In today’s digital world, everyone wants to lead in digital transformation, and the fintech industry is no exception. Digitalization has become essential for business growth. Tech companies are combining next-generation technologies with modern tools to enable automation and drive significant change. This change will streamline operations. Advanced technologies like Artificial Intelligence and Machine Learning are transforming the way the finance and accounting industry operates.
In this post, we will talk about the possible usage of machine learning and artificial intelligence in Financial technologies.
How Do AI and ML Strengthen The Finance Industry?
In 2015, IBM reported that the finance and insurance industry accounted for about 7.4% of the U.S. GDP, or $1.5 trillion. The financial industry collects vast amounts of data daily, including customer queries and company liabilities. Most of this data is confidential or restricted. With the increased risk of cyberattacks, it has become crucial to have a robust data safety system.
Both machine learning and artificial intelligence worked together to relieve the safety-related concerns in the finance industry. Machine Learning (ML) and Artificial Intelligence (AI) help streamline operations by extracting meaningful insights from raw data. They provide accurate predictions that can identify fraud, potential system loopholes, or other threats to future operational integrity.
Leading fintech companies have already started incorporating these two technologies to improve the finance industry by identifying and resolving ongoing and forthcoming alerts. These are the top 10 fintech companies in America that are on a mission to transform the finance industry with high-end technologies.
Here are the possible machine learning use cases in the finance and insurance sector.
1. Financial Monitoring
Machine Learning can be used to improve the algorithms to enhance security significantly. Data scientists have been working on this technology for years to detect alerts such as money laundering or other online frauds.
Experts expect machine learning combined with artificial intelligence to power the most advanced cybersecurity networks in the coming days.
2. Make Investment Predictions
One of the most exciting usages of machine learning is that it makes highly effective marketing predictions based on the previous fluctuations. Machine learning and artificial intelligence work as algorithms to track market changes and ups & downs to develop the best investment strategy with minimum risk possible.
If you plan to invest in stocks, we do not recommend relying on these technologies because human intelligence dominates the stock market.
3. Process Automation
Automation has become the need of today’s emerging financial sector. Since there is no room for errors in the Financial industry, business owners look for algorithm-based technologies to take over the tasks.
Chatbots, paperwork automation, and employee training gamification are some of the best examples of automation in the finance industry. Process automation primarily uses machine learning that enables the finance and insurance companies to enhance their customer experience, minimize costs and scale up the services.
4. Secure and smooth transactions
Machine learning is a reliable technology to detect transactional fraud. The algorithms can track and analyze millions of data centers that is, of course, impossible for humans. Moreover, Machine Learning also minimizes the count of false case rejections and improves the real-time approvals.
Artificial intelligence associated with machine learning is a boon, not just for the financial sector but for the Finance and Accounting market as a whole. According to recent research, the recovery cost for a $1 fraud by financial institutions is close to $2.92. ML-powered software and algorithms can quickly identify and mark events such as fraud or money laundering in transactions.
5. Customer Data Management
Lawful management of customer data has always been a headache for the financial industry. The massive amount and structural diversity in the financial data extracted from mobile communication, social media activity to transactional details, and industry data all come together, complicating the data management process safely and securely.
With machine learning and artificial intelligence, it can be done at ease. Since most financial institutions use clouds to store their data, machine learning can be integrated there to manage the sheer volume of data.
Artificial intelligence can be used as a data analytic tool that can simply analyze the large volume of data sets to process data mining and bring valuable insights for better business operations.
Hopefully, this post has helped you understand the possible uses of how machine learning and artificial intelligence are coming together to shape the financial industry. The next focus of these technologies will be creating a completely automated but secure financial system.