By Senior Consultant, Justin Hannaford.
Artificial Intelligence (AI) is widely recognised as a disrupter within the Investment Management industry. This is because it has the potential to fundamentally transform, among other things, efficiency, and competitiveness. The technology encompasses a wide range of applications and techniques. In many cases, it should be viewed as a tool to augment processes; with humans collaborating closely with machines to perform tasks. By delegating automation to machines, humans can be released to take on more challenging work that adds value to an organisation. With the pace of innovation and change happening around us, the full scope of solutions that AI can deliver is almost limitless. Below, I will discuss four areas within Investment Management that could be considered ripe for AI transformation.
The most obvious use for AI is its ability to automate repetitive, manual tasks through usage of tools such as Robot Process Automation (RPA). Rules-based RPA, to some degree, has been around for a long time. However, AI can now combine adaptive learning behaviour of bots to deliver agile, robust, strategic solutions. These automations can help reduce risk and costs while delivering increased efficiency and accuracy.
Another high-profile candidate for using AI is the collation, manipulation, and analysis of vast amounts of data - using processes like Machine Learning Models and Deep Learning. Both processes utilise algorithms that learn and train themselves to make decisions without being explicitly hard-coded for the task. Deep Learning is one step beyond basic Machine Learning in that it uses neural networks with multiple “deep” layers instead of using simpler, traditional algorithms. It also refines this continuous learning via back propagation, using these complex hierarchical neural frameworks. Within Investment Management, these tools could be leveraged to provide:
Market Analysis: The ability to consume and analyse vast amounts of historical and real-time data can assist Investment Managers recognise trends, patterns, and irregularities. This information can be vital as part of an informed decision process.
Scenario Analysis: Investment Managers can stress-test portfolios within simulated market scenarios generated by AI.
Predictive Analysis: Using Deep Learning and its continuous learning capabilities, AI can make informed predictions about market movement or economic trends.
Powerful AI algorithms can be used to execute a significant volume of trades at high speed. This speed can exploit market opportunities and inefficiencies that would be extremely difficult, if not impossible, for humans to exploit. This type of automation could help reduce operational and transaction costs.
Using tools such as Optical Character Recognition (OCR) and Natural Language Processing (NLP), Cognitive RPA can consume and manipulate unstructured datasets. OCR can be used initially to extract text and data from social media, web-scraping from the internet, as well as images and other unstructured, “unfriendly” formatted media. Once extracted, NLP can be employed by the RPA tool to identify and analyse context-specific information. Additionally, NLP can validate and enrich this data by cross-referencing against rules predefined within the RPA process. There are multiple uses for this data - including being used to assess market sentiment or identify market-moving events.
The above is by no means an exhaustive list of applications of AI within Investment Management. This technology, and its usage, will continue to constantly emerge and evolve in line with industry requirements and trends over the coming years. Organisations should look to leverage AI, not just by implementing the status quo, but by using the opportunity to reevaluate and redesign processes to fully exploit AI capabilities.
Here at Liqueo, we provide organisations with the skills to implement programmes successfully through our flexible workforce model, tailoring solutions for our clients’ strategic goals. We deliver an exceptional, bespoke service to every client via a dynamic and agile framework. If you are interested in how we can help you implement successful programmes or want more information about AI and how it could be incorporated into your organisation, please contact us.
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