills around data,
analytics and technology. The breaking down of tax processes into individual
tasks through automation and standardisation will highlight specific work
routines that could be allocated to new workers not needing deep tax skills.
The evolution of the sharing and social economy will better connect potential supply
and demand and open new resource pools keen to work in different, remote and
virtual ways and within different reward models.
TOMORROW’S TAX WORLD
The combined effect
of these broader technology developments will bring about a sea change in the
way tax authorities and other regulators meet their objectives and manage their
responsibilities.
There has already
been a significant shift towards e-administration with increasing options and
uptake of online filing of tax returns as well as online payments and the full
or partial pre-filling of tax returns. Digital contact channels (online, email,
digital assistance) now dominate and the number of administrations using or
developing mobile applications continues to grow. Electronic data from third
parties, including other tax administrations, as well as internally generated
electronic data, is used in an increasingly conjoined way across tax
administration functions for improving services and enhancing compliance. This
trend also shows in the large number of administrations that now employ data
scientists.
Revenue authorities
already require large volumes of data to be filed. They have defined the
structure and format in which data needs to be maintained and provided. For
example, filing schemas and standard audit files like SAF-T, an international
standard for the electronic exchange of reliable accounting data from
organisations to a national tax authority or external auditors, defined by the
OECD, are being widely adopted.
Gradually, most tax
authorities will be requiring fuller data sets to be filed or made available
and in real-time or close to it. Indeed, they are likely to move beyond this.
Rather than require the data to be filed and managing the transfer and storage
of large volumes of data, they may simply mandate the algorithmic routines that
they require to be run across data sets and then review the results.
This real-time
access to the taxpayer’s financial data will save the effort of data transfer
and rely on taxpayers to maintain a digital record. Such a development will
also accelerate the time at which revenue authorities can review and
investigate a client’s information.
TOMORROW’S TAX PROFESSION
These developments
pose an essential question: What will be the nature and volume of future work
for professionals? When the impact of automation and augmentation increases,
what will tomorrow’s workforce do to replace the time currently spent on
today’s processes? Ultimately, what will be the right balance between human and
machine?
Daniel Susskind and
Richard Susskind also raise the following profound questions in their book ‘The
Future of the Professions’:
- Might there be entirely new ways of organising professional work,
ways that are more affordable, more accessible and perhaps more conducive to an
increase in quality than the traditional approach?
- Does it follow that
licensed experts can only undertake all the work that our professionals
currently do?
- To what extent do we trust
professionals to admit that their services could be delivered differently, or
that some of their work could responsibly be passed on to non-professionals?
- Are our professions fit for
purpose? Are they serving our societies well?
They have
identified the following changes that are taking place across various professions
that are relevant to the tax profession:
- More-for-less challenge
– Across the professions, institutions and individuals are being asked to
deliver more service, with fewer resources at their disposal.
- Existence of new
competition – Many of the technology-driven changes are being driven by
people and institutions outside the boundaries of the traditional professions
(often tech startups), with very different training and experience to
traditional professionals.
- Productisation of
services – Many professionals think of their work as a form of craft, like
an artist starting each project afresh with a blank sheet of paper, or akin to
a tailor stitching a suit to fit the particular bodily contours of his clients.
Now we see a move away from that view, recognising that professional work does
not have to be handled in this bespoke way.
- Increasing decomposition
of professional work – Many professionals think of their work as solid,
indivisible lumps of endeavour that must all be handled by particular types of
professionals, working in certain ways, organised in specific forms of
institutions. Increasingly, however, we are instead seeing professional work
being broken down into composite tasks and activities. Once this is done, it
often becomes clear that the work can either be performed by non-professionals
or can be automated.
- Increasing
commoditisation of professional work – When professional work is broken
down in this way, it transpires that many of the tasks involved in it are not
particularly complicated, they are relatively ‘routine’ and can be automated
accordingly.
A TECHNOLOGY-BASED INTERNET SOCIETY
The Susskinds see a
different set of models for producing and sharing practical expertise emerging
as we evolve into a technology-based internet society:
(A) Networked experts or ‘workers on tap’ model –
Here, it is still professionals that are involved in producing practical
expertise. However, rather than being employed in a particular brick-and-mortar
institution (a firm, hospital or school), professionals instead use online
platforms to work in a far more flexible, more ad hoc way in solving
professional problems. Doctors-on-Demand in medicine and Axiom Law in the legal
world are two examples.
