As the world transcends towards a more hybrid model, the need to co-depend on machines is the reality that humans are facing. Just like many other technological advancements, Machine Learning and Artificial Intelligence came into our lives, travelling straight from science fiction movies. In the past, people dreamt about machines able to solve problems and release some of the fast-compounding pressure of the 21st century.
Earlier, finance used to be an industry solely dependent on the expertise of a highly skilled professional and purely based on traditional methods. Financial Services sector though has boarded the bandwagon a little late but the synergy that the sector has observed in combining human intelligence is commendable. The rise of AI in the financial industry proves how quickly it’s changing the business landscape even in traditionally conservative areas. Here are just some of the most popular examples of HCI in finance.
HCI and Credit Decisions: Technologies such as Artificial Intelligence provides a faster, more accurate evaluation of a prospective borrower, at less cost, and accounts for a wider variety of factors, which leads to a better-informed, data-backed decision. Credit scoring provided by experts’ industry knowledge and Machine Learning solves and implements the most complex and sophisticated rules compared to those used in traditional credit scoring systems. Digital banks and loan-issuing apps use machine learning algorithms to use alternative data (e.g., smartphone data) to evaluate loan eligibility and provide personalized options.
Application in Risk Management: It is not easy to estimate the impact of emerging technologies in financial services with respect to risk management. Huge amount of data needs to be processed with high end processing power source and ML tools. Cognitive computing helps to manage both structured and unstructured data, a task that would take far too much time for a human to do. Algorithms analyse the history of risk cases and identify early signs of potential future issues. Technology is a powerful ally when it comes to analysing real-time activities in any given market or environment; the accurate predictions and detailed forecasts it provides are based on multiple variables and vital to business planning.
Assists in timely Fraud Prevention: For a few years now, frontier technologies have been very successful in battling financial fraud and is likely to improve in future, as machine learning is catching up with criminals. Tools like AI is especially effective at preventing credit card fraud, which has been growing exponentially in recent years due to the increase of e-commerce and online transactions. Fraud detection systems examine clients’ behaviour, location, and buying habits and trigger a security mechanism when something seems out of order and contradicts the established spending pattern.
Banks also deploy Artificial Intelligence and Machine Learning tools to reveal and prevent another infamous type of financial cybercrime such as money laundering. Machines recognize suspicious activity and help manage costs of investigating the alleged fraud schemes.
Technology and Trading: Traders are assisted by Intelligent Trading Systems, that monitor both structured and unstructured data in a portion of the time as compared to the time a human being takes. While time is money in trading: faster processing means faster decisions, which in turn means faster transactions. The forecasts for stock performance are more accurate, since algorithms can test trading systems based on past data and bring the validation process to a whole new level before pushing it live. Technological advancements combine recommendations for the strongest portfolios depending on a specific investor’s short and long-term goals. Hence, there are many financial institutions that trust ML and AI to manage their entire portfolios.
Synergy in Personalized Banking: Technology truly gives results when it comes to exploring new ways to provide additional benefits and ease to individual users. In the banking sector, new age technologies such as AI fuels the smart chatbots that provide clients with comprehensive self-help solutions while reducing the call-centres’ workload. Several apps offer personalised financial advice and help individuals achieve their financial goals. These intelligent systems track income, essential recurring expenses, and spending habits and come up with an optimized plan and financial tips.
It is visible that the convergence of technology and humans is inevitable in financial services and the benefits are multiple and hard to ignore. As the human-tech gap closes in the future, the sector will tend to deliver accurate results and more tailor-made services by combining human and machine intelligence.
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