2021 and 2022 were all about the rise of fintech and its ancillary domain technologies. The rise of AI is increasingly defining 2023. The launch of ChatGPT, an AI chatbot in November 2022, has excited the world about this technology’s powers.
The hype around this also caused its servers to crash during the initial launch months. Microsoft Corp, the mega-cap US tech stock with a $ 2.20 trillion market cap, announced a multiyear investment of $ 10 billion in Open AI, the firm behind the AI Chatbot.
For the FAANG stock management boards, AI could provide much-needed support for their stock prices. Some hedge fund titans are even advising retail investors to use the recent fall in tech stock prices to enter this new age of AI.
AI space heating up
The recent earnings from Microsoft and Google saw the mega-cap leaders preparing their investors for the next big thing – AI Revolution. While Google has emphasised AI-led adoption as the next natural course of action, Microsoft has stepped ahead and signalled a dramatic shift towards a new and exciting future. Microsoft’s $ 10 billion investment only implies the other remaining leaders jumping onto the bandwagon soon. The below chart highlights what the other major players are up to in this space.
How can investment management firms leverage the power of AI?
Investment management firms can look at various domain aspects to harness the full potential of AI technologies. Managing one’s finances is often fraught with complexities, overestimated returns and misunderstandings surrounding the proper execution plan. AI can be used in the following broader areas to leverage the best possible resources:
- Generating the right alpha
Involves using multiple and alternate data sets to identify the outperformance measure and the actual factor model to be used. - Keeping the system efficiency to a maximum
In an environment of intense competition and cost-cutting, the operational efficiencies of any organisation need to be at their highest. - Selecting and disseminating the right product mix
The key for any business to survive and grow over the long term is identifying the most potent areas. AI can be used to analyse and predict future performance based on a holistic view of the current organisational profile and its business mix. - Managing the risk properly
AI can equip firms with tools and services to increase compliance and detect the maximum risk-related downfall that could potentially occur.
Use of AI in financial planning
The high-risk, high-reward financial planning industry has seen several disruptors in the past. The rise of AI has ushered in a new era for service providers and receivers. Some of the key segments where this technology can maximise and provide better outcomes include:
- Analysing
The field of AI takes a data-driven approach to the next level. Predictive Analysis involves analysing multiple data points in tandem and using the suitable training model to forecast the best possible outcome. Financial planning consists of analysing the consumer’s behavioural patterns through bank and credit card statements. The primary purpose of the analyses would be to recalibrate and balance spending habits with the proper savings habit. - Forecasting
Once the core data sets are analysed, the AI system can use a suitable training model to predict the right consumer choices. The model selected can be based on how the consumer categorises his savings needs – conservative, moderate, or aggressive. This can be helpful to the consumer in identifying when and where he needs to change his spending habit. - Automating and reporting
Once the AI solution has been deployed, the consumer can choose this to be on a recurring basis, overseeing the desired results over a long-term period. The consumer can then compare this with his desired outcome and give inputs to the AI model for tweaks. The end success is only met when the AI model outcome and the consumer preference are near equal range. - Spreading awareness and promoting good practises
The AI model can then be deployed as a bot to spread awareness regarding the best industry practices. As per popular field studies, a single bot can replicate and execute as much as 30 times the work of a full-time human. These bots can also use sentiment analysis to see how the mass market consumers react to their outreach. The success of the AI system will ultimately lie in its constant evolution in line with the consumer’s beliefs, goals and changing needs.