AI in financial services is a trend for many industries, however; the asset management sector is experiencing a bit of a lag. This may be due to traditional, established firms taking their time to assimilate or even accept the technological changes on the landscape. Whereas new companies and start-ups are likely to take AI developments in their stride (mainly because they won’t be as fazed by adapting to new systems or best practices).
To keep up the pace and stay in the race, it’s important to know the ways that AI can be disruptive in a good way. Depending on how well you use the tools of the trade.
Hesitations About Entering the AI Race
Asset managers may be reluctant to enter the race based of their current access to AI tools or due to their own fears. However, business leaders can help quash any anxieties they have by tailoring AI to support their own business strategy.
So, what are the fears specific to AI in financial services?
- Trusting in machine-made decisions, without any human intervention
- Relying on machines to consider the context of individual investor needs
- Depending on automated systems to be accountable for client portfolios
This perspective is also the reaction to a full-scale integration, which some firms are in favour of more than others. However, AI can be implemented to help asset managers in an advisory capacity, instead of completely removing the human element from the decision-making process.
According to FinTech experts, as outlined by Money Control, 75% of the distributor’s role is already being performed by AI in financial services. These automated systems are programmed to retrieve relevant information – such as personal details, risks, goals, and investment expectations – before assessing the information and algorithmically matching investment opportunities to the clients’ criteria.
Top AI Strategies to Follow
There are three main strategies that asset managers are recommended to follow to help them achieve a successful assimilation of AI in financial services and their individual business models. These include:
- Allowing Access to the Data – To experience the full potential of FinTech, firms should give AI systems access to the right data sources, like the stock market. This will allow the system to learn and adapt their behaviours.
- Creating a Scalable Approach – AI systems will also need to learn how to react autonomously to changes, such as adapting to new data streams. If there is a reliance on regular human intervention, this will make the automated integration costly and redundant.
- Ensuring a Focused Algorithm – Algorithms should be programmed to continuously monitor data, as well as adapt to perform other functions. This will add to the value and overall scalability of using AI.
As part of core business strategies, firms are strongly recommended to ignore the concept of a one-size-fits-all model. This is because different financial markets require different types of algorithms. Even if specific algorithms can be used to carry out different tasks, like monitoring stocks and setting up savings accounts, there are different complexities to consider. Differentiating algorithms is important, which ensures that both the AI performance and the data generated is accurate.
Path to a Disruptive Future
If this has inspired you to launch your AI strategy in the near future, there’s even more reason to do so with the Global X Management Company’s Disruptive Technologies: In Life & Portfolios survey. Here, they reveal findings on how disruptive AI in financial services affects their most affluent investors:
- Investors with a financial advisor are using technology more so in their personal lives, in comparison to their investment portfolios
- FinTech is predicted to grow in core areas of mobile banking and smart energy
- AI and Renewable Investing (RI) offer greater opportunities because they are viewed as top trends by investors
Remember: you can forge a path to a disruptive future and forego any fears by making AI decisions a part of your day-to-day business ethic. This means automated systems can be implemented as an essential supplementary tool – but with a human still at the helm.
Source: Born2Invest. This article was originally published on Born2Invest.com