AI and Automation in Finance - Possibilities for the future

The need to process mammoth financial data quickly, is lending itself to proliferation of applications that use AI, Machine Learning and Deep learning

Mindtree
Published: 27, Sep 2017

Mindtree delivers digital transformation and technology services from ideation to execution, enabling Global 2000 clients to outperform the competition. “Born digital,” Mindtree takes an agile, collaborative approach to creating customized solutions across the digital value chain. At the same time, our deep expertise in infrastructure and applications management helps optimize your IT into a strategic asset. Whether you need to differentiate your company, reinvent business functions or accelerate revenue growth, we can get you there.

AI’s unprecedented speed, accuracy and cost efficiency have encouraged CFOs to consider its adoption in the Finance and Accountingfunctions (Photo: Shutterstock)
AI’s unprecedented speed, accuracy and cost efficiency have encouraged CFOs to consider its adoption in the Finance and Accountingfunctions (Photo: Shutterstock)

Artificial intelligence (AI) is poised to disrupt the lives of individuals, the societies we live in, and the global economy, causing both excitement and trepidation.  It goes beyond doubt that AI will automate tasks that have long required human labour.  In fact, AI’s unprecedented speed, accuracy and cost efficiency have encouraged CFOs to consider its adoption in the Finance and Accounting functions. This is especially true considering the scarcity of trained workforce and investment constraints to handle increasing volumes of data. Essentially, the finance professional is facing a changed paradigm where he/she needs to juxtapose their valuable judgement alongside AI’s predictive results in a variety of settings.

Unknowingly, automation is deeply entrenched in any Enterprise’s infrastructure -- be it invoice processing, financial accounting or business analytics. There is also an increasing need for Managers to interact with intelligent machines in more collegial ways, taking information they have through conversation or intuitive interfaces, and generating information hitherto not available.  Interestingly, the need to process mammoth financial data quickly, is lending itself to proliferation of applications that use AI, Machine Learning and Deep learning.

Tapping AI to maintain the competitive edge A few working examples will help put this emphasis on automation into perspective.

We believe human activities revolve around five high-level components: data, prediction, judgment, action, and outcomes. This classification continues to remain the bedrock of all our experiments with automation. Incidentally, Financial Institutions are already using predictive algorithms combined with big data to model risk related to Value at Risk (VaR), credit ratings, economic capital, predicting borrower behaviour, portfolio tail risks, Know Your Customer (KYC) and anti-money laundering.

Automation in Accounting
Simultaneity and Immediacy are monikers that define efficiency within organizations. The last few days in a month has accounting teams fretting, frowning and scurrying around to meet their deadlines for invoicing and publishing revenue. Here, is where Automation has an answer! Imagine an application that translates business processes into machine-readable rules that auto generate invoices (data).  Consequently, the same application, in seconds, automatically derives revenues (prediction and judgement) and posts them into the target financial systems (action).  An initiative like this can augur huge productivity gain, setting the team free to handle exceptions (outcome). Subsequently, the accounting team can use human judgement to review a smaller data set of exceptions.

Automation in Travel
Travel accounts for the most complex and biggest spend item in an organization’s spend matrix.  A combination of travel requests, plans, locations, duration of stay and multitude travel advances compound this further. With increasing number of business travellers, this problem is expected to get more complex and unmanageable.  Fortunately, the introduction of corporate charge cards have made it less severe on the accounting fraternity. Their availability and accessibility on a variety of digital platforms help auto-fill travel expense statements based on data feeds from individual cardholders. This helps save productive employee time and hastens the settlement process, bringing in more predictability and ease of use. In the same way, AI can also structure a host of facts, dimensions and measures to provide accurate travel provisioning.

Voice Recognition and Natural Language Processing
If you have heard someone calling, “Alexa, what was our revenue for Europe during the last quarter?” then, you are surely using Information and Insight as a Service. Welcome to the world of Voice Recognition and Natural Language Processing! This brand new innovation can surely provide Just-in-Time and structured information, minus all the noise associated with such data.  Business leaders, halfway around the globe, can have a trained Amazon’s Alexa, Apple’s Siri, Google’s Home or Microsoft’s Cortana answer simple, business questions without sifting through multiple excel sheets or waiting for a finance executive to respond.  Extending this a bit further, think about building a killer application for all CXOs! For example, AI powered data analytics applications which read historic patterns to provide dynamic snapshots of an enterprise’s Profit and Loss Statement (P&L) at the most granular levels. And all of this, ahead of time, helping resurrect investor confidence.

The Road Ahead
Opportunities for automation are immense. We have barely scratched the tip of the iceberg. Let us face it -- any disruption is bound to create disparity.  Despite all the disruptions, we continue to witness areas where human intuition beats machines, hands-down.  The new reality, is AI augmenting but not replacing valuable human judgement.  It will force us to think creatively and engage in experimentation before taking decisions that technology supplements.

So, coming back to the question of whether technologies like Artificial Intelligence, Cognitive Automation, Machine Learning, and Deep Learning have come to stay, my answer is these will get even more integrated in our daily life as businesses employ them in applications. This in turn, would provide interactive digital interfaces and services, increase efficiencies and lower costs.

Automation has come here to stay and is bound to create a better future for all of us.  The need-of- the-hour is for regulators to design governance mechanisms that ensure AI and its allied technologies do not transgress boundaries. Technologists must build trustworthy automation technologies which infuse confidence within our social, political and business environments. This will ensure deeper adoption among all functions that depend on automation to take informed/appropriate decisions to interpret the world around them.

-By Jagannathan Chakravarthi, Chief Financial Officer, Mindtree

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