(B) Para-professional model – Here, less
expert people, using new technologies, can perform tasks that would have
required more expert people in the past. Take the medical diagnostic system
developed at Stanford. It is entirely conceivable that in primary care of the
future, one may not necessarily be treated by a doctor but by a nurse
practitioner who, using one of these systems, can offer the sort of diagnostic
support that might have required a more expert person in the past.
(C) Knowledge-engineering model – This is
what we were doing in the 1980s: engineering systems, derived from the
knowledge of experts, for non-experts to use (in our case, to help solve legal
problems). Many readily-available online DIY tax preparation software and
contract-drafting tools rely on this model.
(D) Communities of experience model – Social
networks are now a ubiquitous feature of contemporary life. Also familiar are
professional networks, where practitioners gather to share their expertise.
Less familiar, though, are communities of experience – where patients, rather
than practitioners, meet to share their experience and advice. Take, for
example, PatientsLikeMe, an online network of more than 600,000 patients who
come together to share experiences of their symptoms and treatments, receiving
support and solving problems that might have required more expert medical
professionals in the past.
(E) Embedded knowledge model – To grasp
this, consider the card game Solitaire (also known as Patience). If this game
is played with physical playing cards and a player tries to put a red five
under a red six, this is possible (even if it is called ‘cheating’). Putting
two cards of the same colour on top of one another is, of course, against the
rules. Now imagine a player who is playing the same game but on a smartphone.
If the player tries the same move, it is not possible for him to do so because
the system simply returns the offending card. The rules are embedded in the
system. A breach is not merely prohibited, it is impossible to perform.
Likewise, as more of our lives become digitised, practical expertise will not
be invoked through the intervention of human beings but will be embedded in our
everyday systems instead.
(F) Machine-generated model – Here,
increasingly capable systems and machines produce and share practical expertise
without any human involvement. Of the six models, this is the most radical,
where traditional recipients of professional work would have access to
technologies that obviate the need for human experts altogether. Although this
scenario is the most widely discussed in the popular debate, it is essential to
keep in mind that this model is only one of six.
While digital transformation will require significant change and pose
considerable challenges, that future will also offer significant opportunities.
It seems clear that revenue authorities will embrace technological change and
use it to gain access to global data sets and thereby create more tax
transparency. This development will increase the demands on tax professionals
coming from increased complexity, rapid change and heightened risk. However, by
embracing the new technologies for handling and analysing data, tax
professionals will be able to improve compliance processes, enrich their tax
analysis and provide greater understanding and value to their organisations.
Over the short
term, it appears that there will be more work to do in both managing the change
and the consequences it will lead to: The greater accuracy that the new
technologies will offer and require for both tax processes. Moreover, the
nature of that work will be different. The digital transformation will reduce
time spent processing, improve analytical capabilities and create significant
new opportunities for businesses to manage their tax obligations.
It’s difficult to
be precise about what the tax digital future will be like, but certain
characteristics seem clear. As a society and as professionals:
(a) We will be data-driven, leading to a more
holistic approach at the enterprise level. We will manage that data better. We
will harness its power to act faster, provide richer insights and create
business value for the organisations we serve.
(b) Big data will lead to greater granularity,
precision and accuracy. We will work with integrated data sets, including all
aspects of the underlying transactions – both the structured and unstructured
data elements. It will result in enhanced analysis in detail rather than
sampling and estimation.
(c) Algorithms will increasingly be the way we
apply our expertise, our knowledge and experience. Furthermore, we will need to
apply that expertise earlier in processes as real-time reporting takes hold and
accelerates the times at which data is submitted.
(d) Robots will take more of the strain. Robotic
process automation technologies will evolve, become easier and cheaper to
deploy and as a result will become ubiquitous tools for professionals to use to
streamline processes. Besides, they will become smarter, infused with AI, and
therefore have a greater impact.
