Data and AI transform banking and financial services: processes get optimised, new revenue opportunities emerge, agile new entrants and digital giants challenge incumbents position. Whether seen as a commodity, a leverage or a strategic asset, data poses new strategic questions to historical players, welcome to Datanomics!
Optimisation and development
At first, technologies are seen as productivity improvement levers either because they automate tasks, eliminate some of them or transfer others to outside the organisation, usually to the clients. Data and AI technologies make no exception: robo-advisors making investment decisions in financial markets, machine-learning solutions used to decide on investments in small caps, chatbots for customer support in retail banking.
On a slightly different note, the widespread availability of massive data sources (social networks, blogs, comments, reviews, ..) opened up an opportunity for automating research on alternative (non-financial) data sources to make investment decisions. Hedge funds, in particular, have been at the spearhead of this trend for a few years now and companies have specialised into providing real-time insights to fund managers based on alternative data. Thasos uses mobile phone geolocation data to inform investors on business activities (are there more clients in this supermarket chain? Are the workers on time for their shift in this factory?).
Banks and financial services operators sit on a large amount of data: bank account activity of their clients and usage activity of their website and mobile applications. Of course, they use that information for optimising their activity: targeted marketing and process optimisation. They also investigated new revenue sources based on that asset: selling data services. Mastercard is reported to have collected 4B$ in 2019 in data services (25% of their total revenue).
New players on the field
As in many other markets, competition intensifies and incumbent face attacks by many different players on various fronts:
- startups using data and AI technologies attack them directly and capture part of their client base. In some cases, they also open new market opportunities thanks to these technologies (for example: robo-advisors for lower-income individuals).
- fintech developing technologies to position in the financial services infrastructure, Stripe is a good example with the recent launch of Stripe Treasury which enables platforms like Shopify to easily offer its merchants access to critical financial products to manage their businesses’ finances. With Stripe Treasury, platforms can offer their users interest-earning accounts.
- digital giants positioning in the value chain to capture or organise part of it. Their data assets and AI capabilities are the main weapons they use to break into this market.
- retailers are not new in that market, since the 80’s they developed financial services to make buying easier. They continue this strategy with renovated offers. Digital natives retailers such as Amazon have been present also since a long time in this field.
Competition is not new in the industry, the difference lies in the type of players fighting and the arguments and critical resources they leverage. As the key success factors change, incumbents face tough decisions to remain relevant in their historical business.
Financial services went trough major market evolutions over the last decade and the Data-and-AI phenomenon is only one of them. 2008 financial crisis and the evolution of regulation strongly influenced the strategic agenda for incumbents. However, though not the only force, we can argue that Data-and-AI phenomenon contributes strongly to shaping the strategic challenges because it questions « where to play » and « how to win » choices:
- Scope and balance: given that attacks are numerous and new entrants use a different playbook, which are the markets where 1) clients are ready to pay for the value proposition 2) the company has an edge? Consequently, which markets should the company exit? Would these exits help to finance the acquisition of new critical resources related to data and AI?
- BtoB and/or BtoC: with the business and technology ecosystem becoming more and more fragmented and diverse, what is the adequate balance between BtoB and BtoC operations to continue capturing enough value?
- Positioning: as finance becoming more and more technology-driven, is it more interesting to position as part of the infrastructure (moving to software-and-platform model) or to use the infrastructure built by others (at the risk of losing the control on value capture)?
- Make/buy/partner: as the technology stack becomes bigger, for which part of the stack should the company trade control against efficiency?
One company has made clear choices regarding these options over the last 5 years: Goldman Sachs. Behind their motto of becoming « the Google of Wall Street », the bank has launched several initiatives that express clear choices regarding the above tradeoffs:
- Marquee is Goldman Sachs own automated trading platform designed to replace the work of some of Goldman’s technology and operations staff by automating more conventional trading functions.
- Automating the job of traditional investment bankers Gemini is Goldman Sachs M&A Dealmaking App. It is designed to help the banks clients to identify under-performing parts of their businesses that make them vulnerable to attacks by activist investors or those that score poorly on environmental, social and government issues. The bank also expects clients to use the product to identify sale or spin-off opportunities and possible takeover targets in the form of unloved or poorly performing company divisions.
- Goldman Sachs partnered with Stripe to be one of the reference partners in the Stripe Treasury offer, which exposes Goldman Sachs products to all users of Stripe Treasury.
- The firm has just released software that allows clients to embed banking services into their own products. As said by the Head of Transaction banking: “This is the financial cloud for corporates”.
- In a move to address BtoC clients, Goldman Sachs partnered with Apple for the launch of the Apple card.
It’s certainly too early to tell if this strategy will pay off in the future, what’s for sure it that it stresses the importance for the other players find their own positioning. This example also shows that as financial services are commoditized, the key part of the value chain to control is the distribution of these services, which is more and more done through companies selling goods and services or the technology platforms which embed in their software access to financial services.