• Machine Learning
  • 5 min read

How AI and ML are shaping the banking and finance Industry 2022

How AI and ML are shaping the banking and finance Industry 2022
Machine Learning is part of artificial intelligence that learns from the data without explicit programming or human interference. AI and ML are transforming the world of banking and finance management. The Existence of AI and ML is enhancing everything starting from customer service, personal finance to fraud and risk management. It is impacting the industries both ways - beneficial and detrimental. There are so many services that have already been better due to AI and ML. such as
  • Minimum operational costs
  • Enhanced customer support 
  • Improved risk management
  • Daily work automation 
  • Increased service speed
  • Improved data processing accuracy and speed
According to Business Insider, The usage of AI and ML in the banking industry will save $447 billion by 2023, and it can reach up to 1 trillion by 2030. 

#1. ‌Investment Management‌

A few years ago, investors and asset managers were clueless about AI and Ml integration into the finance industry. But with the growing time, AI and ML have made it almost easier for investors and managers to analyze technical and fundamental datasets, develop predictive models, and create investment ideas faster and in real-time. Along with that, AI has enhanced an investment process that demands minimal supervision, diminishing the process cost while bringing in money at the same time. 
AI can also be used in the finance Industry for: 
  • Portfolio management 
  • Risk management
  • Compliance oversight 
  • Automated analytics 
  • Automation of office tasks
The finance industry is still not utilizing AI and ML at their full potential. We have a long way to go to fully automate the finance industry.

#2. Risk Assessment 

The finance industry requires accurate data processing. Human hands are not enough to fulfill those requirements in real-time. That always increases the chances of fraud risk. A study by PwC stated that around 47% of companies surveyed were targets of fraud, with an average of six incidents registered per company.
AI in the finance industry helps them to analyze every single transaction in large data sets. AI enables software to dig the processed and even unprocessed datasets in no time accurately. It can provide a report on anomalies of the dataset that aid in risk assessment and mitigation. 
It also helps the organizations to run monthly, quarterly or yearly audits that can flag out the risks as soon as possible.

#3. Credit Evaluation 

Credit evaluation is best for every financial organization before funding anyone. It demands a long process including:
  • Getting accurate information about the applicant
  • Analyzing the collected data to specify the applicant’s creditworthiness
  • Finalizing the creditable amount
This process demands both time and accuracy. The finance organization who has more time on the credit evaluation process is the most unlikeable one for everyone out there. The credit evaluation process requires a lot of data such as credit card history, payment history, the amount owed, length of credit history and so on. The business can fall down if anything goes wrong with the credit evaluation process. 
The AI-enabled credit evaluation software can reduce those risks and help with decision making as well. It can also go through the bulky data accurately in no time that can enhance the credit evaluation process. 
The software can evaluate the credit score with the help of historic and forecast data. So that it can be beneficial for everyone ew customers, students, and startup founders as well as the people with credit history. For finance organizations, it can help them obtain more and more customers with almost no risk. And when it comes to the customer, it can be beneficial for them to get unbiased access to credit services. 

#4. Risk Management

Identity theft, credit risk, fraud risk, underwriting risk are the nightmares for every finance organization out there. AI-enabled finance software can detect those risks with the usage of advanced analytics and predictive analytics. It can identify the specific violated patterns that can help to reduce them.
AI-enabled software will notice oddities in purchase behavior and restrict the card before any further damage happens. The finance software can also signify the probability of the consumer defaulting and preclude the credit from being extended, thus saving the bank from a bad loan. The basic working of AI can enhance early warning systems for credit risk management, stress testing for market and economic risk management and data quality when it comes to fraud risk management.

#5. Fraud Detection 

According to Crowe, the finance industry faces around $5 trillion of loss from the global economy each year, and that number continues to rise. Traditional fraud detection systems were not much help. That is where ML came into the picture. 
The ML integrated modern fraud detection system updates itself from previous fraud trends and prevents them in future transactions. Machine learning integrated software in the finance industry efficiently eases the data analysis work helping fraud analysts to provide more accurate results.

#6. Personalized Banking ‌

Long-term relationships and customer loyalty increase the customer satisfaction rate. Customers are ready to trust and even share personal data if the bank and finance organization provides personalized services.
The banks and finance organizations are using AI/ML integrated web services to fulfill every demand of the customers. The AI-enabled chatbots, predictive analytic systems are a great help to the finance industry for the following domains.
  • Enhanced communication with the users
  • Personalized mobile banking
  • Accurate advising to the users about their spending and savings
  • Fraud detection and prevention
  • Personalized promotional message automation

#7. Debt Management 

The traditional debt collection system used to be complicated, unproductive and messy. AI and ML are working as a boon for debt management and collection. The modern AI /Ml software have made these processes effective, alongside maintaining and enhancing good customer relations. AI integrated finance software are helping data collection providing some of the listed services such as:
  • Improved repayment rates using stats and data 
  • usage of behavioral science for Personalized debt collection methods for different customers
  • Payment automation methods
  • Enhanced A/B testing employing AI

How to Select the Best Partner to Develop AI/ML Solutions for Your Financial Service

Finance organizations should clearly identify their goals before employing any AI-enabled business process. AI/ ML can serve you with various organizational processes than just data processing and mining. So, before choosing your Partner to Develop AI/ML Solutions, check if the company understands your end goal perfectly or not. And the company should be able to develop a perfect solution according to your end goal and requirements. You can drop your inquiries at Hyperlink Infosystem, as we have an experienced team to build a perfectly fit AI-enabled solution for your finance organization.

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Harnil Oza is a CEO of HData Systems - Data Science Company & Hyperlink InfoSystem a top mobile app development company in Canada, USA, UK, and India having a team of best app developers who deliver best mobile solutions mainly on Android and iOS platform and also listed as one of the top app development companies by leading research platform.

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