Digital transformation

Paradigm shift to replace the legacy technology stack of banks [and wealth and asset managers]

The McKinsey & Company article “Banks’ core technology conundrum reaches an inflection point” presents an insightful perspective on the core technology challenge that banks are currently facing, which is now reaching a critical point. While this issue has been discussed for a long time, two factors are making the situation more pressing than ever. Firstly, banks will soon face a talent shortage in their legacy technologies. At the same time, they will have to fight for talent in new technologies. Both talent shortages will put significant pressure on their ability to maintain and evolve their systems. Secondly, legacy technologies are consuming a growing share of banks’ budgets, leaving them with limited resources to pursue strategic initiatives that can drive innovation and transformation.

Another interesting element discussed in this article is how Thought Machine is thinking about solving part of the problem by running products as code and making them independent of the platform, which can be composed of tens if not hundreds of different systems for incumbent banks: “We have a system of smart contracts that run on the platform, but they’re separate from it” says Paul Taylor, founder and CEO of Thought Machine. Brian Ledbetter, a senior partner at McKinsey & Company, also brings up the concept of putting risk controls in code and not in processes for risk management. After infrastructure as code, which we have been discussing for quite some time, we are adding controls as code and products as code, significant paradigm shifts that are complicated for incumbent banks still dealing with mainframes and systems that are 20+ years old.

The challenge of legacy IT stacks and technical debt for incumbent banks has been discussed for decades. Incumbent banks must not look at this as a systems replacement, but as an enabler and a necessity for their future. To be successful, incumbent banks must educate their business on technology, have a technology talent strategy, and bring people to the center of their digital transformation.

Interesting video from the CEO of Thought Machine.

Risk Management

Once in a while, I will discuss some topics that are not totally related to the digital transformation of wealth and asset managers. This is one, even if I could argue that a digital transformation cannot be run without taking and managing some risks.

If we want to talk about risk, not many activities are more dangerous and relevant than mountain climbing. Jimmy Chin, an American professional mountain athlete, photographer, film director, and author, discusses risk management in the context of climbing at a Goldman Sachs talk.

The first element he brings in is embracing failure, especially since there are a lot of failures in climbing. Their first attempt to climb Meru Peak (a mountain in the Garhwal Himalayas) failed. On their way down, they were already making decisions about things they had to change for their next expedition, like being lighter and taking warmer sleeping bags.

A second element is embracing the process, managing the variables you can control, and identifying those you cannot control. By embracing the process, you will focus on everything you need to get together to succeed, not only on the ultimate goal (in Jimmy’s case, reaching the summit.) That’s how you get there.

The third element is fear, which can be healthy, as it helps sharpen senses and motivates. Fear is not helpful when it becomes paralyzing or turns into panic.

Not surprisingly, a key component in risk management is anticipating all the potential problems that can emerge and having pre-defined solutions. When a risk materializes, taking stock of the situation and identifying the perceived and actual risks are essential. And really focusing on the actual risks.

Jimmy also brings the notion of trust and understanding how people function in different situations.

Reference:
Listen to the talk. There is much more there. Goldman Sach, Jimmy Chin talk: https://www.goldmansachs.com/insights/talks-at-gs/jimmy-chin.html

2023 Gartner Emerging Technologies and Trends Impact Radar

Gartner has released its 2023 Gartner Emerging Technologies and Trends Impact Radar. Let me try to give it a read with the eyes of a wealth
or asset manager.

Artificial Intelligence is all over the radar, with Foundation Models, Self-Supervised Learning, Generative AI, and more. Wealth and asset managers must seriously look into Artificial Intelligence and understand how it can be leveraged across their value chain, from investments to operations, risk management, and compliance. Part of the solution will come from their solution providers, like Bloomberg, BlackRock Aladdin, or State Street Alpha, to name a few providers. But wealth and asset managers cannot only rely on their providers. Instead, they must acquire the necessary skills and talent and play with artificial intelligence technologies. War for talent will make it complicated.

