ChatGPT, have you heard of it? What about artificial intelligence (AI) and machine learning (ML)? Of course it does. AI buzz is flooding our airwaves, inboxes and feeds, unless you’ve been under the proverbial rock for a few months. If you’re a wealth manager, especially one focused on sales and marketing, you’ve probably wondered how this new technology can help him grow his AUM.
A quick Google search for “artificial intelligence” brings up the familiar headline “The AI revolution puts jobs at risk.” AI will cause mass extinction. AI will create more wealth than ever before in the next five years.
Theoretically and practically, performanceism aside, AI has been around for years and permeates our lives. Recent events have further increased awareness of its existence and the impact of its spread. We interact with AI every day through the recommendation engines used by apps like Spotify and Netflix, search engines like Google, and ad targeting that makes us wonder if our phones are listening to us. AI is making great strides to change the decades-old way sectors like healthcare, transportation operate.
However, understanding AI architecture, associated terminology, and its expanding application to the wealth management distribution ecosystem can become clearer. The lack of information to address the complexities of AI or to educate wealth managers about the real-world applications of AI with respect to increasing wealth management is useless. As AI looks to asset management, it becomes increasingly important to sift through the noise to understand the more practical realities of this evolving technology and how to interact with it, for a variety of reasons.
AI is already addressing the challenges facing wealth managers by helping organizations stay competitive in terms of performance through alpha generation. Create content. Identify areas for operational efficiency and resource optimization. and improved scalability. More recently, AI has been applied to distribution by leveraging investor data and ML to match products and prospects for higher conversions in a personalized and accurate manner.
We are not saying that AI is the panacea for all the ailments of asset managers, as the solutions available to deal with headwinds are not yet readily understood by many in the industry. The leader of these organizations will benefit from understanding the practical nature of AI, even at a basic level, and in particular he will benefit from understanding how AI can be leveraged to enhance AUM growth and platform availability and effectiveness in the marketplace.
An obvious question to ask before delving into AI to aid sales and marketing is whether you should adopt this new technology. That’s a fair question. Organizations often have technical debt, have already purchased several datasets, are overloaded with underutilized applications, and have some less advanced technology that already addresses one or more of these challenges. Moreover, the ubiquity of data means that asset managers are buying more data than they can reasonably ingest, from which actionable insights can be derived to enhance their business.
These concerns cannot and should not prevent the adoption of new technologies, especially those that can be addressed holistically and effectively. Even better if you can integrate it into your existing CRM or other apps in your tech stack.
If you asked yourself if your business should have a website just because this is 1999 and you’ve already published your phone number in the yellow pages, what would the answer be? An asset manager needs AI today just as he needed a digital presence since the early 2000s since the 1990s. We can’t expect to strengthen our brand, grow our AUM, and stay competitive without rapidly implementing perhaps the most important technology our generation has ever seen or will see.
We are all familiar with the phrase “investments are no longer bought, they are sold”. Asset managers often lament that the commoditization of the industry is reducing management fees, wallet share and brand awareness. The average expense ratio for asset-weighted equity index ETFs has fallen from 30bps to his half since 2005. Mutual fund expense ratios experienced a similar phenomenon, dropping from 1% to 40bps. More products and more new issuers enter the market each quarter.
In terms of AUM, from Q4 2021 to Q3 2022, the world’s 40 largest asset managers collectively experienced a 14.9% decline in AUM and a 22.9% decline in revenue. In addition, increased market volatility leads to less predictability, requiring new strategies for asset managers to ease their burdens.
The next related question is whether new technology will save us. There is certainly enough argument that AI will help asset managers enter a new era of growth, especially as it evolves.
A recent study by McKinsey highlights the importance of AI adoption in the wealth management industry. Asset managers who have invested in AI-powered distribution analytics are seeing amazing results. With the introduction of AI, subscriptions increased by 20% and reimbursement decreased by 5%-8%.
These numbers are insignificant and make it abundantly clear that asset managers looking to protect themselves against earnings-squeezing trends need to evaluate new avenues for growth. What’s more, if you don’t act now, you risk falling behind your peers who are investing in technology.
Organizations that have not deployed AI due to uncertainty about its value or budgetary constraints, or are wondering whether to build AI in-house, should first consider turnkey solutions with existing infrastructure and expertise to reduce time to market and deployment costs.
It’s becoming increasingly clear that AI is more than just a buzzword. It is a transformative force reshaping the distribution of the wealth management industry by creating more accurate matches of products and impacting conversion rates. And it’s happening now. Adopting AI is not optional, but it is a strategic imperative for asset managers looking to succeed in an increasingly competitive market and industry environment. Additionally, deploying an outsourcing platform like TIFIN AMP enables wealth managers of all sizes to leverage vast amounts of industry data and leverage teams with significant AI and ML expertise to produce better delivery results.
