With a tectonic shift towards digital over the past 12 months,, the world is moving at an accelerated pace. The arrival of 2021 is a good time to pause a moment, take a step back and consider what is in store for financial services when it comes to artificial intelligence (AI) innovation. In this post, we uncover 5 AI trends shaping the industry and the impact it’ll have on Financial Services firms in the near future.
It’s not an overstatement to say that AI is influencing every industry and almost every human being on the planet. It has played a transformative role in everything from robotics and big data to the Internet of Things (IoT) as well as our day-to-day interactions through an array of digital devices. In addition, the pandemic has helped us to adapt to uncertainty which has led to a rapid change in consumer trends. Consumer behaviour is now more geared towards digital which in turn, has influenced businesses to prioritise AI and digital transformation.
Studies show that 77% of executives from 151 financial institutions expect that AI will be essential for their business within the next 2 years. Research from Mckinsey has found that AI technologies can help boost revenue through increased personalisation of services to customers, lower cost through efficiencies, reduce error rates and uncover new opportunities based on a vast abundance of data. It also has the potential to unlock $1 trillion of value for banks annually. There is huge potential for this technology to revolutionise the financial services industry and provide us with the change needed to drastically improve customer services.
We’ve done the leg-work and found 5 AI trends that financial services firms need to pay attention to in the coming year:
1. Personalisation and Better Customer Engagement
AI lets firms reduce the time they spend on things like customer identification and due diligence from hours into minutes. Financial service firms can use AI to not only improve client experience by offering seamless and consistent interactions but also by using customer data to highly personalise and enhance those interactions.
Many banks are already offering AI chatbots that can answer questions from customers, manage their requests as well as offer product recommendations. And they can do that 24/7/365. Going one step further, firms might consider Robo-advisors that can create personalised investment portfolios. This allows current employees to redirect their focus on high-value work, which includes building stronger customer relationships or improving the production/innovation of new products or services. Here at Aveni, we also use AI in this way, our technology works alongside employees, rather than replacing them. We will see in the coming years that technology will be used to better understand consumers and their behaviours making certain operations quicker and more accurate as standard.
2. Natural Language Processing (NLP)
Natural Language Processing (NLP) is being used increasingly in the financial sector to evaluate performance drivers as well as forecast the market. It also has the ability to access a range of speech and text data from a variety of different contexts. Another benefit is that it helps banks automate and optimise tasks including collecting customer data as well as searching for specific documentation. Additionality, one of the biggest advantages of using NLP is that it supports fraud management. NLP can monitor suspicious activity as well as develop tools to address the problem. As well as this, NLP helps with due diligence and the screening for anti-money laundering (AML). Therefore, human error is removed, reducing the strain on resources, enabling employees to focus on more high-value outputs. This is because its systems are able to track risk areas and support communication throughout the organisation, addressing the issue before it becomes a major problem. Long term, this helps to reduce the risk of incurring losses. It also helps financial institutions to make better investments decisions as well as assist in streamlining risk management and compliance. This is particularly relevant in response to the current COVID-19 pandemic.
We will continue to see NLP being used within financial services as a way of closing the gap between computers and humans, by allowing machines to better understand commands given by humans in a seamless manner. This is because the financial service industry is dependent on information that is as close to real-time as possible. In order to access and analyse information rapidly, financial institutions are turning to NLP to help them make decisions and provide appropriate advice to their customers.
3. Robotic Process Automation (RPA) and AI-driven Automation
Robotic Process Automation (RPA) is a software robot that imitates human actions, while AI is a simulation of human intelligence that is led by machines. Because of this, RPA has become one of the hottest categories in tech. It enables the automation of tasks for workers, which reduces operational costs, boosts productivity and provides a high return on investment (ROI). These advances in AI not only provide a wave of opportunities but also allows for great intelligence and cognitive understanding of workflows and processes.
RPA has become the new digital workforce within financial services. It has the ability to streamline purchase orders and update client profiles to reconcile their financial statements. This logic-driven software is able to manage repetitive, time-consuming tasks that are usually carried out manually by humans. To put it simply, RPA automates simple tasks so that businesses can increase productivity as well as improve their quality of work. So, this provides a step up from intelligent automation. Although RPA is still largely in development, we will see it becoming more mainstream, improving customer experiences and providing more flexibility. When pairing AI and RPA, it can help CIO’s to diagnose and respond to IT issues in real-time. The true benefit of this is detecting abnormalities early on and helping to close the loop to ensure consistency and increase data quality.
4. The Merging of AI and The Internet of things (IoT)
The combination of AI and the Internet of things (IoT) is one of the most significant keys in accelerating technological development. It also enables disruptive services within the digital domain. According to McKinsey, the number of internet-connected devices is set to increase to 43 billion by 2023. This rise will help companies to flourish as new sensors, increase in computing power, and reliable mobile connectivity pushes advancement and becomes more widely available.
The impact IoTs will have on the financial services industry is that it will allow for more personalisation of products and services which will be centred around customers’ needs as preferences. For example, retail banks will be able to provide more personalised service as they will be able to use IoT to analyse a multitude of customer behaviours including their spending habits. As well as this, wearable payment technologies can be used to build customer profiles and enable fraud detection. This data can be used to take customer relationships one step further, by working in partnership with brands to ensure improved security for their customers as well as offer useful perks.
As financial service firms begin to experiment with IoT and big data, it presents an exciting opportunity for the industry. It’s time for financial service companies to move away from frictionless interactions and implement digitised business processes. By integrating such processes, it will close the “value gap” and regain consumer trust.
5. AI in Risk Management
Due to the financial crisis in 2008, many institutions strived to drive cost efficiencies to counterbalance margin pressures. One way they looked to improve this was through technology, and AI is believed to have had the biggest impact on improving current challenges. A report conducted by Deloitte, confirms that 56% of C-suite executives agree that AI has had the greatest impact on risk management.
By applying AI to risk management, companies are only able to monitor a tiny fraction of interactions, whereas AI can monitor 100% of them, in real-time. This innovation allows companies to respond quickly to fraudulent activities and helps reduce time and effort involved in risk management. Our current product, Aveni Detect is built with cutting edge AI and does just this. Our live monitoring software supports your agents in real-time, letting you move from second-line control to AI-driven detection and prevention at the point of sale or service. With the current economic situation, there has been an increase in online financial transactions and fraud, that’s why it is essential to have a good system to help detect and report fraudulent activities and respond to them accordingly.
Where Do We Go From Here?
AI will transform 2021 even after the pandemic itself has subsided. It is clear to see the benefits of AI in financial services and we will see it grow as we adapt to new technologies in the future.
There are high hopes for increased transactional and account security, as we see the adoption of blockchains and cryptocurrency grow. All kinds of apps and digital robot assistants will continue to improve themselves, thanks to cognitive computing. This will see the management of personal finances become easier and more accessible. Overall, we await better customer care as the use of self-help virtual reality systems are brought to light due to advances in NLP and learn from the data pool of past experiences. As we see this transformation within the financial service industry, we will also learn to adapt to AI in other industries such as education, transportation and healthcare.
As we move forward into the new year and adjust to our “new normal”, AI will be fundamental in making our lives more efficient. This is because AI powers many services that help us in our day-to-day activities. We will become more familiar and more comfortable with AI and it will help companies to build more powerful, more relevant customer experiences.
Learn more about we use AI, visit Aveni Detect