The benefits of AI extend across all business functions, but its potential for the finance function is especially striking, writes Paul Tully
Organisations are investing in artificial intelligence (AI) to improve efficiency, reduce operating costs, and open up new business opportunities.
From smart map apps and fuel consumption optimisation, to sophisticated financial tools for fraud detection, AI is becoming embedded in businesses in every sector.
The question for those looking to harness the power of AI in the best way possible, is whether to build, buy, outsource the technology, or utilise a combination of all three.
At a high level, AI is used to unlock the power of data to deliver better predictive and analytics capability.
The technology can explore “what if” scenarios and offer insights into competitive threats and market opportunities that might arise in the future.
The opportunities extend across all business functions, but the potential benefits for the finance function are especially striking.
AI benefits for CFOs
A growing number of CFOs are using AI to address changes to accounting regulations. We have seen large companies save manpower by using natural language processing (NLP) to review lease contracts, for example. Without AI, this would be a labour-intensive process.
CFOs also need to balance the delivery and growth of performance targets, while ensuring compliance with legal and accounting regulations.
AI offers enhanced insights that can support strategic decision-making in asset valuation, predicting future customer trends, and identifying market growth opportunities through predictive modelling.
The ability to create fraud detection processes leveraging AI, can also help CFOs to create a robust control environment and manage risk more effectively. Options here include mechanisms that recognise suspicious behaviour and classify alerts as high, medium or lower risk.
Finance operations and control
Perhaps no part of any enterprise has as many repetitive, routine tasks as the finance department. Inputting invoices, tracking receivables, and logging payment transactions are high-cost, low-return activities, and not of high interest to employees.
AI can increase efficiency by automating manual people-intensive finance processes, such as the order-to-cash cycle, helping to predict customer debts and improve working capital management.
Accurate, timely and consistent data, generated automatically, can help finance teams to add value to their organisation, leveraging customer behaviour modelling to identify opportunities to grow margins, while also forecasting with speed and accuracy.
Furthermore, using AI to analyse internal financial control points and improve fraud detection can create a more robust reporting environment.
Banks and other financial services organisations are leaders in establishing or acquiring their own AI capability. This is unsurprising given the cost and regulatory challenges facing the sector.
They are using the technology in customer support, automated loan approval processes, “self-repairing” mobile banking apps, and payment optimisation.
They also use AI for automated fraud detection, anti-money laundering checks, customer portfolio management, electronic trading, and property market intelligence.
Third-party solution business
Professional services firms are leading the field in developing third-party AI solutions for clients.
These range from bespoke solutions for individual clients to more general products in areas such as automated insurance claims processing, regulatory compliance checking, HR support, and the use of machine vision to monitor automated production lines.
Third-party solutions are not confined to the professional services sector, or the broader technology and software services industry. Organisations with well-established AI capabilities are making their solutions available on the open market as an additional business line.
Paul Tully is Head of Finance Analytics at EY Ireland AI Labs
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