Artificial Intelligence (AI) is a powerful tool that is widely deployed in financial services. Less than 70 years from the day when the very term Artificial Intelligence came into existence, it’s become an integral part of the most demanding and fast-paced industries. Forward-thinking executive managers and business owners actively explore new AI use in finance and other areas to get a competitive edge on the market. Artificial intelligence is in the process of transforming a variety of models in the global financial services industry. AI is changing how financial institutions generate and utilize insights from data, which in turn propels new forms of business model innovation, reshapes competitive environments and workforces.
AI and Credit decisions
AI helps banks assess potential borrowers much faster and more accurately, while also saving costs. AI-based solutions can immediately analyze countless factors that can have an impact on a bank’s decision. A recent study found 80% of consumers preferred paying with a debit or credit card compared to cash. But easier payment options aren’t the only reason the availability of credit is important to consumers. Credit scoring provided by AI is based on more complex and sophisticated rules compared to those used in traditional credit scoring systems. It helps lenders distinguish between high default risks applicants and those who are credit-worthy but lack an extensive credit history. Lendingkart Finance is a non-deposit taking NBFC which provides working capital loans and business loans to SMEs across India. Lendingkart has formed technology tools based on big data analytics which aids lenders to estimate borrower’s creditworthiness and provides other related services.
Trading
The trend of data-driven investments has been demonstrating steady growth during the last decade. It’s also known as algorithmic, quantitative or high-frequency trading. Quantitative trading is the process of using large data sets to identify patterns that can be used to make strategic trades. Artificial intelligence is especially useful in this type of trading. This kind of trading has been expanding rapidly across the world’s stock markets. Intelligent Trading Systems monitor both structured like databases, spreadsheets and unstructured like social media, news, etc., data in a fraction of the time it would take for people to process it. The business news outlet, Bloomberg, recently launched Alpaca Forecast AI Prediction Matrix, a price-forecasting application for investors powered by AI. It combines real-time market data provided by Bloomberg with an advanced learning engine to identify patterns in price movements for high-accuracy market predictions.
Managing risk
Risk management is another area of application of machine learning in finance. Given that AI offers incredible processing power and can handle massive amounts of both structured and unstructured data, it can handle risk management tasks much more efficiently than humans. Accurate forecasts predictions are crucial to both the speed and protection of many businesses. Financial markets are turning more and more to machine learning, a subset of artificial intelligence, to create more exacting, nimble models. These predictions help financial experts utilize existing data to pinpoint trends, identify risks, conserve manpower and ensure better information for future planning. GIEOM, a Bengaluru-based AI software provider scans a bank’s core banking software (CBS) and alerts senior management if a particular employee or branch has bypassed important steps before giving a loan.
Personalized banking
Artificial intelligence truly shines when it comes to exploring new ways to provide additional benefits and comfort to individual users. The advantages of AI become obvious when it comes to personalization and providing additional benefits for users. AI assistants, such as chatbots, use artificial intelligence to generate personalized financial advice and natural language processing to provide instant, self-help customer service. Voice-controlled virtual assistants powered by smart tech like Amazon’s Alexa are also gaining traction fast. These tools can check balances, schedule payments, look up account activity and more. A number of apps offer personalized 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. SBI Intelligent Assistant (SIA), an AI-powered smart chat assistant, addresses customer enquiries instantly and helps them with everyday banking tasks like a human does. Developed by an AI banking platform Payjo, this smart chat assistant is equipped to handle nearly 10,000 enquiries per second or 864 million in a day, which is almost 25% of the queries are processed by Google each day.
Conclusion
AI is transforming the financial services industry and we can expect widespread adoption to continue. As the technologies give way to new revenue streams and transform business functions, it’s increasingly important for organizations to focus on the long-term implications of AI adoption. Artificial intelligence is leading the next wave of applications and services
