From providing entertainment suggestions to facilitating navigation and shopping, AI has increasingly become the backbone of numerous services relied on daily by a tremendous amount of people. According to the survey results, AI is making significant headway in the banking industry and is currently considered a major disruptor in this field.
The ability of AI to sort vast quantities of data, automate repetitive processes and accurately identify outliers has proven particularly valuable in the back and middle offices of financial institutions. From anti-money laundering to payment fraud prevention, AI is helping financial institutions to not only streamline their workflows, but to increase service accuracy by minimizing the risk of human error.
Wealth management professionals are seeing increased AI adoption in the front and investment office, where they have traditionally been reluctant to incorporate AI in the advisory process, according to Gery Zollinger, Head of Data Science and Analytics at Avaloq. When looking into the attitudes of wealth management clients, he added, it’s clear that the time is right for AI to play a greater role in areas such as portfolio analysis or optimization.
“The main benefits of AI technology in finance are enhanced operational efficiency, increased relationship manager productivity and improved data analysis,” said Zollinger. In the following Q&A, he shares his thoughts on the present and future of AI in wealth management.
What are the current uses of AI in the front office?
Two key areas have been identified where AI is already established in the wealth management sector. The first use case is virtual assistant technology to augment the role of the relationship manager. Smart virtual assistants can support relationship managers, for example, by providing near-instant suggestions to client requests for account statements, transfers, trade proposals, etc. This works based on natural language processing (NLP) – similar to the technology behind ChatGPT. The virtual assistant analyses client-adviser communications, understands the client’s intent and suggests next best actions or relevant news items for the adviser to share. This AI support enables the relationship managers to serve a larger and more diverse client base, while ensuring quicker responses to keep clients engaged.
The second is improved client lifecycle management. Wealth managers can deploy network analytics to automate prospect mapping, while churn prediction engines can alert relationship managers when a client is at risk of leaving the firm. In our experience, these tools can enable wealth managers to increase their client acquisition rate by up to 20% while staving off client attrition.
How will AI help wealth management in the future?
Advances in NLP will help drive conversational banking – i.e. interaction with relationship managers over multiple channels – and substantially increase the productivity of bank employees. An exciting future application of this technology is the combination of NLP with a voice-to-text solution. This would enable the AI to suggest next best actions in near real time, such as generating trade ideas, to the relationship manager during client meetings or generate a summary and to-do list after the meeting has finished.
What about AI in the broader banking industry?
The biggest change on the horizon is new regulation on the use and ethics of AI. A prime example is the pending AI Act by the EU Commission, which sets out clear guidance with respect to fairness, verifiability and non-discrimination. We believe that this guidance will give decision-makers the regulatory confidence to implement value-adding AI tools to leverage their vast datasets, which will ultimately boost innovation in the financial sector. Increased client acceptance of AI is expected over time, especially as individuals become more familiar with AI-augmented tools such as ChatGPT.
About Gery Zollinger, Head of Data Science and Analytics at Avaloq, an NEC Company
Gery Zollinger leads the team behind the Avaloq Insight product line, which is designed to embed data analytics and artificial intelligence in wealth management. Gery joined Avaloq in February 2019 from Credit Suisse, in the global Credit Risk Analytics team, where he was responsible for credit risk modelling within the Private Banking and Investment Banking divisions. Gery has worked in analytics and quantitative modelling for more than ten years. He holds a master’s degree in economics from the University of Lausanne.
Avaloq is a premium provider of front-to-back software and services for 160 financial institutions around the world. Avaloq’s clients include private banks, wealth managers and investment managers, as well as retail and neo banks. Avaloq develops software that can be deployed flexibly through cloud-based Software as a Service (SaaS) or on-premises, and the Company offers Banking Operations outsourcing through its Business Process as a Service (BPaaS) model. Avaloq is a subsidiary of NEC Corporation, a global leader in the integration of IT and network technologies. www.avaloq.com
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