Why empowering everyone with the best investment solutions matters
For too long, banks have restricted their clients to limited models, constrained geographies, and forbidding fee structures. The result? Under-invested clients and paltry returns.
Head of Fintech, Saxo Bank Group
Once upon a time not so long ago, companies tried to generate new business by sending marketing messages to prospective clients by post. Direct or ‘junk’ mail – sending a leaflet or letter to anyone for whom the firm had a job title, street address or postcode – was pretty unsophisticated, and was often derided as a ‘machine gun’ approach.
Although some still use this method, others sought to exploit the greater reach, creativity and traceability of digital marketing when trying to get a message across or identify demand. Some methods still rely on relatively little data, such as an email address, while others combine many, from past purchases to browsing history. Nevertheless, too many of the finance sector’s current client marketing and communication efforts continue to employ the machine gun approach.
Greater precision in finding the target comes only with better knowledge, or, more specifically, data. In our increasingly digitised knowledge economy, we are generating, capturing and analysing data at volumes and speeds that are accelerating exponentially. Through access to high-quality data, artificial intelligence (AI) programmes can ensure messages to and communications with customers hit the correct target time after time.
The more an AI programme knows about a client’s preferences and priorities, the better it can meet and even anticipate future needs. Already, AI-driven apps are proposing courses of action and making recommendations for users’ consent via a click of a mouse or swipe of a screen. Before long, these interfaces will fall away, leaving just an AI-enabled conversation between the customer and the financial service provider.
Sounds far-fetched? In the home electronics market, there is increasingly fierce competition between tech giants – Amazon, Google, Apple, and Microsoft all have horses in the race – to provide the dominant virtual assistant. According to Forrester, Amazon sold six million of its Echo smart speaker devices in 2016, each of which is driven by its Alexa intelligent personal assistant. From car manufacturers to makers of domestic appliances, compatibility with Alexa or its Google equivalents (Assistant and Home) is increasingly a ‘must-have’.
By selecting a virtual assistant, then commanding it to execute various tasks, chores and purchases by verbal instruction, you are embarking on an increasingly collaborative journey. The assistant will begin to anticipate your requirements more efficiently (taking actions or placing orders automatically, without having to be told), making adjustments following every data exchange or, as you might call it, learning from every conversation. To optimise your investment, you might select products because of their compatibility with – or recommendation by – your chosen virtual assistant. Alexa may influence you as much as you influence it.
How does this augur for banks? Banks currently interact with customers across a variety of channels, from branch to phone to web to app. Inevitably, a lot of potentially useful data slips through the gaps that could otherwise help draw an increasingly detailed and accurate client profile.
Already chatbots are making great strides in making the process of interaction more natural for the customer and more useful for the provider in terms of understanding and gauging future needs. As with the virtual assistants that are almost invisibly managing our homes, banks’ AI interfaces could also changing the user experience landscape as they reach maximum utility.
AI has existed in banks’ back offices for some time, but it is fast emerging into new roles, and could well become a core competence in the near future, becoming critical in efforts to optimise customer interactions, ensuring they deepen and broaden over time to sustain valued, trusted relationships. One might say that banks are moving into the ‘curation’ phase, with AI programmes making recommendations based on past experience, in the same way Spotify might recommend a song or Netflix a TV show. It may not be too long before a virtual wealth advisor tells a client that the stock he declined to buy a few weeks ago has dipped in price, potentially making it a even stronger opportunity than before. Today, this interaction might be effected via an email, a text alert or a chatbot, but longer term it might be part of a personalised, one-on-one dialogue, albeit driven by AI.
It’s a long journey from direct mail to ‘anywhere, anytime’ conversations between bank and customers. But AI has the potential to define the user-experience in financial services such as wealth management just as much as in other customer-facing businesses. The app, just as much as the teller, will cease to be the interface or the voice of the bank. As the knowledge economy matures, financial service providers should perhaps consider where they are on that journey and where they want to get to. For many, it may be a relatively small step to the ‘curator’ level, starting with a focus on the desired client interaction, rather than the technology. Indeed, small steps often give the best chance of new initiatives gaining momentum over time.
It may be a bigger challenge for banks to join tech giants at the ‘conductor’ level, where virtual assistants orchestrate an array of services and capabilities, bringing them to the user at the precise point of need. But even if they are not yet fully deployed in financial services, the tools, skills and capabilities that will help banks begin their own AI journey are already fast emerging and available. According to a report published in March by consulting group Opimas, the financial services sector will spend $1.5 billion on AI this year, rising to $2.8 billion by 2021.
Much has been made of the expected rise of robotics in the 21st century, but Amazon, Google et al have pointed the way to a future in which AI applications consume and interpret data to better meet human needs. In the financial services sector, the challenge is to follow that lead, delivering tailored outcomes that enrich the lives of customers.