Today, artificial intelligence (AI) is a highly valued tool for businesses due to its ability to improve efficiency and productivity. The financial sector, in particular, has begun to adopt AI solutions to transform its processes and services, resulting in a better customer experience and greater efficiency in operations.
The implementation of AI in the financial sector is a strong and growing trend. According to an OpenText survey of financial services professionals, 80% of banks are well aware of the benefits of AI and machine learning.
In addition, another survey on its application in financial services conducted in 2020 by the World Economic Forum, in collaboration with Cambridge University's Centre for Alternative Finance, revealed that financial executives at 151 institutions already saw massive adoption of AI in the next two years, confident that AI will become an essential business driver across the financial sector.
How is it implemented in finance?
Financial firms are using AI to reduce costs and streamline a wide variety of functions, over three main areas: the front office (conversational banking), the middle office (fraud detection and risk management) and the back office (underwriting).
Financial institutions can leverage conversational artificial intelligence to enhance the customer experience by offering faster and more personalized service. Virtual assistants can answer frequently asked questions, such as branch locations, balance inquiries and general bank account information. In addition, thanks to AI technology, these assistants can solve basic problems or requests, such as user authentication, service contracting and appointment scheduling.
Implementing conversational AI solutions in a financial institution's customer service can be very beneficial, as it allows customers to get fast and accurate answers 24/7 without having to wait in line to speak to a representative. This improves customer satisfaction and reduces the workload of customer service staff.
AI is used in fraud management in financial transactions. Machine learning algorithms can detect suspicious patterns that would go unnoticed by humans and alert financial institutions before significant losses occur.
It is also used to assess financial risks by analyzing large amounts of data and patterns. It helps financial analysts predict market fluctuations, identify investment opportunities and make informed decisions. Automated financial advisors, also known as robo-advisors, use AI to provide personalized, automated investment recommendations to investors. By analyzing the investor's personal information, the robo-advisor can create a suitable investment portfolio and manage it automatically.
For example, automating middle-office tasks with AI could save North American banks $70 billion by 2025. In addition, the total potential cost savings for banks from AI applications is estimated to be $447 billion by 2023, of which $416 billion will be in the front and middle office.
In this sector, it can increase the efficiency and accuracy of accounting, invoicing, document management and other routine tasks. With AI, finance teams will be able to execute actions more efficiently, improve decision making and increase their agility in responding to market changes.
By using machine learning models, companies can process underwriting requests faster and more accurately. As business process automation becomes more widespread in finance, the industry will benefit from a complete transformation, paving the way for a more efficient and customer-centric future.
AI-driven business process automation has become a revolution in the financial sector, thanks to its potential to increase efficiency, improve decision-making, enhance customer experience and streamline back-office operations. AI will play a pivotal role in shaping the future of finance by transforming the way finance teams work and deliver value to their customers. To remain competitive and achieve their goals, finance professionals will need to anticipate and leverage AI.
At Hey Now we develop artificial intelligence based solutions that meet the demand for these new functionalities and more.