Artificial intelligence is transforming almost every industry, not the least of which is finance. In fact, AI has the potential to increase the income of the financial services sector by 34% and propel economic growth by 26% by 2024.
AI is an essential tool to exert leadership and gain an advantage in the fiercely competitive financial space. The technology enables credit decision making, risk management, fraud prevention, trading, personalisation of banking and financial services, and process automation. Cognitive computing with digital assistants is making personal finance management exponentially easier, facilitating short- and long-term planning.
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Overall, AI drives productivity and value in the financial sector. But the technology can also be a double-edged sword; it can add convenience and efficiency but also make the system more vulnerable. This article explores how AI can be a friend and how its tendency to become a foe can be overcome by liquidity providers (LPs).
Since capital efficiency is the lifeblood of a brokerage, optimised pricing for clients is key to driving revenues and providing superior customer experiences. When AI is employed for provisioning liquidity, it analyses market conditions, facilitates the identification of optimal entry and exit points, and adapts quotes to real-time market conditions. Plus, AI/ML enables data-driven decision-making through advanced predictive analytics.
No wonder then that 60%-75% of LPs believe that AI can significantly transform the process of investment in private equity. AI can also transform pre- and post-trade liquidity decisions.
A prerequisite for optimal pricing is full knowledge of the competitive landscape. However, this does not translate into practice where market knowledge and visibility are asymmetric and incomplete. This is because:
The technology also facilitates dynamic liquidity management. AI-powered intelligent decision-making follows a three-step process of price prediction, price likelihood weighting, and liquidity allocation to carry out dynamic liquidity provisioning.
Liquidity providers use AI-powered tools to dynamically set speeds and offer optimised pricing to their clients. However, there have been concerns regarding such practices associated with regulatory compliance, privacy and ethical implications and the overall data quality (cleanliness, relevance, accuracy and potential biases).
The most prominent challenges for other industries embracing digitalisation and advances in technology do not spare liquidity provision either. Such challenges include unauthorised record retention, cybersecurity, and risk of data leaks. Some of the other challenges include:
Today, the role of LPs has evolved from simply quoting the tightest possible spreads to assessing skew sensitivity, skew leakage and market impact to adequately leverage their resources and offer the best execution. Moreover, the sheer growth in the volume of available data necessitates the use of advanced tools for real-time market analysis. Further, adjusting offers quickly is essential to drive revenues and quantifiable benefits.
Artificial intelligence is facilitating enhanced market liquidity provision with high-frequency algorithms that improve the efficiency of market price formation. AI also makes quantifying “subjective” or qualitative benefits possible for proper liquidity audits and measurement of ROI.
AI is giving birth to the next generation of liquidity management, called dynamic liquidity provision (DLP), a concept borrowed from decentralised finance.
The longer-term objective of AI-powered liquidity solutions is to leverage measurement, simulations and optimisation as inputs to execution systems and to form a feedback loop to enhance the accuracy of liquidity solutions. A need could arise to measure factors beyond explicit transaction, such as cost of capital and cost of clearing, to make pricing more precise and gain a clear picture of liquidity and associated costs.
An AI boom is brewing as data increasingly drives business decisions, especially for liquidity services in the financial sector. Despite some shortcomings, it is increasingly becoming an integral part of liquidity management and provision. The elastic nature of cloud computing is embedding flexibility and scalability within the solution. The ultimate objective is to understand liquidity and increase transparency. It is up to the LP to make a friend of the technology, navigating the complex environment of the industry to help its partner brokers reap the benefits of AI.
While liquidity management is a complex endeavour, the AI technology suite is helping all participants access solutions that give them a competitive advantage in the electronic financial market. It is an ongoing exercise to counterbalance the increasing complexity of liquidity. The added agility in liquidity provision ensures enhanced trading experiences through market prediction, data analysis and transaction optimisation, while fostering smooth order placement and execution.
This enhances the relationship between the LP and the partner broker, making it more efficient and transparent. The only requirement is that the liquidity provision platforms be scalable and flexible to support real-time bespoke pricing that provides tailored value streams to meet individual needs.
Therefore, choose to partner with an LP that has dedicated technology teams proficient in managing the technology infrastructure. X Open Hub is a leading global liquidity provider with solutions that support over 5,000 instruments and multi-jurisdictional compliance. Contact the experts to learn how the award-winning LP can help you gain a competitive edge with stable and reliable liquidity under all market conditions.
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