5 AI Trends to Look Out in 2022

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Nowadays, Artificial Intelligence is becoming the most relevant and hyped topic of the current generation and in 2021. From Facebook renaming it’s company to Meta by pushing their brand into the metaverse to Tesla building the first Autopilot digital automotive, the AI trends are endless with possible opportunities. Below, are the top 5 talked about AI trends to look out in 2022 from our CFTE experts:

1. New AI Tools and Transformations Trend from David R.Hardoon

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Dr. David R. Hardoon is a Managing Director of Aboitiz Data Innovation, Senior Advisor for Data and Artificial Intelligence of Union Bank of the Philippine, Chief Data and Innovation Officer of Aboitiz Group, Senior Advisor of CPF Board and Corrupt Practises Investigation Bureau.

AI has helped to build many tools that are very useful to everyday people. An example is the powerful Language modeling universal translator where someone hears an unfamiliar language, we can use a device to understand them. These AI technologies help us to understand and retain the beauty of various languages by bringing human languages closer to computer code. Another example is many companies have been using satellite sensors and drones as they are getting cheaper and easier to acquire. Using satellite information analytics, it is possible to bring objects from one point to another safely and efficiently.

Explainable AI, help build trust with end-users to further enable adoptions. Bringing industries and combining their respective data for decision-making in a way that is not just a black box. Edge AI is an AI algorithm processed locally directly on or near the device. They are moving closer to the physical assets to reduce latency for data-centric questions and enable more real-time value such as a Smart Fridge counting groceries inside. AI metaverse is a unified persistent digital environment to create online environments that people share and help us with tasks we’re there to do.

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2. AI Trends Applied to Financial Services from Jean-Philippe Desbiolles

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Jean-Philippe Desbiolles has been working in IBM for more than 16 years and is now the Vice-President & managing directors of the Financial Services in IBM France.

Most large companies are deploying AI, globally, 31% are actively deploying AI while smaller companies are still in the exploring phase, 43% globally have not deployed AI yet. Even Though AI is about Data, Algorithms, and technology, we should also focus on the learning, cognitive sciences, and human interactions at the center of everything. AI at scale requires 3 pillars: Operating model (appropriate AI and data factory), Platform Approach (harmonized one AI and data platform), and Trust & skills (transparent, robust, and applicable for all decision-oriented processes). The objective is to create trust, make informed decisions to leverage AI and humans, and be ready for audit and regulatory compliance.

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3. Usage of AI to Modernise Business Models Trends from Diane Nolan

Diane Nolan has been working in Accenture for more than 20 years and is now the Managing Director of the Financial Services.

Data quality is not an excuse for lower returns as speed is everything. A clear data strategy is vital to unlocking the value of accurate data with analytics to get the AI foundations right. A data flywheel increases data utility and drives continuous improvements better than the classic actionable insights model over time. The difference comes from combining process, behavioral (team skills), and contextual data (customers). Modern platforms and startups need to start with data to accelerate AI learning, empower users and enable collaborations to create a movement for automotive deployment.

Companies are becoming sustainable ‘alpha’ by creating their environmental datasets to create sustainable investments and insights. This long-term vision for utilizing ESG utilities to race for AI data leverage and optimize investments. The key is to start the journey now, whether using quantum computing to identify threats and opportunities or to just learn and decide on a quantum innovation roadmap to apply for your innovative business.

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4. Utilisation of AI to Improve Banking and Payments Trends from Winnie Cheng

Winnie Cheng graduated from UBC with a BSc in Applied Science, an MSc in Electrical Engineering from Stanford, and a Ph.D. in Computer science and Finance from MIT. She is the director of AI Lab at PwC, Advisor at Fundnel Limited and Hatcher+, and a Senior Lecturer at CFTE.

Before the pandemic, customers were comfortable doing various banking transactions with digital banking accessibility from their mobile phones, and with the rise of investing platforms and crypto wallets, customers can control their money and accounts. Neobanks user registration doubled between July 2019 to June 2021 while the traditional banking apps shrank a little. On August 19, Chime, US biggest Neobank raised around the funding of $25B. Neobanks offer better convenience and User Experience through digital channels. 70% of transactions are performed by bank customers online.

The pandemic has also driven the growth of contactless payments as it is much more convenient, cleaner, and more efficient than physical cash transactions. A survey done by VISA stated that 48% of consumers would not shop at a store that did not offer contactless payments. Retail investing also increased as people have more free time on their hands and access relevant information from the web. For instance, Gamestop stock boomed 2700% from retail investors.

Cryptocurrency goes mainstream in 2021 and banks are taking them seriously. On October 19, the first US Bitcoin made its debut on a linked ETF on New York Stock Exchange. Banks such as JPMorgan have begun offering Crypto funds access to their clients. Tesla, early this year too, allowed Bitcoin for a short period as an acceptable payment but it may come again soon in the future. Nonetheless, digital currencies are a serious digital asset class. Overall, we are living in an invisible bank era where people are not aware of who is providing the financial service behind the scenes. Fintech is everywhere but in a different form.

5. Personalisation Trend Using AI to Identify Customers Needs fo from Jon-Tzen Eng

Jon-Tzen Eng was an undergraduate of Business (Banking and Finance) from Monash University. He worked in Standard Chartered Bank for more than 14 years. He was the Chief Strategy Officer at a leading Chinese Fintech, Pin An technology. Now, he is the General Manager Of Technology and Innovation at New World Development Company Limited, an Advisor at global startup generator, Antler, and a Senior Lecturer at CFTE.

AI is at the center of everywhere from personalization to investment decisions in financial services. With AI, completing KYC takes less time to identify a customer’s identity in virtual banks to open an account. AI also invented human-like avatars to create natural human line conversations and provide advice and recommendations. As banking is in the business of trust, making AI explainable and transparent is key to maintaining the business going forward. AI enables ‘The Metaverse’ to ensure your authentic identity and to create new interaction with money and services.

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Conclusion

To conclude this article, limitless optimizations and developments can be accomplished in the field of Artificial Intelligence. These top emerging trends are only an indication of what the future awaits for AI and its contemporaries in 2022.

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