Like the European Union (EU)'s General Data Protection Regulation (GDPR) that entered into force in 2016, the upcoming Artificial Intelligence (AI) Act will have extraterritorial scope and global impact. Considering the AI Act's broad scope and the financial risks relating to non-compliance, businesses must prepare for these future regulatory changes now and proactively take the initiatives to comply with best practices early on, according to a new whitepaper by Swiss data services company Unit8. The paper, titled Upcoming AI Regulation: What to expect and how to prepare, delves into the EU's forthcoming AI Act, providing insights into the future development of AI regulation in Europe and the potential implications for organizations worldwide. The European Commission (EC) unveiled a proposal for a legal framework on AI in April 2021, seeking to address risks of specifically created by AI applications, proposing a list of high risk applications, setting clear requirements for AI systems for high risk applications and defining specific obligations for AI users and providers of high risk applications. The proposed rules also propose a conformity assessment method for AI systems, propose enforcement after an AI system is placed in the market, and propose a governance structure at European and national level.

Swiss data services company Unit8 highlights the key analytics trends that we will see accelerating in 2022 in its "Advanced Analytic Trends Report". The report compiles feedback of industry leaders from Merck, Credit Suisse, and Swiss Re, on using mega models in top-tier companies. Mega models (e.g GPT-3, Wu Dao 2.0, etc.) show impressive performance yet are extremely costly to train. Only a few companies are able to compete in this space, nonetheless, the availability of these mega models opens the possibilities to new applications. There is still a major challenge around quality control before these are broadly adopted in a business environment but they already assist developers in writing snippets of code.

Lendable, an AI-powered consumer finance platform, has announced a GBP 210m funding round at a valuation in excess of GBP 3.5bn. The round was led by the Ontario Teachers' Pension Plan Board (Ontario Teachers'), through its Teachers' Innovation Platform (TIP). TIP focuses on late-stage venture and growth equity investments in cutting-edge technology companies led by mission-driven entrepreneurs. Lendable was founded in 2014 with the vision to use technology to make consumer finance work better for hundreds of millions of customers. Lendable applies AI and automation to enhance underwriting, and offer customers better rates, transparency and service, while offering institutional investors ranging from global banks to family offices access to the asset class.

Machine learning is the use of data and algorithms to allow machines to imitate human behaviour. This technology is applied in many different ways. One of these is in the boosting of cyber security, an issue that has become quite sensitive over the past few years. Cyber security can lead to the complete failure of an organization, especially if crucial data is lost to the competition. Customers are also likely to abandon a company if it develops a reputation for poor cyber security.

The leading Swiss AI start-up Unit8 gives something back to society – not just at Christmas, but throughout the year, too. Employees use 10% of their working time for projects dedicated to charitable purposes. Refugees, homeless people, children and young people, and forest fire prevention benefit from these efforts – and last but not least, the employees and customers of Unit8 do, too. Artificial intelligence (AI) does not have the best reputation everywhere and is repeatedly stigmatised as unethical. 'Like any other technology, AI is neutral in nature. Whether it has a positive or negative impact depends on the decisions made by the people who develop and use AI,' says Dr Marcin Pietrzyk, CEO and co-founder of Unit8.

With data becoming a core business asset for financial companies, artificial intelligence and machine learning (AI/ML) continues to be a focal point in maximising the competitive advantage of this'new oil'. This is according to a new study by LSEG Labs, The Defining Moment for Data Scientists, on the applications of AI/ML in financial services. The study found that the adoption of AI/ML within organisations has remained steady since 2018. Over the last three years, between 40-50% of respondents reported deploying AI/ML in multiple areas. The survey is based on responses from 482 data scientists, quants, model governance professionals and C-suite executives, from both sell-side and buy-side financial institutions.

Avaloq and Personetics are entering into a strategic partnership to connect Avaloq's global banking clients with Personetic's AI-powered personalized engagement solutions. Personetics, a global provider of data-driven and personalized engagement solutions for bank customers, is joining the Avaloq.one This partnership gives Avaloq's banking clients access to Personetics Engage, a business solution that offers deep analysis of customers' financial data in real-time, understands their financial behaviour, anticipates their needs and acts accordingly on their behalf. Personetics Engage provides data-driven day-to-day personalized insights, financial advice and wellness programmes, tailored to mass market, affluent as well as small business customers. Personetics Engage is supported by a rich set of tools used to help banks create Personalization IP for market differentiation while delivering significant business impact.

In a whitepaper released last month, the European Commission (EC) unveiled its strategy to promote the development of artificial intelligence (AI) in Europe whilst ensuring the respect of fundamental rights. The whitepaper outlines the institution's plan to develop what it calls an "ecosystem of excellence" and an "ecosystem of trust." The idea here is to create a legal framework that would address the risks for fundamental rights and safety related to AI, all the while introducing initiatives to support and facilitate the adoption of the technology. "AI offers important efficiency and productivity gains that can strengthen the competitiveness of European industry and improve the wellbeing of citizens," the paper says, adding that AI can also contribute to finding solutions to urging societal challenges related to sustainability, demographic changes, democracy and crime. At the same time, AI entails a number of potential risks such as opaque decision-making, discrimination, intrusion in citizens' private lives or can be being used for criminal purposes.

In the same way technology is changing the financial services industry, technology is also changing how the industry and supervisory authorities implement and enforce regulations. Today, an increasing number of supervisory authorities are turning to technology to support their work, leveraging so-called supervisory technology (suptech) applications to digitize report and regulatory processes. Suptech refers to the use of innovative technology such as artificial intelligence (AI) and machine learning (ML) by supervisory agencies to support supervision. As with other regtech solutions, suptech is about improving efficiency through the use of automation, streamlining administrative and operational procedures, and digitalizing data and working tools. The main goal here is to reduce the burden on firms and allow for more proactive monitoring, better reporting, oversight and overall compliance on the regulator's side.

In the same way technology is changing the financial services industry, technology is also changing how the industry and supervisory authorities implement and enforce regulations. Today, an increasing number of supervisory authorities are turning to technology to support their work, leveraging so-called supervisory technology (suptech) applications to digitize report and regulatory processes. Suptech refers to the use of innovative technology such as artificial intelligence (AI) and machine learning (ML) by supervisory agencies to support supervision. As with other regtech solutions, suptech is about improving efficiency through the use of automation, streamlining administrative and operational procedures, and digitalizing data and working tools. The main goal here is to reduce the burden on firms and allow for more proactive monitoring, better reporting, oversight and overall compliance on the regulator's side.