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With increased competition and the need for providing better services to customers, businesses are always under a pressure of constant innovation. They require to adopt the latest technologies in order to combat changes the market is producing.

Data has always been an extensive part of the business processes. Like in order to get a consumer onboard, a significant amount of data is asked by the person. This might include personal details, work information, etc. However, when it comes to lending and payment sector, the requirement of customer data increases substantially. Several aspects related to income, past credits, transactions are evaluated before the loan is approved. Over the course, businesses started monitoring and evaluating the data to back certain decisions and make lending less risky. Today, data has become hugely vital for today’s progressive lending businesses.

Data analysis has become crucial in decision-making processes in the lending sector. Technologies like AI and ML help to interpret user data, hence, streamlining the lending process from top to bottom. Businesses can now analyze a customer’s financial portfolio, check creditworthiness, and make credit-based decisions.

Revamp credit risk modeling

In simple terms, credit risk modeling refers to the evaluation of potential risk or loss due to the failure of a borrower in loan repayment. It provides lenders with deeper insights into customer behavior by using various analytical techniques and advanced technologies. Let’s see how data is becoming the pivot point for analyzing and interpreting customers.

Risk assessment

According to a survey, more than 45% of bankers believed that data analytics is useful in preventing both fraud and non-repayment. Data analytics measures credit risk involved in granting a loan to a customer using advanced analytics models. All the data including income statements, past taken loans, repayment information, etc. are combined to bring out a number that decides whether the borrower is eligible. It helps lenders to determine whether the borrower is capable of repaying the loan in the said time.  

Although credit scoring firms are doing this since years, the time has evidently changed now. Businesses require more accurate and personalized results. With rule-based credit scoring methods, lenders can check the creditworthiness of the borrower based on their own goals and requirements. Akeo Lending is a customized lending solution that utilizes data to offer automated credit checks based on your business goals.

Read more on what is rule-based credit scoring and what benefits does it offer over conventional credit scoring model?

Fraud management and prevention

Credit fraud has become a serious concern to lenders and banks. Digitalization with the help of data has paved the way to streamline the lending process and significantly reduce the chances of frauds. A variety of data is evaluated to derive reports that reveal the authenticity of the customer.  The intelligent systems acutely analyze the user’s historical data to ascertain their past loan repayment patterns.

In today’s world, lending businesses also consider user’s social media accounts to generate data insights. Such data greatly helps lenders to reduce the chances of risk leading to fraud prevention. Moreover, it substantially broadens the market, creating new customers and revenue streams.

Customer Analysis

Lending businesses are constantly at risk of losing customers (borrowers) and to retain them, they must offer better services and personalized experience. The success of these services depends on the right action on the right customer. As businesses are becoming more data-driven, they are gaining every sort of data about consumers to gain insights and effectively segment their clients. Data analysis significantly helps to identify payment patterns, financial behavior, and which services customers are more likely to choose.

For instance, a borrower with a superior credit score and steady income can be offered with a low-interest loan. In contrast, if the borrower has a poor credit score, the loan offered to him might be of high-interest and against sufficient collateral.  

Data Analytics and Lending

The world of Fintech and lending is constantly evolving. With more and more digital lending platforms, accuracy and predictability have become key drivers to success. Data has become vital for lending businesses to shift from the noise and get the right information based on facts and statistical numbers. Adopting data analytics and imbuing it into credit risk modeling and lending workflows is the key elements of surviving and prevailing in this rapidly changing environment.