“Endless opportunities” was the upbeat theme of WE ARE GUERNSEY’S 2022 Funds Forum, with two panels exploring how sustainability and technology will help drive the post-pandemic economic recovery globally.
It is clear that technology Is transforming the funds space. Here, Cognitive Finance CEO Clara Durodie, who took part in the second panel session discussing the impact of technology on the funds sector, discusses how fund administrators and boards can prepare for the tidal shift it has created.
Recently, the chief economist of a global wealth management firm stated emphatically on record that he does not care about technology, and he is only interested in its economic impact. Many responded with resounding critical comments.
I had the opposite reaction. I am not critical because I understand the reason why he feels this way — technology was never before a required skill set. Such opinions can only come from professionals who remain committed to their trade, which they have been refining over decades, and this trade has not been technology-centered. Historically, lawyers, bankers, and accountants have been the decision makers in our industry. Naturally, technology has never been a necessary skill set for management.
From an operations perspective, the IT department has always been merely a back-office issue. The rapid technological expansion and associated impact is changing this. The IT department is fast becoming front and centre for boards and management teams, and yet IT as a whole still fails to feature as an ongoing board agenda item. You rarely see the head of IT being invited to sit on the C-suite or on the board — the technophobes seek to avoid IT discussions at all costs.
In my previous corporate life, I often found myself at the confluence of discussions between the IT department and management. Both sides were frustrated with each other as neither could understand — or even try to understand — the other. They spoke different languages. This continues to be a general characteristic of our industry.
This lack of communication created a rift, where each party would try to overcome their own fears and establish a working relationship. The fear of looking uninformed and unable to carry a meaningful conversation remains in many organisations. It is rooted in a lack of education about the other side’s type of work and the associated challenges.
From a business strategy standpoint, the incorrect and incomplete use of technology will likely leave you trailing your competition. Technology, specifically artificial intelligence (AI), is a powerful business tool that requires considered and managed deployment if your organisation seeks to stay ahead. You cannot ignore it. You don’t have that option. You must use it, but use it within a well-understood set of governance parameters.
This is hard.
So, I understand why this chief economist would hold that view. Technology is complex and not easy to understand. However, to evaluate its economic impact you need to care about technology. This means that you need to learn about how technology works and what makes and breaks a company using or building technology. This new learning creates value in operations, strategy, and investment research. It helps identify profitable investments ahead of others. This new learning can only be achieved by unlearning old ways of doing a job and creating new habits and heuristics, or relearning how you do your job.
When this chief economist says that he does not care about technology, he is merely using an avoidance strategy. I have seen many leaders in our industry using avoidance strategies when confronted with conversations about technology. We all use avoidance strategies when faced with paradigms that upend our habits, mental models, and heuristics gained over decades. It is only human – it is our flight strategy. Some call it burying one’s head in the sand, others define it as another’s problem. Whatever you call it, it is an avoidance strategy that will ultimately only cause harm to your business in the long run.
Leadership teams are operating in a complex and fast-moving environment. It has become very complicated and risky to pivot your business model to a tech-driven one, especially when you do not know much about what technology can do for your company.
I am not going to consume your time by recycling typical consultants’ vacuous platitudes and diagrams as your golden ticket to a successful digital transformation. Instead, I will share in plain English the six pillars to start your journey, which I call “technology fundamentals strategy.”
Learn to unlearn and relearn
This is the core of continuous professional development, especially when change occurs almost daily. New technology challenges our ways of doing business. Unlearning means letting go of old habits, heuristics, and ways of thinking. It is a conscious process, and most of the time it is an uncomfortable one. Relearning means replacing our old ways with new ways, new thinking, and new habits and heuristics. Relearning is shaped by what we learn. Possibly the most valuable byproduct of unlearning and relearning is that we strengthen our cognitive abilities and maintain a strong brain plasticity, which are directly correlated with reduced cognitive decline. In other words, we keep our brain young and may also keep Alzheimer’s at bay.
