AI is rapidly transforming the finance industry. Fund managers, investment banks, retail banks, private equities and fintechs are recognising the value of machine learning algorithms to their business strategies.
This started with automating manual processes. It has spread to close processes, releasing time and resources for finance professionals to spend more time on analysis, strategy and action.
AI can handle more complex processes than previous rule-based automation applications. This increased capacity improves accuracy and consistency across processes while working with much higher transaction volumes.
AI and data science increase the profitability by helping them to make objective, data-driven decisions. They directly improve margins by, say, more accurately calibrating risk or identifying under-priced assets.
Machine learning improves efficiency for finance companies by reducing costs and raising productivity. They hone decision-making processes, automate execution and refine risk management and regulatory compliance.
Machine learning also offers financial organisations an evolving range of marketing techniques to manage their customers, competitors and market outcomes.
Descriptive analysis uncovers the truths about how financial markets operate. Descriptive analysis provides key summary statistics, drawn from defined objectives, ideally in an intuitive and visually appealing format.
Explanatory analysis demonstrates causality in financial market behaviour. It explains the sequence of events behind a market-based outcome, like an asset price, a yield curve or a portfolio performance.
Predictive analysis quantifies events of strategic interest such as a derivative price path, a paired stock price or an investor’s risk tolerance. This provides a framework for evaluating and ranking strategic and tactical choices.
AI in asset management can analyse the expected returns and volatilities of thousands of securities and provide optimal allocations on a continuous basis. Algorithmic trading exploits complex market patterns to make split-second decisions and execute trades autonomously.
In credit scoring, AI allows for more objective and accurate assessment of potential borrowers. Machine learning algorithms excel at fraud detection spotting anomalies almost immediately.
AI enhances the customer experience. The individual customer’s features, priorities and attitudes to risk can be used to tailor products and services.
Every organisation with data engaging in the broader finance industry can benefit from data science and machine learning. It can sound very technical and specialist, but it’s more accessible than you might think.
You don’t need to know anything about data science or AI. You don’t need to learn anything about machine learning, computer programming or cloud platforms. And you don’t need any expertise in data privacy and security.
We take care of it all so that you can concentrate on executing your business strategy and refining your tactics to maximum effect. This leaves you free to concentrate on making the decisions that count most to you.