Artificial Intelligence—Who Parents After Adoption?

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Artificial Intelligence (AI) is in its spring and with it the first signs of integration are beginning to appear within the asset management industry. Alpha generation, productization of operations, and enhancing customer experience are all possible with the right AI model. Firms that are earliest to adopt and better understand this emerging technology will have disproportionately greater odds of capturing the opportunities that lie ahead. However, before firms journey down the AI path, it’s important to understand what it is, why hiring a Director of AI will be critical to future success, and where value can be found.   

What is AI?

To paraphrase Wikipedia, AI is the ability of a computer program or a machine to think and learn by mimicking human cognition such as problem solving. It essentially aims to make computers “smart” through the interpretation of external data, subsequent analysis of that data, and finally the output of findings to achieve specific goals and tasks through flexible adaptation.

How should asset managers prepare for AI? 

With adoption of AI imminent across the industry, asset managers should seriously consider hiring a Director of AI. The Director of AI will set the vision for internal AI use and facilitate the roadmap as it becomes increasingly critical to the long-term success of their firm. Asset managers such as Fidelity have recently pursued and hired for the role, and I expect many others to follow their lead shortly. Ensuring effective use of AI will require dedicated resourcing to understand the possibilities and prioritize areas for implementation within a firm.

What should firms be looking for in a Director of AI?

At a high level, the candidate will have a deep understanding of computer science, data mining and correlation analysis coupled with broad asset management industry expertise. The role is responsible for establishing a scientific discovery process whereby assumptions on AI can be clearly tested and validated for value. Success will be measured on the ability to combine data sets derived from a firm’s application stack (data warehouses, OMS, analytics, performance, pricing, etc.) to produce meaningful investment decision criteria, optimize operations, and enhance the customer’s user experience. A firm’s AI capabilities will vary greatly based on the Director of AI’s talent and ability to execute. The differences are where true value will be created.

Where is the value?

1. Alpha generation

Most active funds are desperate to show differentiated returns and justify management fees. AI deployment will provide the best opportunity for asset managers to generate alpha in the years ahead via the creation of new investment decision making data. Today, most investment research is limited by human capacity and bandwidth to synthesize data. AI technology offers a way to reduce these limitations by leveraging algorithms to dissect and correlate market outcomes using a firm’s data stores, including both structured and unstructured mediums, on a 24/7 basis. Early adopters will create data arbitrage with respect to their competition by accessing a more thoroughly vetted and in depth set of analytics to drive their investment decision making process.

2. Productization of your middle and back office capabilities

No longer just a cost center, middle and back office operations should leverage AI as an enabling technology to productize their processing environment. Through design and experimentation, the Director of AI can seek out ways to optimize data intensive functions. For example, AI could be leveraged to handle dispute resolutions on cash and position reconciliations by enabling pattern recognition on breaks. Remediation steps with brokers and counterparties could be automatically triggered based on learned outcomes from prior resolutions, vastly reducing time spent to manually clear those breaks. As AI solutions become fully optimized, firms will have an opportunity to bring their product or service to market, generating significant returns. Although not directly AI related, think of BlackRock as a tangential example. They built their proprietary trading, risk and compliance platform Aladdin to address their internal operating needs. Realizing the worth, BlackRock commercialized the solution and as a result captured tremendous value for their efforts. AI initiatives should adopt a similar set of first principals and seek to productize their intellectual capital in the market. 

3. Enhanced customer engagement

Customized user experience and content will become the norm under an AI enabled model. Consumers are succumbing to information fatigue and are numb to marketing material that is generalized in nature. Asset managers need to personalize the client engagement model. First generation AI bots are already capturing and learning from a users’ website engagement to cater investment products that are better suited to meet the needs and preferences of the consumer. Expect new product segments to emerge as AI technology continues to evolve and learn from a consumer’s interactions across their platforms.      

Parenting After Adoption

AI technology will continue to permeate the asset management landscape with new use cases in the months and years ahead. As is true with any new and maturing technology, there will be many ups and downs during the early years of experimentation. A capable Director of AI will bring an innovative mindset that facilitates the AI discovery process within their firm. Technology is moving faster than ever and there will be outsized opportunities for firms that deploy solutions quickly and effectively. The wait and see approach, a luxury of previous generations, will end up costing asset management firms dearly.

It’s important for firms to consider who will oversee and nurture this new progeny. Now is the time to get that Director of AI on board!