AI AND machine learning (ML) are spreading across virtually every industry, with an increasing focus on fintech and financial services.
A McKinsey report found that 55 percent of UK businesses have adopted AI in their everyday practices — and Bank of England data show that 72 percent of financial services firms have implemented it in some form.
But British officials are warning organisations that integrating artificial intelligence-driven chatbots into their firms carries the risk that the bots can be tricked into performing “harmful” tasks.
Britain’s National Cyber Security Centre (NCSC) said that experts had not yet come to grips with the potential security problems of language models, or LLMs.
Some envision AI displacing not just internet searches, but also customer service work and sales calls.
The NCSC said that could carry risks, particularly if such models were plugged into other elements organisation’s business processes. Academics and researchers have repeatedly found ways to subvert chatbots by feeding them rogue commands or fool them into circumventing their own built-in guardrails.
RiverSafe CTO Oseloka Obiora says the race to embrace the technology will have “disastrous consequences” if businesses fail to implement basic due diligence checks.
“Senior executives should think again, asses the benefits and risks as well as implementing the necessary cyber protection,” he said.
Authorities across the world are grappling with the rise of LLMs, such as OpenAI’s ChatGPT. Security implications are still coming into focus, with authorities in the US and Canada saying hackers are also embracing the technology.
STX Next CEO Ronald Binkofski isn’t worried. He says the rapid uptake shows how well-suited AI and ML applications are to fintech. “AI-powered trading algorithms can analyse market data and execute trades in milliseconds, enabling real-time decision-making and taking advantage of market opportunities before human traders can react,” he said.
The vast amounts of data AI and ML can churn out reduces the chance of human error so common in manual data handling. “This accuracy is crucial in areas like fraud detection, risk assessment and compliance,” Binkofski says, “where even minor mistakes can have significant consequences.”
AI and ML also assist businesses to scale, he believes. “Automated systems can handle large volumes of data and transactions without compromising performance, which means that as fintech companies grow, automation ensures that their processes can scale.”
AI-powered recommendation engines analyse individual preferences and behaviours to offer tailored investment options, insurance plans or financial advice.
“ML algorithms can continuously learn from new data and adapt their models. Early adopters will benefit from automated systems that improve over time, becoming more accurate and efficient as they gather more information.
“In the fintech industry, the difference between success and failure can be extremely small.”
Stepping into roles that don’t even exist yet
ANALYTICS and evaluation platform Leadership Dynamics has released a report into AI’s role in the future of the C-Suite.
The industry report underscores the imperative of nurturing leaders who can step into roles that may not even exist today.
The emergence of chief supply-chain officer and chief artificial intelligence officer positions indicates momentum building to steer organisations into an AI-dominated future. Another new role, that of chief growth officer, emphasises the symbiotic relationship between technology and customer-centricity, while the chief empowerment officer heralds a paradigm shift in leadership dynamics.
“The C-Suite of tomorrow is a complex nexus of innovation, adaptability, and strategic prowess,” says Samuel Robberts, chief strategy officer at The LCap Group, which is powered by Leadership Dynamics.
The report serves as a roadmap for businesses aiming to harness the potential of AI while addressing the challenges that lie ahead, says Robberts.
