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The Intersection of AI and Other Emerging Technologies

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By Evangelos Skianis, Chief Technology Officer

Technology has revolutionized the financial services industry in recent years, and the pace of innovation shows no signs of slowing down. From artificial intelligence to cloud computing, financial services companies are leveraging cutting-edge technology to create more efficient and client-centric solutions.

As technological evolution is still unfolding, new and emerging technologies will continue to reshape our industry. Here are six major trends that are likely to drive the future of fintech:

Artificial Intelligence (AI)

With applications ranging from fraud detection to algorithmic trading, AI will bring even more sophisticated applications that help financial services companies streamline their operations and deliver more personalized services to clients. AI-powered chatbots and virtual assistants could become commonplace, augmenting the client experience with everything from inquiries, supporting them during specific use cases to identifying patterns in client behavior that could help improve how companies respond to them, thereby strengthening client retention.

AI will also be used to support internal operations to protect client data as well as predicting operational incidents and take actions to resolve them when they occur.

A rapidly emerging field of AI is Large Language Models (LLMs) which underpin modern Natural Language Processing (NLP). LLMs allow computer systems to interpret human language in real-time, thanks to advances in computing power, machine learning techniques, and huge amount of available data that is used for training. Within the financial services industry, NLP can be used to streamline data-gathering capabilities and provide more efficient data processing, removing the need for manual input in many cases which will result in a reduction in human mistakes. We have seen success using this technology in expediting capital statements and distribution payments to create a more efficient workflow as well as using plain English to query APIs and databases without the need of programming skills.

In the next few years, we will see an increase in the number of use cases that AI will automate or augment. As this area is rapidly growing, current machine learning models will fade after a relatively short time. For fintech companies that want to stay on the cutting-edge, they’ll need to monitor the innovations and evaluate when change is required to the models they apply.


Blockchain technology has the potential to improve the financial services industry by creating a more secure, transparent, and efficient system for transferring and storing financial data such as tokens representing financial or physical assets or specific customer data without exposing personal identifiable information.

While blockchain is over 10 years old, it is still in its early stages of adoption, and we expect to see more financial services companies using the technology in coming years. One potential application for blockchain is in the realm of customer identification. By using blockchain to facilitate customer onboarding, companies could reduce the time and cost associated with customer KYC and trust a single source of truth.

Another interesting aspect of blockchain is smart contracts. Smart contracts are software programs that are developed and stored on the blockchain and represent an agreement between two or more parties. These contracts run automatically whenever specific conditions are met and execute transactions and store data to the blockchain upon execution. An example of a smart contract would be a loan facility which can be represented as a smart contract and run daily to calculate interest, or whenever a payment is received to calculate the interest and capital repaid amount. As the smart contract is stored on the blockchain, it can be viewed by participants as well as depend on blockchain build in validations which protect them from tampering.

Since blockchain is a non-centralized technology, it is imperative that financial firms and industry bodies develop and adopt a framework on how to utilize blockchain to share trusted information between participating parties.

Big Data Analytics

As financial services companies collect more data about their clients, they will need more sophisticated tools to analyze and extract data insights from that data. Big data analytics can help better understand client behavior and preferences, identify trends, and make more informed business decisions. For example, financial services companies could use big data to offer personalized investment advice based on a client’s financial goals and risk tolerance or use this data internally to manage market and enterprise risk.

To be successful in big data analytics, companies should set up good data governance and data engineering practices and build centralized teams to implement their data platform by using both build and buy strategies. These teams will be critical and act as a center of excellence as companies will democratize the use of data to multiple teams within their organizations but under a controlled data platform that is constantly improved and supported by dedicated data engineering teams.


This is not a specific technology but instead it involves using a set of technologies such as cloud native services, low-code and data flow tools, Robotic Process Automation (RPA), APIs, and Machine Learning/AI. These technologies will be coupled with an agile product-oriented approach to support a business-led direction to rapidly re-engineer and automate as many of a company’s processes. The global pandemic has expedited this initiative as companies will use hyperautomation to eliminate bottlenecks, optimizes processes, and automate manual tasks which will result in a workforce which will be more productive and motivated to approach new tasks and processes with the use of technology.

Quantum Computing

Quantum computing has the potential to dramatically improve the speed and power of computing. In financial services, this could solve complex mathematical problems that are currently beyond the capabilities of traditional computers. An example of how this technology could be used is optimizing investment portfolios or simulating market behavior. While this technology is still young, it is expected that financial services companies will explore its applications in the coming years.

From an overall technology standpoint, it is expected that Quantum computing will have direct and important impact on current cryptography and secure communication standards as well as AI, and it is wise to keep an eye on post Quantum encryption standards and research and development going forward.

Cloud Computing

Amazon began offering IT infrastructure services 17 years ago and the first big cloud provider was created. Since that time, the field of cloud computing has grown significantly with big technology players offering cloud services and many fintech companies using cloud as their preferred choice of infrastructure.

We expect cloud providers to keep climbing the value chain and compete outside of infrastructure services such as data and integration tools, Machine Learning/AI, business intelligence, low/no code tools and automation tools which will be used by firms to iterate, innovate, and introduce a vast number of efficiencies to their operational teams and clients.

All these technologies have enormous potential to change the way we do business today. At MUFG Investor Services, we explore and evaluate new technologies regularly, in a quest to continually improve how we serve our clients. We serve as a critical extension of our clients’ infrastructures, so understanding their needs and challenges is top priority for us. We are tasked to solve problems for them, and to do this we need to embrace innovation with an entrepreneurial approach and invest heavily in technology – both through build and buy strategies – to provide next-gen solutions that help improve efficiency, security, privacy, and resiliency. Of course, with innovation comes risk, but falling behind the curve is an even greater risk. We know that the rewards of innovation can be huge and by staying at the forefront of technology we are positioning ourselves to be a leader in our industry and to deliver better outcomes for our clients.