Artificial intelligence (AI) in banking is a fast-developing reality as banks around the world are looking to leverage the technology to reduce costs and create better client experiences.

“Based on our UBS Evidence Lab survey of 86 banks, an optimal scenario of limited disruption suggests AI technology could potentially lead to a 3.4% revenue uplift and cost savings of 3.9% over the next three years,” UBS strategist Philip Finch wrote a recent note titled Is AI the next revolution in retail banking?

Goldman Sachs estimates a £26 billion (US$36.2 billion) to £33 billion (US$46 billion) in annual “cost savings and new revenue opportunities” within the financial sector by 2025, enabled by AI and machine learning.

One of the most basic objectives for AI at banks is a reduction in time “wasted” on any task that can be automated. These include rules-based tasks, such as entry, validation, and manipulation of data, as well as creation, uploading, and exporting of data files. Other examples of back-office activities to which AI can be applied include account reconciliation, report generation, mortgage approval, notification of delinquent loans and audit support.

But AI can also be used to recognize customers, offer personalized experiences, services, and build loyalty by offering suggestions based on customer behavior. AI can use transactional and other data sources to help banks understand customer behavior to improve their experience.

Organizations around the world are beginning to greatly simply processes through intelligent automation, according to Mitch Siegel, financial services strategy leader for KPMG. AI enables them to expose and actually make use of enterprise data that’s been traditionally trapped in complex core systems.

UBS has already invested US$11 billion into AI since 2010. That figure is set to rise to more than US$47 billion by 2020. The bank recently unveiled plans to expand a site in Manno, southern Switzerland, into a center for AI, analytics and innovation. The site is to focus on finding specific applications for USB’s information technology platform to use Big Data and AI.

UBS has already launched a robo-advisor that uses machine learning to offer automated investment advice based on customers’ financial circumstances.

Earlier this month, Credit Suisse introduced Amelia, a virtual agent the bank has been developing in partnership with IPsoft, an AI technology provider. With Amelia, Credit Suisse aims to automate IT support.

Last year, the bank unveiled the Credit Suisse RavenPack Artificial Intelligence Sentiment (AIS) Index, a project initiated in partnership with RavenPack to create quantitative investment strategies from news analyses leveraging RavenPack’s artificial intelligence algorithms.

The AIS Index tracks the notional performance of an algorithmic US large-cap sector-rotation strategy, harnessing the power of big data analytics to make sector allocation decisions in a tradable and systematic way. The strategy is based on sentiment scoring extracted from news data by RavenPack’s artificial intelligence algorithms.

Meanwhile, Swisscom has taken two directions in its AI effort: at university research level, Swisscom has its own AI lab at the EPFL in Lausanne, and at startup level, Swisscom operates the Pirates Hub, a community and innovation platform for startups and experts.

Switzerland, an AI hotspot

AI startups are popping up all over the world, and in Switzerland in particular, the scene is growing rapidly. According to Swisscom, the thriving Swiss AI scene has been fueled by a supportive startup ecosystem and the vast amount of corporations looking to enter into development partnerships.

Metin Zerman, the open innovation manager of Swisscom’s Digital Business Unit, publishes the quarterly Swiss AI Startup Map, which presents an overview of around 100 of the most important Swiss AI startups.According to him:

“Everywhere, where companies have universities and research institutes as direct neighbors who attract talent from all over the world and where leading research in AI is performed, is in upheaval.

“A good 60% of all startups on the Swiss AI Startup Map are based in Zurich, while 16% are in Lausanne and the remaining 7% in Geneva, Berne or Basel. A high density of accelerators, incubators and investors can be found concentrated in these metropolitan areas. They are also close to Germany and France, both of which are excellent and growing markets for AI startups.”

 

Process Automation with AI

One of these startups is Parashift, a venture building company for the financial industry. Among other products, Parashift, successfully built Accounto.io, a Swiss based online bookkeeping and accounting service provider. The company is offering it’s Robo-Accounting API based services to large customers and ERP makers.

Parashift is focusing on the development of a few technologies which enables them to use them through a broad range of products such as the machine learning based robotic process automation engine used in Accounto. Furthermore by using similar methologies they are even able to solve complex process automation in banks and insurers.

Featured image: Artificial intelligence, Pixabay.