Blockchain is also quite present with Web3 and Tokenization, both being in the 3-6-year horizon. Most wealth and asset managers are already testing tokenization in one way or another, and they should continue. Tokenization will have many benefits for the industry, from speeding up transactions, eliminating some intermediaries and therefore reducing costs, making some asset classes available to smaller investors, improving the liquidity of some assets, and more. Tokenization will require some industry alignment and standards.

No surprise, Digital Twins are here too. Gartner is probably thinking more about Digital Twins in the context of manufacturing and industrial activities. But as discussed in this blog, the potential for digital twins in the financial industry is real and massive.

Then, there are hardware and infrastructure with Neuromorphic Computing, 6G, and Hyperscale Edge Computing. If wealth and asset managers continue to move to the cloud, they’ll be able to leverage these latest hardware technologies as they become available in the cloud.

Using digital twins in wealth and asset management

I have always been fascinated by digital twins and the potential they offer. There are many examples of companies using them. BMW has partnered with NVIDIA and uses real-time digital twin factories to optimize its production and conduct predictive maintenance. Emirates Team New Zealand uses digital twins to design and test its boats. SpaceX uses a digital twin of the Dragon capsule to monitor and adjust trajectories, loads, and propulsion systems. McKinsey says that companies can achieve ~50% faster time-to-market, ~25% improvement in product quality, and ~10% revenue uplift with digital twins.

Let’s start with some definitions. What is a digital twin, and how does it differ from simulations and standard CAD (Computer-Aided Design)? Simulations are usually limited to one process (i.e., narrow scope) and do not leverage real-time data. In contrast, digital twins are a virtual representation of a real, complete system fed with real-time data, lasting the system’s entire lifecycle. They allow rapid iterations and optimization of the system. The next big thing is linking digital twins to augmented and virtual reality, interconnecting digital twins, to finally creating the enterprise metaverse.

How about we use digital twins in wealth and asset management? I am hesitant to say that we have already been using them for a long time to model portfolios, test investment strategies, and assess the impact of certain events, to name a few examples. A “purist” might say these are more simulations than digital twins. And this is correct in many cases. The backtest of a portfolio is a simulation. But when an asset manager builds models to optimize portfolios daily, using near-real-time data, it’s getting very close to being a digital twin.

Traditional wealth and asset managers have yet to fully leverage the potential of digital twins because their use of data is limited (which is not/less the case for quantitative asset managers), they could leverage more near/real-time data and alternative data, and they could leverage more data across their entire value chain, from market research to portfolio construction, product development, marketing, and sales and distribution.

Many solutions are available to wealth and asset managers to use and leverage more data. But it requires more than tools. It requires technical skills and talent. Investment teams must have developers within their teams to use advanced market research solutions. Product Development teams must learn data science (e.g., Python) to get the best out of markets’, customers’, and competitors’ data. And the IT team must support these platforms.

Another challenge is where to start and how to build digital twins. A mistake might be to try to build a full fledge digital twin at once. It’s better to start small and evolve the first version. A good suggestion is to run hackathons to develop prototypes quickly and test the initial concepts. And the beauty of the hackathon is that you will have a multi-disciplinary team working together with portfolio managers, product development guys, and engineers.

To be successful, wealth and asset managers must make this a Firm objective, driven from the top. They must invest in talent and team upskilling, and ensure the right innovation culture is in place.

Let’s look at the digital transformation of other industries – The Washington Post

Looking at other industries to think about innovation and how to leverage technology in wealth management is always interesting. In that context,
the digital transformation journey of the Washington Post led by Shailesh Prakash is very insightful.

They quickly recognized that The Post needed to achieve excellence in both journalism and technology. It was a radical transformation, moving the IT department from an IT system babysitting mindset, IT systems in which the newsroom staff had very little confidence, to a product development mindset, building and inventing digital products. Part of the journey was adopting agile and colocating the engineers with their partners from the newsroom. They decided to build versus buy, set a fast experiment and innovation culture, and developed an obsession with products. Attracting and retaining the best engineers was key in that journey.

