Global financial crises have led to major upheavals in the economic and political sectors over the years. And recovering from such scenarios often takes decades. For instance, the Second World War and the financial crash of 2008 are two of history’s biggest financial crises; maybe the financial repercussions would not have been as damaging if we had the means to predict the effects of these seismic events.
More recently, the detrimental effects of the 2008 financial crisis led to prominent public figures across the world questioning financial institutions about their inability to anticipate and prepare for such an event. Andy Haldane, Chief Economist at the Bank of England, even went as far as to state that the profession of economics was “to some degree, in crisis". To avoid a repeat of such a scenario, complex efforts are underway to build a solution that can gather the requisite financial information from around the globe and to create new economic models, which can simulate real-world scenarios to accurately predict the next financial crisis.
Today, thanks to recent advances in technology, we have tools that possess the ability to collate and analyze huge volumes of information in real-time. This provides financial institutions with the ability to obtain an accurate indication of the world’s economic health and potential financial risks associated with it. Modern financial systems can understand, reason and learn just like humans; so, they have the ability to anticipate financial crises.
Can AI predict the next financial crash?
At the heart of the field of economics is the concept of money, an invention that is measurable. However, economic history and contemporary events such as the Bitcoin bubble indicate that the ebbs and flows of the financial world are increasingly hard to accurately predict.
The fragility showcased by global economies over recent years indicates that humans alone cannot serve as the sole protectors of the global financial system due to its evolving complexity. The larger question that should then be asked is whether Artificial Intelligence (AI) technologies, including machine learning, can predict subsequent financial crises or not.
The primary drawback of using AI, or similar technologies is the issue around transparency when it comes to the methodology and technology of the algorithms themselves. This issue is intrinsically tied to the credibility of the financial industry itself, and hence requires focused efforts to be redirected towards addressing such concerns.
An AI ecosystem for the world’s economy
Today, the biggest investors in AI and machine learning tools are financial service providers and related industries as their responsibilities include the delivery of insights into financial risks and how to manage them. Subsequently, many other organizations across verticals and industries (in other industries?) have also jumped on the bandwagon and are turning to deep learning technologies to make sense of the unstructured data that is generated from corporate reports and social media. All these organizations are working together to spot financial risks and predict financial crashes whilst uncovering identity fraud and conducting many other routine tasks.
While the number of businesses that are using AI for predictive analyses has considerably increased, many of them still utilize AI for narrow and specific tasks within the complex financial world. For instance, AI is still being used to study either an individual company or a specific financial risk. While it certainly helps to employ AI in such a niche and targeted manner, the need of the hour is a holistic view of worldwide financial risks in a globalized and highly-interdependent world. While current solutions offered by technology firms can address issues such as identity fraud or compliance failures, they are still not mature enough to predict fundamental structural problems that led to the sub-prime mortgage crisis in 2008.
For AI to effectively function as a guardian of the financial world, technology firms and financial service providers need to undertake a greater degree of collaboration and cooperation – not dissimilar to the formation of a united government front in the face of an unprecedented global threat. Such a strategy will play an integral role when it comes to predicting and thwarting the next great financial recession. The vision entails a holistic AI ecosystem that can gather and analyze zettabytes of financial data from a variety of sources to predict highly impactful events before they occur.
Lastly, every new technology comes with its own set of challenges. Implementing AI can also potentially lead to concerns over data protection and intellectual property. These issues will have to be adequately addressed before organizations can confidently claim to have the power to predict the next global financial crash using AI.
(Nageswar Cherukupalli, vice president – Client Services, Financial Services and Insurance, Infosys)