According to PwC’s analysis unit, Strategy&, the GCC region is set to reap US$23.6 billion in economic impact from generative artificial intelligence (GenAI) by 2030. In what analysts called a “conservative top-down estimate”, Saudi Arabia will see US$12.2 billion in value and the UAE US$5.3 billion. The rest will be shared among Qatar (US$2.6 billion), Kuwait (US$1.6 billion), Oman (US$1.3 billion) and Bahrain (US$600 million). Sid Bhatia, Area VP and General Manager, Middle East, Turkey & Africa, Dataiku, tells us more about how teams can truly modernise, armoured with GenAI tools.
The second-highest ranked industry in Strategy&’s projection was banking and financial services, which is predicted to see a US$3.5-billion bump. The Gulf’s BFSI sector has long been a trendsetter in technology adoption. With a savvy eye on consumers’ shifting preferences, legacy banks have been quick to cater. There are many examples, from the rise of digital banks — Emirates NBD’s Liv, Mashreq Neo, Gulf International Bank’s meem and Bank ABC’s ila — to the roaring trade in FinTechs, such as Dubai’s PayTabs, Optasia and Sarwa, Abu Dhabi’s NymCard and Kuwait’s One Global.
As the BFSI-tech union continues to deepen, it is clear that GenAI has a part to play. But it also has a broader role in the finance function across industries. In many ways, Large Language Models (LLMs) were made for financial professionals. When it comes to arduous, cyclic tasks like preparing quarterly reports, reconciling ledgers and aligning with regulatory standards, GenAI models can do the work of dozens of people in a fraction of the time. A reduction in sweat and tears means happier employees. Greater accuracy means happier regulators. And enhanced efficiency means happier board members.
What GenAI brings is a means to plug gaps and overhaul juddering processes. Legacy systems and manual workflows are routinely accompanied by silos — a sinister word that in the business world denotes inefficiency. GenAI can essentially become a field marshal for change in five main areas.
1. Market intelligence
Market intelligence is a labour-intensive process at the best of times, but where data silos are present, it becomes maddening; and if information is not current, the task is impractical. With GenAI, finance departments can automate gathering and collation of data from sources as diverse as market reports, social media and news pages. AI is a natural pattern-matcher, so weeding out emerging trends, where challenging for a human, is a trivial exercise for GenAI, which can quickly provide a buffet of actionable insights that lead to shrewder decision-making.
2. Compliance
The Gulf region is exceptionally business-friendly, but governments are pragmatic in their attitudes to regulation. To protect consumers and economic security, mandates are periodically introduced that change enterprises’ risk profiles. In seconds, GenAI can consume and commit to memory gargantuan chunks of information — a task that would take weeks for a human professional to complete. GenAI can then automate the extraction of information from a range of sources and classify it in line with regulatory requirements. From employees’ payroll information to customers’ PII, automation increases accuracy and speed and takes a lot of the headache out of compliance management.
3. Contract interpretation
What GenAI can do for compliance extends to contract management. It can extract key clauses and present advice to decision-makers with considerably less risk of missing the fine-print than if a human had performed the task. GenAI can speedily discover and arrange salient information such as payment terms. It is also ideally placed to retrieve information that human agents would have difficulty in committing to memory, like supplier-specific clauses. GenAI allows employees to focus on negotiation and compliance, thereby (once again) improving risk management.
4. Social listening
Customers live digitally and share their experiences with everyone. For commercial entities like banks, this sharing may be with the brand in the form of direct feedback, or it may be with other consumers on social media. For a bank with millions of customers, it would be impractical to have employees trawl even the company’s own feedback data in search of insights. LLMs, however, are very much up to the challenge. They can sift through surveys, reviews and social pages rapidly. They can find connections and recurring themes, recognise sentiments and tie comments back to specific products or product lines. And they do so without bias, ensuring more accurate insights. This is the kind of information businesses can use to improve offerings and delight customers.
5. Financial summaries
Documentation, when done manually, is one of the most time-consuming tasks in an employee’s daily workload. Financial commentaries are orders of magnitude lengthier and more complex. But when GenAI takes over data synthesis and analysis of trends, performance and risk, it can rapidly produce initial drafts of deliverables such as quarterly performance summaries or market-outlook reports. This alleviates the burden on finance professionals who need only fine-tune the commentary. The labour saved by GenAI puts time back into the hands of innovative humans who can use it to strategise and create.
GenAI next
AI’s power lies partly in its ability to cover a wide range of use cases. GenAI amplifies this power because of its ability to take on such a wide range of previously human-centric activities. The benefits of GenAI for finance teams are plentiful and obvious. The main challenge for organisations eager to avail themselves of these advantages will lie in how to securely integrate GenAI into their workflows. Every finance manager wants more accurate forecasts and faster processing. The enterprise must take care during procurement to ensure the chosen AI partner can integrate GenAI with full security, governance and operational controls, so customers and regulators can both be satisfied with the result.
A finance team equipped with GenAI will be a strategic leader within any organisation, whether in the FSI sector or elsewhere. The capability to lubricate the machinery of finance and therefore of business, comes as standard. And when team members become comfortable with their AI colleague, the business will be setting standards of excellence for others to follow — in compliance, customer experience, employee experience and product innovation.