“Ignoring technological change in a financial system based upon technology is like a mouse starving to death because someone moved their cheese” ~Chris Skinner
The world of artificial intelligence is booming. Artificial Intelligence is a stimulation of human intelligence, it is like a human representation that works better than humans in some cases.
Usually people refer to a single component of AI such as machine learning, while referring to the links of products and services with AI. AI requires a base of hardware and software for writing and training machine languages. In simpler words, AI systems work by ingesting labeled data, analyzing and making patterns out of the data and using the patterns to make predictions. AI focuses on three things: learning, reasoning and self correction. AI is important because it saves a lot of time, improves decision making and reduces clerical work by giving insights into an enterprise’s operation that they might not be aware of. AI is good at detail oriented jobs, it delivers consistent results and AI powered virtual agents are always available. There are 4 types of Artificial Intelligence: Reactive machines, Limited Memory, Theory of mind and self awareness.
One of the examples of AI are self-driving cars that use a combination of computer vision, image recognition and a deep learning of how to drive a car staying in a lane and avoiding obstructions such as pedestrians and potholes. It seems as though no industry or sector has remained untouched by AI’s impact and prevalence.
The world of financing and banking is among those finding important ways to leverage the power of this game-changing technology. AI is increasing in the financial sectors like retail and corporate banking (tailored products, chat bots, credit scoring), asset management (advice, risk management), trading (automated execution, back office), insurance (advice, claim management). The use of AI mechanisms can unlock insights from data to inform investment strategies, while it can also potentially enhance financial inclusion by allowing for the analysis of creditworthiness of clients with limited credit history (e.g. thin file SMEs).
Have you ever asked a chat box a question about opening a savings account? Has your bank ever called you to verify account activity on your credit card? AI in finance transforms the way people interact with money. The majority of banks (80%) understand the potential benefits of AI, but now it’s more important than ever with the widespread impact of COVID-19, which has affected the finance industry and pushed more people to embrace the digital experience. The younger generations prefer digital banking channels with a 78% of millennials never going to a branch if they can help it.
AI in finance is disrupting financial institutions. AI applications collect data of the users and give them financial advice. But with disrupting institutions it also helps the corporates to catch hold of financial crime through advanced fraud detection spot anomalous activity as company accountants etc. it also helps in predicting and assessing the loan risks, taking credit decisions, trading, managing finances, personalized banking etc. HyperAutomation, a part of AI that assists humans to do their job in Machine learning, Data management platforms, Bio Metrics etc, also helps in the financial sector like the Payroll, claims digitization process, revenue cycle management etc. It also helps in the areas of digital asset management by implementing microsoft based RPA solutions and in commodity trading by creating a power apps mobile application and implementing microsoft based RPA solutions. The financial institutions are pushed to increase their IT and AI budgets. Companies like Kensho Technologies, Enova and Vectra AI are examples of financial institutions that use AI. We, as a Team at CFO bridge, are collaborating with InnoHat, working on a production that helps to achieve a business outcome through redefined automated processes with no or minimal human intervention.
AI in finance also means new employment opportunities. According to Bloomberg reporting and data from LinkedIn, job listings requiring AI skills in the financial industry increased nearly 60% in the past year. The most common job openings in AI and FInance are for machine language engineers and data engineers. A person who has a finance background and is interested in AI has an upper hand in these new opportunities.
