Robert Cottrill, technology director at ANS, discusses how the financial services sector can utilise AI to improve operations and maintain a competitive edge.
Confidence in the efficiency, security and privacy of a financial services business’ technological processes is known as digital trust. Artificial intelligence (AI) can help to boost this within any financial business, whether it be a small company or a global enterprise.
The pace of AI development in recent years means this cutting-edge technology now has the capacity to play a crucial role in protecting business data and streamlining operations, but it must be deployed cautiously. This is particularly important for financial businesses due to the volume of sensitive data they typically process and store.
Growing digital trust: the benefits of AI
AI has boundless potential to transform financial businesses, but one use that can make a big difference is automation and data processing. By passing this often time-consuming and laborious work to machines, costs are reduced, and workers’ time is freed up to dedicate to other, more lucrative projects.
Administration is just one area where AI can add real value. For example, it can free up employee time by setting up new client accounts for them or by taking notes automatically during calls. Many of us encounter chatbots when we visit a website nowadays, but these are likely to become more advanced as AI develops. For financial businesses in particular, these AI chatbots are allowing customers to find answers to any questions they might have on tax, savings or credit quickly and easily.
With AI, financial businesses can process huge amounts of data for tasks such as monitoring, analytics, performance measurement or forecasting. Valuable insights from this data can be used to drive improvements such as more accurate calculations or a more comprehensive understanding of markets. Algorithmic trading, credit valuations and risk analysis are all great examples of tasks AI can assist with. The processing potential of AI technology also lends itself well to data checking, which can help financial businesses to improve the accuracy of their outputs too.
Many financial businesses have already embraced text generative systems like ChatGPT, which can produce content such as research reports, quickly and efficiently. For example, these tools can assist with the creation of collateral for clients, such as informative booklets, or by producing copy for websites and blogs.
AI to improve security
In addition to streamlining processes and improving efficiencies, AI can assist with many of the security issues that arise time and again within the finance sector. For example, criminal activity such as fraud and money laundering have long been major concerns for businesses operating in this area. ‘Invisible AI’, which works in the background, can be used to identify irregular patterns in financial data, unusual behaviour, and alert fraud managers to potential risks. AI can also be used for identity verification and facial recognition technology, which can help prevent cases of misidentification or identity theft.
As AI is ever-evolving, its deployment within financial businesses will require tech talent to create, run and monitor it. To transform financial businesses successfully, leaders need to remember that people are central to the adoption of AI.
Taking caution with AI – potential drawbacks
Due to the high stakes involved in protecting data and information, technology leaders within financial businesses must be thorough in their deployment, management and governance of new technology like AI. There is potential within AI systems for personal information to be misused, as there have been cases where sensitive data has been inputted on an AI system and ‘spit out’ elsewhere. The implications of this can be huge for victims, so it goes without saying that personal data must be protected at all costs.
AI systems can be targeted by cyber attacks, whether it be through vulnerabilities or malfunctions in the software. Some of the worst outcomes of these attacks are data breaches, which comes at a huge cost to victims and the business affected. According to the IBM Cost of a Data Breach Report 2023, finance firms lose approximately $5.9 million per data breach, which is 28% higher than the global average.
Financial services businesses striving to prevent data breaches and cyber attacks fuelled by bad actors using AI can find an ally in AI too. In a ‘battle of the bots’, AI can be used positively to fend off threats when deployed effectively, helping to analyse traffic and networks to detect and neutralise threats. Using software like Github CodeQL AI can scan code for potential safety risks, while deploying AWS’ Code Guru Reviewer uses AI to find security vulnerabilities in code. FS CISOs using these tools can build safer and more secure AI systems which ensure cyber threats are kept at bay.
Preparing for an artificially intelligent world
The integration and success of AI within a financial business is a continuous and iterative process. It’s not a matter of deploying AI and then waiting for the benefits to pour in. Like any new technology, AI’s use needs to be determined by the business goal it is going to help achieve, and have full governance, compliance and ongoing optimisation.
Those FS businesses who wish to optimise this technology to the fullest must prepare for upfront costs, as well as budgeting for ongoing optimisation and management of AI, carrying out research and development and employing the tech talent to manage it all. But if deployed effectively, AI has the potential to transform the way financial businesses work across the board, from enhanced administrative practices and streamlined data processing to better understanding of customers and markets.
Getting value quickly
From talking to many tech leaders in financial services organisations, it has become apparent that the fastest way to value for AI projects, is to work closely with tech partners who have the expertise and the engineering resources on tap. However, it is crucial when choosing a partner, that the partner provides some sort of co-managed service, so your tech teams are learning from the AI experts and gaining the knowledge to run the systems themselves.
What is clear is that AI isn’t going anywhere. In fact, it will continue to revolutionise the way we work for years to come. For any financial businesses yet to reap any rewards from AI-enablement, now is the time to start building digital trust and preparing for the technological wave, or risk being left behind.