Through their excellence in technology, they built a set of tools they could sell to other publishers: Arc Publishing (Arc XP) was born, generating tens of millions of dollars of revenues for The Post.

Deep dive into the digital transformation of the Washington Post with the University of Virginia case study. There are also plenty of resources on the web. Just search for Shailesh Prakash (who is now at Google). If you like this digital journey, I also recommend reading the Goldman Sach’s Digital Journey case study from Harvard Business School. A great read.

Brace for tough year of cost-cutting

2022 has not been the best year for asset managers, and nobody knows what 2023 will bring. Most asset managers will cut technology spending, have to focus seriously on IT investments that will move the needle, and get their acts together. While some could argue that it’s now the right time to invest in tech to become more effective and efficient. Define a realistic set of key delierables for 2023 and then focus, focus, focus!
Read the FT article Asset managers brace for tough year of cost-cutting in 2023.

Think like a software company

Software is eating the world (“Why software is eating the world“, Marc Andreessen, Wall Street Journal, August 20, 2011) and many companies see the importance of becoming (like) a software company. It starts with committing to a software culture through leadership, communication, and investment. Leadership: Bring tech and software experts and visionaries on board, measure specific software KPIs, get software leaders to join your board (or advisory board, or technology board, just pick one), and join some of theirs. Communication: Communicate constantly about the strategy, value proposition, and progress of software, internally and externally. Investment: Sustained investments in software are required over many years. Management must also measure employees’ satisfaction.

JPMorgan started its journey with culture and mindset, talking about business outcomes, obsession over customer experience, and delivering value faster.

Invest in empowered product managers, while driving engineering excellence through autonomous teams and flexible architecture. The quality of the product managers and their ability to steer is critical to the success of this endeavor. Build on the ecosystem, leveraging others’ platforms and offering your own platform. Bring in “citizen developers”.

Last but not least, understand how to leverage software and data, where it can make a major difference.

Two key sources:
1) “Every company is a software company: Six “must dos” to succeed“, McKinsey Quarterly, December 2022.
2) “Inside JPMorgan’s appointment of 25 “mini-CEOs” and new strategy to operate more like a startup <…>“, Business Insider, April 2022.

As Ram Charan says, digital transformation is hard. Many firms have spent millions of dollars with very little result to show for it. Even defining what digital transformation is for a given industry or company is a challenging question.

The digital transformation of an asset manager must cover multiple dimensions and will evolve. It will impact the business model, client relationships, the supply chain, and the organization. Some elements of the digital transformation to consider:

Client experience, focusing on the client, digitalizing their experience, and giving them access to data and self-servicing;
Data, becoming a data-driven organization, leveraging new technologies like but not limited to data science, natural language processing, and artificial intelligence. For incumbents, data is often a significant challenge. There is data all over the place, with different definitions and formats, and minimal abilities to extract the value of all this data;
Process automation, trying to achieve the highest possible straight-trough-processing level, eliminating manual work and potential errors;
Digital disruption, identifying how Fintechs, pure digital players, and others will impact the industry, and defining required changes.

The digital transformation does not have to be a big bang. On the opposite, it should be a step-by-step approach. A company can quickly achieve results and deliver business impact by leveraging digital enablers with limited financial means. A key obstacle is often the company’s culture and mindset.

The digital transformation must come from the top (the CEO or the executive suite) and it must embark people even before it starts. Do not “outsource” your digital transformation to one individual or your IT organization. It’s a team effort that must engage people with sound business knowledge, deep operations expertise, and in-depth technology knowledge and expertise. Having the right talent is part of success. Finally, educating your senior management team about technology and digital transformation would be best.

Key to the journey is to identify the first, right step. Ensuring that it is feasible in a way it can quickly deliver business value. A good place where to start is usually the value chain. Map it, identify key pain points, and prioritize deliveries. Part of the journey is to find a pragmatic approach and not just dive into the digitalization hype.

Constantly revisit your target and the steps you are taking. If you are failing, recognize it quickly, and start again.

Recommended reading: “The digital leader“, Ram Charan and Raj B. Vattikuti, 2022.