IncorporateAI Literacy for everyone
Promote a culture of ongoing learning and intellectual curiosity. For this, engage human resources (HR) early before rolling out large transformation projects. Allow for a minimum of six months for HR to roll out a plan. Make provisions for strategic workforce planning and re-skilling as part of employee value retention and growth.
Consider dissociating AI capability and your data strategy from your existing IT mainframes and systems. Allow data teams and leadership to build patience and the high tolerance levels needed to handle the numerous failed attempts and repeat testing required before success is achieved. Create a culture where people are not penalised for failing and where the need for patience is accepted.
Technology education should be rolled into continuous professional development (CPD) training. I mean tailored education, not mass training of pre-recorded courses issued by leading academic institutions. This training is about tailoring it to the unique needs of your organisation. It is not about its academic value, it is about its practical applications specific to your organisation’s needs. More often than not, academic teachings struggle to find value in the real world. The Chartered Institute for Securitites and Investment (CISI) is on the right track, and they are doing a superb job to support the investment management community.
In addition to this type of‘blanket’ training, each organisation should carefully select specialist training strictly tailored for their staff. This training should be delivered in-house. For instance, a fraud detection team should receive specialist training in reinforcement learning to ensure they have a competent understanding and awareness of essential and basic fraud detection and protection solutions. The Board and the C-suite, on the other hand, should have access to tailored training on the business and governance of technology relevant to their work, with a focus on data-driven business models applicable to their sector. Being technology literate is becoming as important as understanding a company’s financial statements. You do not need to be an accountant to read the accounts and make strategic business decisions. In the same vernacular, you do not need to be able to code to be AI literate and make sound business technology decisions.
Stay intellectually curious
Build a culture where you encourage and reward intellectual curiosity. You will find that people are naturally curious and willing to learn when you make space for their learning and recognise their efforts. Make sure that this curiosity is embedded in the annual employee assessment. And that you reward it. You’ll be surprised at the dormant value that exists in your employees.
Use technology as a business too
Technology, and more precisely AI, is a business tool. Like any other tool, it is up to you what you make of it. So make sure you use it to its full capacity. You can pretty much use it on all business activities from stock picking and investment report writing to reconciliation and funds distribution. By learning how it works, you can extract its full value.
Embed ethics and governance around technology
Proper technology governance enables you to unlock the full potential that AI can deliver for your business, without landing you in trouble years later. Technology is beneficial as long as you assign its capabilities to your business interests, and as long as you continually monitor it. Ethics and governance of this technology must be your ongoing concern. Embed strong AI governance principles early on, and make it a part of your ethics teams, not a part of compliance. Ethics is not a compliance issue – it is a corporate culture issue.
Ensure that technology follows business strategy
In other words, make sure that you have clearly articulated your business objectives (AUM, clients, geographies, etc.) and only then should you align your technology procurement to those objectives. This means to design your AI strategy with this focus in mind, which includes your data strategy, cloud strategy, people strategy and every things else to support deliver your business objectives.
It also means that you do not chase shiny new things (technology solutions that are in fashion) or short-term strategies that your consultants might typically advise as the ‘lowest hanging fruit’ (i.e. cheap to start and easier to convince the board), but can ultimately lead to compounded and potentially abortive expenditure to realise long-term objectives.
Instead, educate your board that AI requires patience and reiteration. It is complex and needs informed leadership, and it relies on their patience, funding, and continued support. To take full advantage of AI requires embedding it within the business strategy, the company’s purpose, and its culture strategy and operating models.
In conclusion, dissociate AI capability and your data strategy from your existing IT mainframes and systems. Data teams and leadership teams need space and support to build patience and the high tolerance level needed for repeated testing and associated failure until success is achieved. Establish a culture where staff are not penalised for failing and where they have time to deliver — be patient. This strategy requires a business-wide approach to be successful.
It is not “just an IT problem”.
