The Covid-19 pandemic has had unprecedented effects on sectors all over the globe, with the financial services sector being hit particularly hard. Without knowing when things will get back to normal, company executives are having to find ways to cope with the challenges they face.
Chandini Jain, the CEO of Auquan, has a lot of thoughts on this and believes the answer lies in AI. She has over 7 years of global experience in finance, working at Deutsche Bank in Mumbai and New York, and later as a derivatives trader at Optiver in Chicago and Amsterdam. At Optiver, she traded volatility arbitrage strategies and was involved first hand in making the shift from discretionary to quantitative trading. Chandini also holds a B.Tech in Mechanical Engineering from IIT Kanpur and M.S in Mechanical and Computational Engineering from the University of Illinois, Urbana Champaign.
Here she shares her thoughts on how AI can help overcome the biggest challenges faced by CIOs in financial services.
This year has seen the business world turned upside down with a pandemic that has thrown markets into chaos and catalysed a global economic crisis. That market volatility has made things especially difficult for financial firms that need to closely monitor and predict business trends across the world. Chief Information Officers (CIOs) and their data scientists need to adapt at an accelerated pace to stay on top of such economic uncertainty.
These problems presented by the pandemic are compounded with the existing issue of data overload. An estimated 80% of information on the Internet is unstructured data, making it basically impossible to sift through without machine help. So how can a firm efficiently unlock insights into a company or track economic developments to make the best of its investments?
Today the most reliable solution is through the use of artificial intelligence (AI). AI not only gives portfolio managers and CIOs a way to handle massive amounts of data, but also the chance to access market-moving insights ahead of time. Automating parts of the research process and pooling from data science platforms means a firm’s decision-makers can act immediately because they don’t have to waste extra time going through reports and news stories.
Here are three ways AI-powered tools can help CIO’s overcome their most common challenges:
Optimising research for what matters most
For most CIOs at asset management firms or hedge funds, their team’s time is very limited. When combined with everything available on news and social media, data that is already oversaturated with annual reports and stock market fluctuations becomes difficult for CIOs to parse through and make timely informed investment decisions. To ultimately be selective and find the most crucial facts in this mountain of unstructured data requires a honed-in approach that only AI and machine learning can provide to these firms.
Machine learning tools can go through data to identify important information while automatically accounting for context and synonyms. This means that it will pick up results for both Marks and Spencer and M&S as being the British retail company or that a phrase like “Columbia stocks are soaring,” applies to the sportswear company, not the New York City-based university or capital city of South Carolina.
Through the use of AI, financial institutions can combine human rationale with data-driven insights to get the most out of their funds. These quantitative funds are usually performing better than discretionary ones as asset management firms have seen up to a 30% increase in revenues due to predictive algorithms, according to a 2019 McKinsey report.
Getting the best out of a portfolio even in a volatile market
Covid-19 has brought about market volatility not seen since the 2008 financial crisis and, according to Business Insider, volatility is expected to remain high well into next year regardless of a possible vaccine being made available. Thankfully, AI-powered tools are becoming more accessible and can give tools to CIOs, as well as portfolio managers, that help them to expand and refine their portfolio diversification.
The onus will be on fund managers across the world to act immediately to ever-shifting valuations and get their firms out of bad positions. Fortunes can change drastically from one day to the next in today’s market.
For example, Tullow Oil of the UK saw its shares fall 70% at the end of last year to a 16-year low after the company had lowered its production forecasts in Ghana. The move came as a shock to investors. However, with machine learning tools, these investors would have been able to see relevant stories that signaled clear warning signs coming from the African country’s energy sector and would have given a CIO the information needed to pull out of the investment on time.
Being able to catch surprising trends like this early can be the difference between major losses and huge wins. Getting insights quickly can ultimately save cash. Through the use of data-driven analytics, AI can provide the opportunity to tap into more complex information that opens the door to new strategies and outcome-oriented solutions. Being ahead of the curve can enable fund managers to invest early in opportunities and reap the benefits.
Getting better performance despite fewer resources
Jobs in the financial sector have always been insecure, and even more so now. Losing money for one or two quarters – whatever the context – can result in the employee being fired. The banking sector is set to see record job loss this year, as the pandemic accelerates an existing decline in a sector that has lost an estimated 500,000 jobs since 2014. It’s clear that finance workers are under immense pressure in this cutthroat environment to return immediate investment results.
Again, smart solutions work to identify early opportunities and avoid losses. AI tools can increase team efficiency and equate to more time to uncover more prospects. Using AI to manage risk and to generate new revenue potential are its two most common applications among financial firms.
AI and machine learning are perfect for smaller firms and operations that have been forced to size down to save on costs. Massive teams of analysts are likely a thing of the past, as these tools can rapidly synthesise information. In fact, a World Economic Forum survey estimates that about 85% of firms in the financial services are using some form of AI to help their work, meaning those who have not already adopted it are likely far behind their competitors.
For those firms with access to cutting edge technology and with the ability to adopt and integrate new AI tools into their operations, it can lead to a business model that reduces costs while consistently improving their outcomes.
CIOs face undeniable challenges today with an economic crisis that will last for an undetermined amount of time. Couple that with a rapidly growing landscape of information that can feel daunting to comb through, and it becomes clear they will need help from AI to maintain efficiency
