Machine Learning: A Smarter Way to Microfinance Collection

Machine Learning: Revolutionizing the Microfinance Industry

Introduction 

Did you know that using artificial intelligence can reduce losses by 23% in a financial business? That is the power that machine learning and AI offer to the Microfinance industry.

Machine learning combined with artificial intelligence can go through a borrower’s digital interactions to point out variables and indicate an impending financial crisis in advance. A decrease in online transactions or an absence of salary records in the last few months can play a significant role in effectively assessing possible risks. It can be more of an assistance than a static credit score.

Machine learning can predict chances of default by studying customer behavioral patterns and records. It can help Microfinance companies take timely measures against defaulters to protect their cash flow liquidity and take informed and mutually beneficial financial decisions.

“The above graph shows the 14 most important features of the random forest model using machine learning in the field of credit scoring.”

Machine learning has made the microfinance industry smarter and more effective. Here are some of the positive changes that came with using it:

• Better Credit Assessment – Implementation of AI and machine learning in the microfinance sector has made credit assessment a faster, easier and more efficient process. AI also checks other potential factors, including behavioral patterns of the borrower, utility bill payments and social media behavior.

• Risk Analysis- Machine learning and AI conducting research are often essential for a microfinance company to run a risk analysis. The Implementation of machine learning algorithms ensures risk cases are identified at the early stages. Therefore, companies can take the required measures beforehand.

• Better Customer Experience – Customer satisfaction is one of the essential areas in the microfinance sector. A fast and effortless lending process increases the chances of a microfinance company having recurring and new happy customers daily. Machine learning does this job more efficiently and makes the process error-free.

• Automation – Today leading financial firms globally use machine learning algorithms or AI to automate their lending process. Loan processes like loan origination, servicing and collection use automation by AI. It helps save time and cost, as opposed to using the traditional methods or workforce.

• Helps battle fraud – One of the biggest challenges of the microfinance industry is frauds, resulting in huge losses. In 2019, there were 270,000 cases of credit card fraud. AI gives microfinance companies robust fraud detection and prevention systems. Companies can prevent financial frauds like money laundering by using AI and machine learning. AI also helps in reducing the investigation costs by up to 20%.

Conclusion

Despite the many positive effects of AI and machine learning in the microfinance industry, it is still in its beginning stages. However, it is reshaping the industry for good. Implementing automation in the processes saves both time and labor.

Another added benefit of using machine learning is better security. Since AI can assess both traditional and non-traditional data of the users, it significantly decreases the chances of fraud by the debtors. It is not just a boon for the lenders but also for the borrowers.