Artificial Intelligence (AI) is a form of computer science used to create intelligent machines that can recognise human speeds, objects, can learn, play and solve problems like humans. AI can support companies in performing accounting and legal tasks within limited amount of time. AI can replace a lot of monotonous tasks, thus we will be more technologically advanced in accounts. It allows us to focus more on ‘A’ factor, i.e. analysis, & support us in interpreting the data based on past trends.
I read a quote written in book “Mathematical Corporation” by John Sullivan published in 2017 which is quite fascinating, extracts of which is as follows, “The most powerful weapon in business today is the alliance between the mathematical smart of machines and the imaginative human intellect of great leaders together they make the mathematical corporation, the business model of the future”. AI not only eradicating mundane task and enhancing precision, however, also bringing radical changes at macro level with huge reduction in cost and increase in productivity. It is no surprise that decision makers see building explainable AI solutions as a competitive advantage.
One form of AI is Natural Language Processing (“NLP”) which is quite beneficial for finance department. NLP is the natural language which is analysed by computers. NLP could be used in finance to comb thousands of legal documents and contracts, which are basically knowledge repository that contains critical data on organizational commitments, rights, remedies, and rules that reflect business decisions made in the past that will affect performance in the future, within limited amount of time, in turn help us in finding changes in control provisions. One can also use AI to review accounting standards, for example, leases, every time there is a change in lease standards, companies have to search through thousands of leases to comply with new standards. Further, it could be used to search through prospectus of investments to examine whether the security complies with the Volker Rule.
Millions of invoices are processed each year and as per my understanding, use of machine learning is easy to detect anomalies in invoices, it will result in accurate invoicing and further if we see the larger picture, it could in turn help us to support legal laws as well, as invoices which involve international parties, accurate invoicing helps us in avoiding serious consequences. Further, machine learning not only help us in making invoice testing much more efficient, however, also support in analysing the invoices, hence provide audit comfort.
Consolidation could be performed via AI by easily extracting the data from multiple sources because of involvement of machines, thereby will give us more time for creating business strategies.
NLP can be used in mergers via automating research on target segment activity and thereby enabling intelligence collaborations by way of monitoring and understanding cultural similarities and differences of two companies, fostering interactive alignment by leveraging qualitative input across a large spectrum.
One can track the changes in price among multiple suppliers via AI by vanishing the hassle of incompatibility between different file formats received from multiple suppliers; in turn aid in creating improved procurement system.
AI not only support in speeding the reconciliation process, however, also pin point fraudulent transactions promptly. Without AI, though through cutting edge software, things have been easier in finding discrepancies between internal accounts of business and bank accounts, however, quality of output is as good as quality of data entry. With AI, there has been sweeping shift for the better. Smacc, a German based software firm, uses AI to help freelancers, small companies and medium sized enterprises to automate their accounting systems and financial reporting.
AI also plays a vital role in risk management. According to the Association of Certified Fraud Examiners, the average organization loses 5% of its annual revenue to internal fraud. Organizations and auditors can typically only audit 10% of expense reports manually, leaving the majority of potential fraud to go undetected. AI, on the other hand, can audit up to 100% of spend reports along with doing expense management. Further, purchase orders, employee receipts, travel bookings and credit card transactions can be automatically scanned for purchases made outside of policy, thus enabling us to quickly correct the errors, in turn, support in abiding corporate policies.
Natural language generation is another AI tool where text can be generated by computers. Natural language generation can be used to process thousands of tax returns annually, even for clients having expat status or having other complicated tax situations.
AI is also very useful in banking sector. Hedge fund’s use of AI is accelerating and reshaping the industry, particularly in investing, cost models and recruitment. In 2018, Barclay Hedge’s Survey found that over half of hedge fund’s respondents (56%) used AI to inform investment decisions. Two-third said they used AI to generate trading ideas and to optimize portfolios and just over a quarter used automation to execute trades.
AI not only support us in processing & generating data, however, also aid in resolving queries arising from users in timely manner via AI Chabot’s. Integrating AI into Customer Relationship Management (“CRM”) also aid in improving revenue numbers. It will ensure that customers will no longer be offered products and services that are inappropriate basis their requirements. The North Face, a large e-commerce retailer, is great example of a company stepping up their game by using AI to better understand their customers.
Question to ponder upon is after creating super intelligence life, will it impact the job market? Remember, when we were on verge of advert of internet, same worries about the future surrounded us, however, lead to creating more opportunities for us. It only resulted in making our task easier and now we can hardly recollect a day spend without Internet. Change is constant; however, change brings with it the need for planning the future, which is already now. It’s high time now to learn how to interact with smart machines irrespective of our primary skills.
[This article is intended for academic discussion only. Author can be reached at garimamittal@live.in for academic discussion]
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