Technology is transforming the way businesses work and the role that people play in creating and delivering value to their customers. Innovation is impacting the world beyond consumer goods and services and is now affecting a wide range of expert professions, such as accountancy. In the field of taxation, innovative technology is encouraging tax authorities to introduce new digital taxation requirements, whilst also helping businesses improve the efficiency and effectiveness of how they meet these rapidly-changing compliance obligations.
Advances in artificial intelligence in particular, are shifting the future of taxation, with machine learning applications helping tax authorities and taxpayers analyse very significant volumes of financial information in seconds, to a high degree of accuracy. Traditional compliance processes that were often considered mundane and potentially error-prone will soon be a thing of the past.
As a branch of artificial intelligence, machine learning is not only changing the future of tax, but also the future of work. Charles Brayne, EY UK and Ireland’s lead Partner for tax technology states that over the next three years new and emerging technologies will deliver a transformational change to the lives of tax professionals like himself:
“Historically, a lot of what we have done has been linked to our ability to read and interpret accounting data, then apply the appropriate categorisation from a tax perspective. There are sometimes huge complexities around that categorisation, which in turn has made the task of automating the decision through traditional technologies enormously difficult. However, with the advent of new machine learning applications that continuously refine and improve their analysis, we are starting to see a new generation of tax technology tools that deliver quality results at lightning speed. That changes the day-to-day activities – not just for my team and the people I work with, but for my clients too.”
Pulling together the right skill sets
EY has identified the traditional areas of tax accounting and compliance work that can be done in new and different ways. Brayne mentions that the EY tax practice has had to ask itself: “If we don’t effectively embrace these technologies, how are we going to be relevant to the clients we work with going forward and how can we introduce them to the very same technology?” Brayne recognises that the skills required to design, develop and use these new technologies are not yet found in the more traditional training programmes for accountants and tax professionals, so there is a need to think very differently about the type of people he needs in his team. As part of this initiative to pull a very different set of skills and capabilities together, the first recruit for his team was senior data scientist, Harvey Lewis.
Lewis, who’d used advanced technologies to solve highly complex analysis and classification challenges in past roles, was charged with looking at the work of EY tax with technology in mind. “We have since then brought in business analysts, software developers, we’ve brought in quality assurance developers, user experience designers and built a technology business in tax. This has opened up very different possibilities for us”, Brayne explains.
Change is possible
DeGusta thinks that it has become increasingly possible to change the traditional ways in which insurance companies have worked in the past. “If you’re still working with the fax machine, you are probably going to go the way of the fax machine. So insurers realise they need to change, and from our perspective as a partner it’s important for us to understand why they haven’t adopted these technologies in the past, and to provide a solution that addresses those problems while moving them forward”, he says.
There are varied reasons why certain technologies and innovations haven’t been adopted, and so ClarionDoor works with its customers to find out what they are, and how to resolve the issues affecting their ability to use them to innovate. He claims this represents an “exciting opportunity” to assist companies that have historically struggled with technology projects to work with a partner that understands that technology is only part of the solution. People and processes often matter just as much, if not more, than the technology itself.
He then approaches the subject of how artificial intelligence; machine learning; and automation can help insurance companies to innovate: “The potential is amazing, and it’s very exciting that people are thinking about it, but one of the things we’re thinking about is about how to help insurance companies to easily try these new techniques and see the potential impact, for instance on the prices existing customers would pay, or the decisions underwriters make?”
Today there isn’t enough focus on automating innovation; every new idea or data source that an insurance company wants to use, first has to go through a lengthy sequence of emails, meetings and IT projects. “We are trying to focus on how we automate that process to enable companies to get from where they are today to that promised land of automated, intelligent underwriting and selling”, he explains.
It goes without saying that data has been the epicentre of modern insurance. Data is everything to an insurer. Insurance companies traditionally compared their polices against their claims to consider how they relate to each other. Now, with the abundance of external data available, they have the ability to go further, analysing why customers didn’t buy their policies or why they didn’t sell to certain people. The cause may be pricing: was it too high? By using this data, you can find out more about customer profiles to find out what they look like, and what motivates them.
DeGusta explains: “The real opportunity here is that insurers now have the ability to create more innovative pricing models based on a larger data set, rather than just relying on their own data. Building models, based on their own data, only captures the profiles of consumers or businesses that have already purchased their products. Often insurers don’t even capture or study the customers they quoted who didn’t buy – we make sure all of that is available for analysis.”
To create innovative products, and to attract new customers while retaining existing ones, insurers need this extension of data to avoid limiting their outreach. By avoiding such limitations, they can connect with the broader market. “So, with the influx of data that extends beyond just what the insurer holds, they enable more innovation in their products”, he adds.
Delivering a quality outcome
Complex analysis can be made simpler and more immediate through machine learning technology. However, Brayne says that the benefits extend beyond efficiency. “We still need to prepare returns as well as reports and that requires us to analyse thousands of lines of data. Doing this across multiple countries is a huge undertaking and it goes without saying that the analysis needs to be right. Interestingly, we’ve found that the technology not only performs at speed, but it is also highly accurate when it comes to identifying areas of legislative uncertainty. This means that whilst up to 70% of the effort is removed from standard compliance and accounting tasks, our tax teams are able to focus their attention on areas of higher risk. Overall, we are seeing technology increase the quality of the work performed.” He sees this as a significant and positive change.
Freeing up resources to add value
In the short to medium term, Brayne expects more fiscal authorities around the globe to adopt similar technologies. This will lead to the collation of more data, more quickly than ever before, from their taxpayer base. He warns that if organisations don’t adopt technologies capable of analysing and processing this data at speed, they will end up “embracing risk and that’s not a good place to be.”
He also says that organisations that don’t embrace technology will find themselves missing out on the current opportunity to free up existing tax professionals from repetitive tasks that don’t add a lot of value. “There are many activities undertaken by tax professionals that are not yet susceptible to advanced technologies and continue to require empathetic human skills. These include negotiating with tax authorities, working collaboratively with stakeholders, advising business partners on new developments, dealing with unprecedented events, and more. Why not focus experienced resources on these areas and leave the machines to what they do best?”
Changing the future of work
He then emphasises that there is no need to be frightened of artificial intelligence. “We shouldn’t be looking at these technologies and thinking that they will diminish the role played by humans in the future, or that this is all about cost-reduction and people losing their jobs; it’s not about these things at all, it’s about embracing the technologies and the opportunities they open up. That’s the message I give to my teams, and it’s the message we share with our clients.”
However, as vital as it is to understand the limitations of people, it’s also important to comprehend the limitations of technologies as they currently exist, to ensure that they are used appropriately, effectively and efficiently.
Brayne is confident that much of the work that tax professionals do from an advisory perspective will continue for many years to come. Tax is unlikely to get less complicated any time soon. However, it’s important to assess the tax activities that technologies can or can’t perform to comprehend what organisations should be doing differently. The aim of embracing technology is to change the future of work for the better. It is possible to achieve this with the help of digital transformation, machine learning and continuous innovation.
To find out more about EY’s Tax Technology and Transformation campaign, visit ey.com/uk/taxtech
Charles Brayne is a Partner in the UK and Ireland for tax technology, you can follow him on LinkedIn here.