According to Francesco Filia and Daniele Guerini, authors of The Future Of Finance: The Rising Tide of Fintech Lending And The Platform Economy, AI capabilities include credit scoring and risk assessment; fraud detection and prevention; chatbots and virtual assistants; personalized banking and financial planning; algorithmic trading; customer relationship management; regulatory compliance; robo-advisors; and natural language processing .

When such points arise, it is perhaps inevitable in this time of rising labor costs – increased by forces such as the UK government’s increase in employers’ payroll taxes – that people assume AI will replace them. To an extent, that’s true but it is more complex than that – AI will replace some roles, but augment humans’ capabilities and hopefully productivity, in others.

Rob Pettman , president and chief revenue officer, at TIFIN, an AI and innovation platform for the wealth sector, told this news service that there are three main elements to the AI use cases for wealth management: growth, cost reduction and risk management/reduction.

“In 2025, we will see widespread adoption,” Pettman, who joined the firm in April, said. He is based in Charlotte, North Carolina. 

One use case is helping the distribution of wealth management advice at scale,” Pettman said. “We have talked about personalization for a long time in this business…but it is still a mess. AI changes that market to be more scalable.”

To some extent, that comment dovetails with observations on how delivering mass-affluent wealth management requires the ability to handle mass-customization. AI, while not a silver bullet, holds the key in some ways to making this a reality. 

At Broadridge, the US-headquartered group providing tech solutions to financial firms, examples of AI enhancements include BondGPT, which is powered by OpenAI GPT-4 that answers bond-related questions and assists users in their identification of corporate bonds on the LTX platform. This app distills bond issuer and market data so that users can pose questions – such as how to find a replacement for a bond of a certain type – quickly, and in seconds, rather than minutes or hours after talking to an analyst, as has previously been the case.

The rise of generative AI has sent shockwaves through financial services.   Allvue Systems, which provides investment tech, to give another example, has issued a report showing that 82 per cent of general partners in private equity firms use some form of AI in the fourth quarter of 2024. 

"Since ChatGPT's launch in 2022, AI interest has skyrocketed and financial institutions are increasingly exploring and implementing this technology," Phillip Mortimer, CTO of Accelex, a UK-based group focused on AI in areas such as the private markets ecosystem, said. "These firms are recognizing AI's transformative potential to enhance efficiency, generate valuable insights, and maintain a competitive edge. In private markets, for instance, AI adoption is accelerating manual processes like?intelligent document capture and?data extraction, significantly?enhancing operational efficiency while?boosting?portfolio?transparency," Mortimer said. 

Time for specifics
Pettman wants to see more focus on specific applications for AI and less general commentary and noise, however understandable that might be. 

“At the moment there is a certain amount of exhaustion,” he said. 

Giving an example of a specific use of AI, Pettman discussed TIFIN’s offering, SAGE, which focuses on portfolio construction through AI-powered proposal engines and analytics. He highlighted how generative AI can analyze documents, identify patterns, and extract insights. By combining AI with data and analytics, SAGE, he said, delivers scalable personalization. It generates tailored commentary by integrating research insights with client account analysis or customizing portfolios based on manager research. This level of personalization at scale was previously impossible, he said. 

AI can help with producing documents and information that investment committees can examine, such as private markets and other areas that eat up hours of time, he continued. 

“You can reduce due diligence times by 80 per cent,” Pettman said. 

In-person and online
In-person analysis and meetings, in the initial stage of an investment, are still unavoidable, but AI can then slice through the time involved in subsequent stages, he said. 

Another important use case area is risk management. This news service asked Pettman about the hot topic of outsourcing to third-party providers and regulators’ concerns about maintaining standards in this case, as well as the function of “model matching” so that clients can get the investment that they want and are suited for. 

AI can help what is happening to an investment model continuously, so that clients can understand why a particular decision took place. This also helps a wealth manager demonstrate their value proposition, Pettman said. 

TIFIN has been busy. In July, it rolled out an India business to expand ts direct-to-customer and business-to-business AI for wealth applications. The new entity is called TIFIN India. It was launched with the DSP family group, a financial services firm in the country.

TIFIN’s companies have included 55ip , Paralel, and Magnifi, TIFIN Wealth, TIFIN Give, TIFIN AG, TIFIN AMP, Sage, Helix, and TIFIN @Work. TIFIN has been backed by JP Morgan, Morningstar, Hamilton Lane, Franklin Templeton, SEI, Motive Partners, and Broadridge among others.