AI SOLUTIONS

clear audit trails , to mitigate risks , especially within finance departments .”

“ To oversee the rollout of AI systems across the industry , enterprises could consider having a Chief AI Ethics Officer . With this , use cases can be measured from concept to implementation , with more robust testing , to evaluate risks . AI has an important role to play in streamlining outdated manual processes , so it ’ s up to industry to reach a state of confidence where they can adopt AI safely .”

AI has the potential to revolutionise the industry , but big banks have been slow to adopt these technologies compared to FinTech companies . Only 6 % of retail banks are prepared to implement AI at scale across their business , a Capgemini study found .

Central banks have been urged to enhance their AI capabilities by the Bank for International Settlements , which recognises both productivity gains and risks associated with AI , such as misinformation and hacking . Large language models , the core to most generative AI models often generate inaccuracies , raising concerns about the technology handling sensitive information .

“ There ’ s not necessarily a rejection of AI , but there is hesitancy ”, said Wincie Wong , head of digital at NatWest , who called for the technology ’ s risks , ethics and vulnerabilities to be assessed .

Oseloka Obiora , CTO of RiverSafe , commented : “ The vast volumes of sensitive data held by financial services institutions make it a prime target for cyber-breaches , both from malicious external actors and from insider threats . Without the proper security protocols and regulations in place , AI only serves to heighten the threat facing these institutions , so hesitancy around mass adoption is wise . In fact , 20 % of CISOs admitted that an employee at their organisation exposed company data using AI tools such as ChatGPT according to our recent research , highlighting the risks that the industry is facing from itself , let alone from outside attackers .”

Anssi Ruokonen , Director of AI Research and Enablement at Basware , said : “ For financial services to adopt AI safely , industry and regulators should be collaborating on best practices and standards for AI implementation . Ideally , solutions should be sandboxed before being rolled out , but it is important that industry recognise that vulnerabilities do exist and not all solutions can be tested beforehand . Therefore , AI systems should be built with continuous business monitoring and investment , alongside

AI ’ s ability to quickly analyse large volumes of text and numerical data can significantly reduce industry costs , yet job loss fears and regulatory concerns are among the factors preventing bankers from fully embracing the systems .

Kelly Fordham , Director of Financial Services at Investigo , commented : “ Financial services are facing a significant shortage of staff , still recovering from experience gaps formed during the pandemic , and institutions are struggling to fill core functions such as financial crime , risk and compliance as a result . AI has its place supporting staff , but , ultimately , the sector needs to overhaul its approach to recruitment and make the industry attractive again .”

“ Banks , for example , require specialised staff who can give them tighter balance sheet control . However , finding qualified staff who want to take on what can sometimes be seen as a less glamorous role has proven challenging for years . Therefore , financial services need to revisit staffing , considering routes such as interim staff for urgent projects , better career progression opportunities , and personal and skills development to make staff feel valued , all with the goal of boosting attraction and retention .” �

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