Switzerland’s Financial Sector Embraces Machine Learning Technology, Revolutionizing Industry
Switzerland’s banking and insurance sectors have undergone a significant transformation over the past year, rapidly integrating machine learning applications into their daily operations. This shift towards digitalization is not only resulting in cost savings but also enabling the provision of ultra- personalized financial services.
Widespread Adoption of Machine Learning Technology
Machine learning technology has become increasingly widespread in Switzerland’s financial sector. Banks are utilizing it for risk and fraud assessment, automated compliance checks, and even autonomous client onboarding.
Risk and Fraud Assessment
According to Pascal Wyss, Head Artificial Intelligence at Zurich-based Technology, Innovation & Management (TI&M), machine learning is used by banks to rapidly process large amounts of data in risk and fraud assessment. The technology alerts compliance officers to any suspicious activity, allowing them to focus on complex cases and undertake additional assessments when necessary.
Automated Compliance Checks
Machine learning technology is also being utilized for automated compliance checks, enabling supervisors to verify clients’ backgrounds and ensure they are not politically exposed or linked to blacklisted countries.
Autonomous Client Onboarding
The autonomous onboarding of new clients has become a common practice, with some banks able to open accounts in as little as five minutes thanks to artificial intelligence.
Challenges and Opportunities
While the adoption of machine learning technology is gaining momentum, several barriers hinder its swift adoption. The legacy IT infrastructure used by banks often lacks the necessary flexibility and capacity to support state-of-the-art algorithms and produce real-time outputs.
Explainability
Explainability is a major issue, as bankers must be able to interpret and understand how AI and ML systems make decisions. Stringent data protection laws, such as the EU General Data Protection Regulation (GDPR), also require the explainability of machine learning software used by Swiss banks.
Future Developments
In the next phase of machine learning development, ultra-personalized financial products and services are likely to emerge, with companies offering cross-services based on client data. This could include:
- Personalized banking services
- Optimized trading costs
- Portfolios designed to reflect clients’ risk appetites
Conversational Interfaces
Conversational interfaces in the form of chatbots will also become more prevalent, enabling complex queries to be answered. For example, chatbots may calculate how much someone should inject into their supplementary pension scheme by analyzing earlier bank transfers.
Accelerating Adoption and Future Outlook
The use of AI applications within Switzerland’s financial sector is expected to accelerate in the coming years, partially driven by the strong presence of fintech start-ups in the country. As machine learning technology continues to revolutionize the industry, it remains to be seen how these innovations will shape the future of finance in Switzerland.