Wissem Souissi believes that AI will revolutionize many aspects of investing, for managers and allocators.
Wissem: I think AI is going to revolutionize many aspects of institutional investing for both allocators and asset managers. For starters and most relevant to us at Dasseti, it has huge potential to enhance research and analysis for allocators as well as engagement and distribution for managers.
Before or after investing in funds or companies, investors send detailed RFPs, collect a lot of data and conduct onerous due diligence. AI can help aggregate manager data, analyze information and files. AI can even help generate data requests to be sent to managers or portfolio companies. No more puzzling over what question or type of question will get the answers you need. This could be huge for allocators or ESG teams.
When the responses come back from managers, we see AI helping with comparing responses and flagging issues, maybe looking for trends or responses that aren’t clear or need more clarification from the manager. This could significantly reduce the time required for fund selection and ongoing monitoring.
From a manager perspective, we see AI helping investor relations teams to produce slick, consistent DDQ and RFP responses, pull together marketing materials and generally ease the communication channels with their allocators. The immediate benefits will be seen in the time savings, and possibly the volume of work that an IR professional can complete when some AI capabilities are applied.
Imagine a generative AI tool trained specifically and solely on your company data and previous RFP responses. It would learn your tone and continually improve the responses you were giving, without the worry of sounding like everyone else and becoming homogenous.
Wissem: Exactly. AI excels at consuming and correlating large datasets faster than humans can. But you still need experienced investment professionals who can direct the machines, then interpret those outputs and make nuanced judgements. Everyone is using the term “co-pilot” to describe AI, and I think it fits perfectly.
Wissem: I think it will raise the bar on using data to drive investment decision making. With AI, firms will need to have their data management act together - well-organized datasets, clean data architecture, strong data governance.
Firms that embrace AI will leapfrog their peers in leveraging data for better outcomes.
Wissem: There are certainly challenges. The investment sector is highly regulated for good reason – Investment management firms have a duty of care to their institutional investors, institutional investors like pension plans have a fiduciary duty to their members. They have to keep data safe, make sound decisions and keep generating returns.
AI needs to be implemented ethically and transparently, with diligent risk management and testing. But these challenges aren't insurmountable.
Wissem: That's a great question. AI is still so nascent that the regulators are trying hard to catch up with the technology. In the US the SEC proposed some new rules over the summer, targeting broker-dealers and investment advisers. They're focusing on how these companies use AI tech and have specifically mentioned predictive data analytics.
Essentially, they want to make sure broker-dealers and investment adviser firms don’t prioritize their own profits over their clients' needs. It’s in line with the usual fiduciary duties, but focuses on the potential for bigger conflicts of interests when firms rely more heavily on AI and data. While its still in the proposal stages, firms need to really watch out for any bias that favours them over their clients and make sure that if they are using AI they have solid checks and balances in place.
In Europe we have all eyes on the EU AI Act which is set to become the world’s first comprehensive legal framework for artificial intelligence. Its proposing a classification for AI systems with different requirements and obligations for systems based on whether they are high risk, medium risk, low risk etc.
It’s yet to be seen what risk level software platforms like ours will be classified as, but we are of course taking data protection and security incredibly seriously as we build out our own capabilities.
Around the world we’re seeing a lot of regulatory discussions happening at a governmental level. China for example issued a set of temporary measures in August this year that require generative AI service providers to submit security assessments before releasing mass-market AI products.
The G7 have discussed AI and are advised to also take a risk-based approach and the FCA in the UK are keeping a close eye on the 3rd party risks that AI projects might pose, as most AI deployments are hosted in the cloud.
Italy imposed a month-long ban on ChatGPT earlier this year while they investigated claims of a security breach.
Japan is working on some regulations around the use of sensitive data and expects to release something by the end of the year. So there's lots happening in a lot of places, but it's early days yet for regulators.
I think existing regulations focused on risk, compliance, and consumer protection will certainly shape how AI is applied. For example, regulations like GDPR focus heavily on data privacy and transparent use of personal data. Firms will need to ensure AI algorithms align with those principles.
The key will be working closely with regulators to demonstrate how AI benefits the investment industry as a whole.
Wissem: Thanks, this is an exciting time for our industry and we’re proud to be at the heart of it. We'd love to talk to asset managers, private equity managers, institutional investors and ESG teams about our AI roadmap if they are interested. Get in touch here.
Asset management industry starts to adopt new technologies, but attempts are superficial compared to what those technologies can offer. Will this...
Fundamental change is accelerating The period of the tailwind of rising asset prices, growing AUM, and stable fees is over. After more than 20 years,...
Fund managers operational quality is becoming a prominent selection factor for institutional investors. What does ODD reveal about a prospective...