Amidst the uncertainty of the pandemic, capital markets firms are forging new paths towards growth.
As a result, record numbers of Australian firms have set their sights on Artificial Intelligence (AI). In fact, new research reveals 40% of Australian sell-side firms and 60% of buy-side firms are planning on investing in AI in the next twelve months to enhance their competitive strategy and growth trajectory.
This investment and adoption across capital market firms is being closely mirrored at a government level, with the Australian Federal Government recently announcing an AI Action Plan. This entails an investment of $124.1 million to aid Australian leadership in developing and adopting responsible AI.
While these are promising developments, the data shows that there is still plenty of work to be done, particularly on the sell-side with just under one-third (30%) of firms rating their AI capabilities as very effective, compared to 59% globally. For AI to really reach critical mass, firms need to understand the value of AI to their business and tackle their barriers to adoption head on.
The AI potential
AI is becoming a game-changer for capital market firms for several reasons – from improving operational efficiencies to delivering smarter investment ideas. Our research shows that the top reasons why Australian sell-side firms are investing in AI are to strengthen compliance and risk management (40%) and enhance process automation and operational efficiency (40%). On the other hand, buy-side firms are advancing their AI projects to enhance investment insights by combining new data sources (60%).
Using robotic processing automation technology, AI is helping firms cut significant amounts of manual activity from operations. Additionally, the rise of big data coupled with increased maturity of AI and machine learning is transforming the traditional investment process. In market, we’re seeing investment and portfolio management sectors leveraging AI applications to predict the performance of their investments and modelling risk. Asset managers, for instance, are using AI and alternative data to calculate and enrich their investment decisions.
The adaptive, predictive power of these technologies enables firms to dramatically deliver continued value and reshape operating models. When used correctly, the benefits are not only profound but incredibly diverse.
One other significant applications of AI for capital markets firms is in the fight against financial crime. Money-laundering schemes have grown increasingly sophisticated as financial criminals exploit the rise of the digital economy during the COVID-19 pandemic. AI helps firms to connect disparate sources and types of data, manage high volumes of increasingly sophisticated transaction types, all while working in an increasingly shortened detection time frame and remediation period. This means that it is easier for firms to spot suspicious behaviour, reduce false positives and trace the life of the crime. This helps firms to reduce AML risks and stay compliant in the face of ongoing regulatory upheaval.
Despite the fact many firms are looking to increase their investment in AI, hesitancy around the technology remains. Much of this stems from a lack of understanding around what AI is and does. Also, in the case of AML, firms often have concerns on how the surveillance will be used, how it will affect their customers, and how they should provide outputs and feature-based explanations to regulators.
But firms need to remember that AI is just a collection of advanced calculations that boil down to making predictions by leveraging all data sets to get a 360-degree view. In fact, the same data that is used for AML prevention may also lead to higher productivity and surprising new ways to serve customers.
Ultimately, implementing AI requires the right combination of technology, processes and people. In order to identify the right AI tools and models, firms need AI talent that can master the full spectrum of the data life cycle and are cognizant of the problems they are trying to solve. The AI talent need to understand the nuances within AI models so that they can shift from a rule-based system to one that leverages the adaptive power of machine learning to develop and train models.
The key to future success
There is a real cost to ripping out old systems and process – and to buying and implementing new ones. But with better processes and smarter tools, financial institutions will reap countless benefits. From cost savings through AI-powered automation to enhanced decisioning and analysis, AI offers great promise for forward-looking financial institutions that want to tap into their data for competitive advantage.
With AI proving to be no longer just a viable option for capital market firms, but fast becoming the competitive edge integral for future success, we are certain that the next 12 months will see AI become more mainstream within the financial sector.