It has been well accepted that Artificial Intelligence has contributed to increasing productivity as well as efficiency in the finance sector. Artificial Intelligence involves the use of data, rules, knowledge, etc to find solutions to problems that were classified as unsolvable a few years back. The use cases in finance for applying AI techniques to improve existing processes are numerous.
AI in finance is reshaping the business, from addition to wealth management and providing personalized financial services. Here are some use cases where AI has established its importance in finance.
- Building individualized finance:
According to a report by Deloitte , customers are expecting individualized services from retailers. That is the services which can be personalized according to their own interest. In the case of budgeting apps, artificial intelligence helps customers to track their spending habits, giving you tons of cognizance into what you are spending money on. The banking applications can offer savings recommendations based on a customer’s income. Algorithms like apriori are used in departmental stores to discover useful information about customer’s behavior and transactions. AI powers the smart chatbots that provide clients with solutions while reducing the load on call centers.
2. Empowering financial inclusion:
In 2017, 1.7 billion people globally were unbanked due to unavailable credit score, according to the Global Findex database published by the World Bank . Due to AI, financial services are getting more affordable for individuals and businesses. AI-based tools can enable financial inclusion by using data and AI algorithms to detect financial frauds. It helps finance lenders differentiate between high-risk applicants and those who are creditworthy. According to Jessica Goepfert, program director at market research firm IDC, the industries like banking and security will have opportunities for cognitive systems.
3. Identifying potential future risks:
It’s difficult to exaggerate the influence of AI in the finance sector to predict and manage potential risks. AI algorithms analyze the history of risk cases and predict the early signs of future risks. They can efficiently analyze real-time activities in the market and can provide accurate predictions and detailed forecasts. A Los Angeles-based company Zest.ai used machine learning algorithms to predict risk and reduced loss by more than 25% annually .
Data-driven investments also known as quantitative trading have been rising steadily over the last 6 years. Such type of trading is expanding swiftly across the globe and AI offers multiple benefits. AI monitors both structured data like spreadsheets and unstructured data like social media. In trading, we can say “Time is money” because faster decisions mean faster transactions. The deep learning architectures like LSTM and GRU can keep track of past transactions in its memory cell for predicting stock performances.
5. Finance through social media:
We share vast information on various social media platforms including photographs, thoughts, interests, etc. Fetching useful information from this huge amount of data is a challenging task for all kinds of businesses. This is where AI algorithms come into the picture. The big giants like Amazon, eBay extract your personal data when you like/share the post you are interested in shopping, feeding you relevant posts within a couple of minutes. Facebook knows your past, Google knows your present but, Pinterest desires to know what you want next hence, Kosei has assisted Pinterest in developing an AI-based interface that can provide personalized recommendations based on user-specific searches and interests . Thus companies are boosting their finance by extracting relevant data from user feed.
In 2017 artificial intelligence started gaining its position in the market. Majority of companies began investing in R&D to automate their process and to detect numerous frauds. In 2019 the global AI in finance was estimated at USD 6.67 billion and is expected to reach USD 22.60 billion by 2025.
What to expect in the future from AI in finance sector ?
Predicting early outcomes is a hot topic these days for the bodies working in finance but, one thing is for sure: AI is innovating new techniques day-by-day for reshaping the financial industry. AI will increase transactional security as the adoption of blockchains and cryptocurrency expands.
All kinds of AI-powered assistants will continue their process to perfect themselves due to which customers will have the freedom to personalize their financial services. The finance sectors will get a boost due to more involvement in AI.
We also expect to see better customer care services with help of AR/VR systems that use AI as a base layer to build applications. The growth of syntax and semantic analysis will improve NLP applications to build comprehensive responses.
Authors: Yash Jadhav, Pratik Fandade, Adnan Sadar, Akash Dhadiwal, Nikhil Ravulaparthy.
We hope you find this blog interesting and helpful.