In March, ITWeb reported generative artificial intelligence (GenAI) is seen to be a game-changer in the banking industry due to its ability to analyse vast amounts of data, and generate images, texts, audio and other types of content.
This article revealed the Boston Consulting Group estimate that the global GenAI market will reach $60 billion by 2025, accounting for 30% of the total addressable market for AI in general.
In banking and investment services, application of generative adversarial networks and natural language generation can be found in most scenarios for fraud detection, trading prediction, synthetic data generation and risk factor modelling.
It has immense potential in this market because of the ability to take personalisation to new heights – a major contributor to customer loyalty and enhanced services.
AI can automate many basic banking activities, like payments, deposits, transfers and customer service requests. It can handle application processes for credit cards and loans, including acceptance and rejection, providing near-instant responses, according to a Hewlett Packard Enterprise overview.
It’s simply no longer a matter of ‘if’ CFOs will be successful with AI; it’s instead apparent that it is crucial.
Cost optimisation and improved efficiency are obvious benefits of the technology, in addition to AI helping finance teams to be increasingly agile. Above all, it enhances decision-making processes. With its ability to quickly analyse large data subsets, it’s reducing the time finance departments spend on routine tasks, such as categorising expenses and transactions.
The black box of technologies
CFOs likely will agree that finance teams are the backbone of any company’s success. But this in turn brings heavy responsibilities in the form of well-informed decision-making.
In the past, finance departments have been heavily people-driven and reliant on human experience and intuition. Today, AI has created a paradigm shift that’s enabling finance teams to better collect, process and analyse data, resulting in faster, meaningful insights.
They are increasingly turning to AI to make accurate predictions of outcomes and seeking different ways to incorporate those into internal processes. Gartner provides an example of this with its prediction that 20% of all test data for consumer-facing use cases will be synthetically generated by 2025.
Invoice payment reminders and financial evaluations − like tracking KPIs around sales, revenue growth, cash flow and expenses − are just some examples of key areas in which businesses are utilising AI.
Moreover, with the rise of GenAI, CFOs will likely want to focus on learning how this will impact every finance function all the way through to producing preliminary drafts of financial statements.
Revenue growth is a top priority for CFOs. Forbes notes GenAI tools provide them with the means to identify growth opportunities and market trends by optimising pricing strategies and models using AI algorithms. This also leads to enhanced customer experience and loyalty through personalised, AI-driven recommendations.
All these factors combined with AI's predictive capabilities translate into a competitive-edge, helping CFOs to stay ahead of market trends and differentiate their organisations through innovative AI-powered financial solutions.
CFOs need to get with the programme
CFOs are known for being averse to risk of any kind. But investment in AI and automation needs to be high on a CFO’s radar and not discounted due to lack of understanding or fear of the unknown.
It’s simply no longer a matter of ‘if’ CFOs will be successful with it; it’s instead apparent that it is crucial. Finance leaders can incorporate the pattern-recognition skills of AI in machine learning applications into their operations, to great benefit.
Automation is changing how finance teams work but to aid that change, upskilling is required to ensure staff understand the tools available to help them to succeed. Additionally, this growing interest in AI and automation has enabled many application vendors to tailor their roadmaps to AI, forcing finance functions to adapt to these changes.
According to Deloitte, smart CFOs must now give serious thought to AI implementation. It is noted the technology, which enables computers to be taught to analyse data, identify patterns and predict outcomes, has evolved from aspirational to mainstream, opening a potential knowledge gap among some finance leaders.
Remove mistrust by highlighting the wins
CFOs should consider communicating automation milestones with key stakeholders across their organisations. Sharing the wins will unquestionably inspire broader adoption and innovation.
For example, organisations might reimagine the products and services they’re providing and explore building robust in-house AI capabilities.
If finance leaders are to keep pace with change, automation will be an important investment, with implications for other business functions. Shifts in the market mean CFOs must move their priorities, and this evaluation process allows for better insight into which vendors and solutions are meeting bottom-line requirements and driving the best outcomes.
One can elaborate ad nauseum on the benefits of AI in so many areas, but staying ahead of increasingly sophisticated fraud schemes is one of its greatest capabilities.
GenAI can analyse vast amounts of transactional data, identifying patterns indicative of fraudulent behaviour and providing real-time alerts to finance teams, minimising financial and reputational damage.
The bottom line on AI, which is being referred to as the fifth industrial revolution or the cognitive era: It’s here to stay and businesses of all shapes can grasp it, use it to the full, or possibly get left behind.
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