(e) The user experience will be more digital. We
will consume information in a more personalised way through the video and other
mixed reality media. At the moment, work in systems such as email involves
interacting through a keyboard. In the future, we can expect much more use of
natural language processing, talking to virtual agents and connecting through
online forums.
TOMORROW’S TAX PROFESSIONAL
With these dramatic
changes will come a significant impact on the tax professionals’ lives – how we
work and what we do. The relationships and roles within our organisations and
with advisers will be different. They will be expected to do more work earlier
in the process as transactions are recorded, or internal controls put in place,
and also in the later stages, in areas of controversy and dispute resolution.
Consequently, the
skills and capabilities required will be very different from today with a blend
of ‘automation and augmentation’ impacting the workforce. Manual processes will
be replaced by automation of data flows and the impact of robotic process
automation. At the same time, professionals will be augmented by AI
technologies embedded in the ways knowledge is accessed and experience used to
apply it to business circumstances. An example of this is an AI-driven tool
that can act as a virtual research assistant that can help in searching for
relevant case laws, analysing rulings and assessing whether a tax case is
likely to be successful.
The above
transformation will trigger a complete overhaul of the processes and the
resource models to get tax work done. Tax processes will be broken down into
individual tasks and allocated to new workers not always needing deep tax
skills. For example, several BPO firms carry out tax return compilation and
filing work on a large scale by employing graduates who work with the tax
return preparation software with minimal training. The evolution of the sharing
and social economy will open up talent networks, crowd-sourcing models and the
so-called ‘gig’ economy to the tax marketplace on the lines of examples given
under the networked expert or workers on tap model above.
The skills required
for tomorrow’s tax professional will continue to include the traditional skills
such as core technical expertise (to deal with increasing complexity in the
ever-changing tax and regulatory landscape) and professional ethics; the tax
professional will need to imbibe additional skills such as:
(I) Increased technology skills specifically with
respect to the familiarity with continuously changing applications such as
specialist tax software, electronic tax administration platforms and also other
disruptive technologies, such as artificial intelligence / digital assistants,
to augment their output.
(II) Business and commercial skills to think and
align tax and business strategy.
(III) Risk assessment and management skills in
respect of tax positions taken, corporate structures, existing and emerging
laws, regulations, political initiatives and shifting public perceptions.
(IV) Communication and collaboration to manage
relationships – engage, interact, influence and inform stakeholders in finance,
statutory audit and tax administrations. Ability to translate tax jargon for
non-technical stakeholders such as boards, management, investors, clients and
media.
(V) Advocacy and negotiation. Advocacy for tax
policy and strategy. Dispute resolution – internal and external.
SUM IT
Change for tax professionals is just round the corner. Like other
professionals, they, too, will continue to ride the rapid wave of technology
changes and associated risks as humankind continues to pursue the digital
future. While it is difficult to predict decisively what the future holds, the
meta-trends are recognisable in the technologies today as we try to anticipate
and shape our plans accordingly.
At the same time,
we must also realise that in five years we may be working with technologies
that are yet to be invented. Hence, riding the crest implies tireless
monitoring of developments and agility in experimenting with and adopting new
technologies. The new road for tax professionals could be fraught with no speed
limits as the pace of digital transformation hastens. The professionals must
map out the potential impact of all disruptive technology and actively engage
with the emerging trends. Relentless evolution and adaptability will continue
to be the cornerstones, while yet retaining their core strengths.
In this context, it
may be worth remembering Mahatma Gandhi’s recommendation: ‘The future
depends on what we do in the present‘.
REFERENCES
1. Deloitte (2019), ‘Our digital future – A
perspective for tax professionals’; https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Tax/dttl-tax-deloitte-our-digital-future.pdf
2. OECD (2019), Tax Administration 2019:
Comparative Information on OECD and other Advanced and Emerging Economies;
https:/doi.org/IO.1787/74d162b6-en
3. OECD (2016), Advanced Analytics for Better
Tax Administration: Putting Data to Work;
http://dx.d0i.org/10.1787/9789264256453-en
4. Susskind R. and Susskind D. (2015), ‘The
Future of the Professions: How Technology will transform the Work of Human
Experts’
5. Diamandis
P. and Kotler S. (2020), ‘The Future Is Faster Than You Think’
