Artificial Intelligence in terms of opportunities and challenges for Swiss banks
Yesterday we were amazed by the first smartphones. Today they have almost become an extension of ourselves. People are now used to be connected all the time, with highly efficient devices on highly responsive services, everywhere and for every possible need. This is a new industrial revolution – the digitization . and it forces corporations to transform their business models to meet customers on these new channels.
Banks worldwide are on the first line in this regards and for many years now they have well understood the urgency in proclaiming digitization as a key objective. From a user perspective, the digitization confers enormous benefits in the form of ease, speed and multiple means of access and a paradigm shift in engagement. Since banking as a whole benefits from going digital, it is only a matter of time before operations turn completely digital. The journey to digital transformation requires both strategy investments as well as tactical adjustments in orienting operations for the digital road ahead. Fortunately, if technology can be perceived as a challenge, it is also a formidable opportunity. An in this regards, Artificial Intelligence is a category on its own.
Artificial Intelligence and it’s potential in the banking business.
AI provides a unprecedented opportunity to make banks smarter. Deploying AI solutions in banking leads to better customer intelligence and better customer experience. Both are key to increase benefits and reduce operational costs. There are multiple applications for AI solutions in the banking business around three major axis:
1. Customer Experience revolution when putting technology in direct contact with the customer
2. AI analytics improving operational efficiency in various domains (e.g. investment research, credit scoring, etc.) or providing personalized advisory to customers
3. Risk mitigation with better fraud detection, more efficient AML, more efficient compliance controls, etc.
One of the most impressive opportunity on the customer experience revolution axis is formed by chat-bots and voice assisted banking. The need for physical presence is definitely fading and technology empowers customers to use banking services using voice commands and touch screens.
In regards to improving operational efficiency within the bank, the most promising evolution comes form the conjunction of Real-time Big Data processing with Machine Learning. The technology can provide personalized, value-added products to customers as it learns about spending habits or investment profiles, but it can also automate most analytics duties within the bank. Data-driven AI applications are intended in the future to cover the whole range of financial decisions: advisory, calculations, scoring and forecasts, for the bank as well as for the customers. For instance if approving a commercial real estate loan was traditionally a several days process within a bank, using AI will reduce it to a few dozen of minutes. Last but not least, embracing AI has been at the root of significant improvements in Fraud detection and AML. Companies like MasterCard and Visa have been using AI to detect fraudulent transaction patterns for several years now. At NetGuardians we deploy AI solutions for digital banking fraud prevention and internal fraud detection for several years as well. AI solutions are key to react proactively and inform the customer before the funds leave the bank. AI enables to implement Transaction analytics but also behaviour analysis aimed at catching more complex fraud patterns.
What about Swiss banks ?
Interestingly, while most would describe Switzerland as less innovative than other countries such as UK for instance, especially in the retail banking space, the reality is a quite differentiated picture. The digital solutions of the major Swiss banks are among the best in the world and Machine Learning algorithms are used down the line on the three axis described above. Due to their conservative nature, the major Swiss banks have a tendency to rather follow the market best practices and state of the art in terms of customer experience evolution but on the backend side – the technology running under the hood – they are rather very well in advance. The situation of smaller Swiss retail banking institutions is somewhat similar. Their strong footprint in their regions, their attractive conditions as well as their good digital banking solutions in general relieves the pressure. The biggest difference with major banks is that smaller institutions don’t necessarily have the ability to research AI or Machine Learning technology on their own so they rely on third party providers such as NetGuardians for fraud prevention or other fintechs for other use cases.
In this sense, keeping a close proximity with engineering schools and universities is a tremendous opportunity to stay on the top of the game and get in touch with the numerous fintechs flourishing in Switzerland. One could only advise them to be less timorous when it comes to supporting these startups since investing in them is eventually their only way to support the development of the technology that will be available to them in the future. Private banking institutions on the other hand are more vulnerable today, at least for the smaller ones. Their margin is reducing and their wealth management business is increasingly cannibalized by other actors such as External Asset Managers, Fintechs or bigger institutions – even retail institutions where AI has been instrumental into making them reach a level of proximity in advisory that was so far the exclusive privilege of private banks. Private banking institutions need to understand the urgency in revolutionizing the private banking customer experience and recover the lead in this regards from the other actors. Here as well the opportunities for Artificial Intelligence applications are striking: operational efficiency, advisory, etc. |
Chief Technology Officer