With the current situation, the Fintech domain is gaining significant traction from the market. The crisis created by the pandemic has effected a lot of companies, but they are adapting well by enabling trending technologies like Artificial Intelligence and Machine Learning into their systems. 

Since most of the systems are now moving towards more app-based processes, these technologies are opening gates to numerous opportunities for people interested in this domain. From SMEs to large-scaled Fintech companies- all are adopting these technologies into their systems. 

How can these AI and Machine Learning help Fintech Industries?

We know that early adopters of mainframe computers and relational databases have been Fintech companies. They were always keen to understand how technology can smoothly solve human problems, thus increasing the companies’ efficiency. These companies started adopting methods that included AI and Machine learning that was derived from various aspects of human intelligence. Varied, deep, and diverse datasets can be crunched easily by using these technologies. 

In the olden days, bankers used to assist customers better with their connections, but with digitalization, this personal touch has been lost. So, the main question here is, can technology bring back this personal touch? The answer to this is quite evident with the current advancements in AI and Machine Learning. These technologies can process large pieces of information about the customers that are practically impossible to do manually. This data that is retrieved can be used to provide better and suitable services or products to the customers. This will ensure that companies find whats right for their customers and gain customer loyalty. 

Top 6 Usecases of AI and Machine Learning in the Fintech Industry

We conducted in-depth research and jotted down the best five use cases of AI and Machine Learning in the Fintech Industry. 

1. Accurate and Improved Decision Making

As our world is quickly growing in the new technological ecosystem, it also becomes prone to several financial cybercrimes. So how do we deal with this? Thanks to AI and Machine Learning, companies can now secure their accounts and provide their users with a safe environment. When we talk about cybersecurity in Finance, we often come across cryptocurrency and blockchain concepts. However, we expect to incorporate Artificial Intelligence and Machine Learning into digital security. 

These algorithms enable us to detect any suspicious activity and also notify users regarding the same. They help us to monitor all sorts of patterns continuously and notify whenever there is anything unusual. This way, users can keep track of all the aspects, even if they aren’t available. These technologies also help us to identify any kind of illegal activity like money laundering or detect any corruption network in any institution. 

2. Fraud Detection and Security Management

Several analytics tools help us to collect and analyze data that is necessary for conviction. After this, AI tools learn and monitor a user’s behavior and pattern to identify any warning signs of fraud attempts. Machine Learning concepts can be adopted in different stages of the claims management system. Artificial Intelligence can be used to handle a massive pile of data in a short time. Thus it reduces the overall processing time. This results in better customer experience for the users. 

3. Automated Customer Care/Support

Chatbots are one of the most popular AI applications. They have started to receive considerable attention due to the involvement of Machine Learning. These chatbots can interact with customers at any given time and hence are quite handy. Fintech Industries use these bots to solve a significant number of customer complaints at the minimum expenditures. Since COVID-19 has given us the new normal of social distancing, Finance companies may soon adopt more of this technology to solve their customer problems. 

4. Insurance Management

Artificial Intelligence will automate the underwriting process and thus use more crude information to enhance customer decision making. This technology can help insurance management by providing automated agents that can help customers online and guide them with all the requirements. Usually, people opt for insurance when they have suffered a loss, and for a faster process, automatic underwriting can be used. For example, if you feel some treatments may be expensive for insurance, it is better to detect these risks for better prevention. These risks can be calculated by using a Machine learning algorithm that will consider historical data.

5. Predictive Analysis of Stocks

Predictive analysis can serve as a game-changer in various financial services that most affect business strategy, revenue collection, sales, and resource optimization of a finance company. It will help in enhancing different operations and refining internal processes, thus transcending all the competitors. This analysis can help in the calculation of credit scores and hence help in the prevention of bad loans.

Final Thoughts

The current situation has given us the opportunity to explore what technology is capable of. It is time that the Fintech Industry adopts these technologies and makes the best use of it in the near future. 

According to a survey by GreatCall, 93% of the doctors believe that healthcare apps and platforms can improve a patient’s health and 80% of physicians are already using mobile and web technology to deliver the patient care. 

The above image from Statista shows us how the market size has been affected by various domains and how it is estimated to increase by 50% in the near years. The market size is predicted to skyrocket by 2025 with a net worth of 60,000 million US dollars.

1. Healthcare Sector

The hospitals are provided with insights on the various patient records, diagnoses, cases etc. Using various business systems and data visualization tools, medical practitioners can operate better by getting real-time information that supports decisions and thus by this, they can deliver actionable insights.

2. Telemedicine

Telemedicine platform allows patients to seek medical advice remotely and discreetly regarding any symptoms they are developing, or possible side effects of certain treatments from certified doctors. The doctor helps in diagnosing the problem and offers consultation followed by the required prescription.

3. mHealth Applications

The health conscious crowd is increasing day by day. People are more drawn towards tracking their fitness and staying fit. These applications insure that a user can log in their exercises and other physical activities by syncing it with their wearable gears. 

4. Wellness

These wellness applications hellp a user to log their everyday lifestyle. They can log in their diets, and various physical activities. They are provided with data like their everyday calorie intake and an apt diet plan that is customised based on their daily activity, BMI, Age and Gender. There are apps that provide trainers and people a platform to exercise and meditate together at the comfort of home. Many apps also help women track their menstrual cycles and also look up for any common health related query. 

5. Healthcare booking

Appointments are automatically placed within an application where it gives the patient and doctor flexibility of time. It also generates automated reminders for both and synchronizes external calendars and doctors’ availability.

6. Clinical Decision Support (CDS)

CDS is a health IT component that has various tools to boost decision-making in the clinical workflow. These tools include computerized alerts and reminders to care providers and patients, clinical guidelines, condition-specific order sets, and other such things. It provides the medical experts and patients knowledge and person-specific information that is sorted by using technology that aids in making this process simple.

7. Wearable Sensors

The basic fitness sensors track the number of steps a person has taken in a day. The advanced wearable gears allow continuous monitoring of the heart rate of a person and also measure the blood pressure. Using this information, the device is able to calculate and report accurate data on calories burnt by exercising.

8. Mobile Wireless

Smartphones, tablets, and mobile apps are changing the physician-patient dynamic. These wireless devices empower the patients to control and improve their health and they also allow the medical experts to conveniently work using these technologies. Social media also plays a vital role in spreading awareness about health on a global level.

In conclusion, the digitization of the healthcare industry, technology provides equivalent opportunities for both the medical personnel and the patients to ease their respective demands.