Today’s customer expects fast, seamless and hassle-free access to loan services at a time, place and channel of their choice. But unfortunately, many lending firms struggle to earn customer loyalty, as they face challenges in meeting their customer expectations. Lending firms and FinTech’s are constantly trying to implement tools and processes to keep their customers happy. But major issues like customer buying habits, customer acquisition, fraud detection, application screening, credit and collections has always been an area of concern. Here, Predictive Analytics can be a big relief which can solve all these issues through data-driven decisions.Predictive analytics model will help lenders make meaningful future decisions by analysing and modelling data to gather insights that can be used to stand out from the competition.
What is Predictive Analytics?
Predictive analytics (Predictive modelling) is a subset of business intelligence that basically analyse past behaviours to predict future. It is the art and science of analysing and modelling data to gather insights that can be used to make meaningful decisions. It includes mathematical techniques, machine learning techniques and processes that are applied to historical data, identify trends and make a best valuation of what will happen in the future.
How can it help the Lenders?
The consumer lending business is centred on the notion of managing the risk of borrower default. Credit scoring systems and predictive models attempt to identify the chances of uncertainty and provide guidance for the identification, measurement and monitoring of risk. It gives the lenders a clear picture of whom to trust and who had defaulted the payments in the past. It will help lenders to make faster and more accurate credit decisions.
Areas addressed by Predictive Analytics
- Fraud detection: By considering information beyond the individual’s credit report, a more accurate estimation of a borrower’s default risk can be calculated.
- Cost efficiency: Lending institutions can reduce operational cost and the loan application life cycle can be completed with fewer individuals performing fewer steps.
- Faster lending decision: Predictive models make consumer lending decisions easier and improve the overall quality of the borrower portfolio. It brings consistency and predictability in the loan-disbursement process.
- Improving Operations: Predictive model helps to forecast inventory and manage resources.
- Customer buying habits: With predictive analytics, lending firms can rapidly segregate various customer segments. It helps to identify, target and retain the most profitable customers.
- Customer acquisition: Reach the right customer with the right product.
“LENDING BUSINESS WITH HUGE AMOUNTS OF DATA AND MONEY AT STAKE, HAS LONG EMBRACED PREDICTIVE ANALYTICS TO DETECT AND REDUCE FRAUD, MEASURE CREDIT RISK, MAXIMIZE CROSS-SELL/UP-SELL OPPORTUNITIES AND RETAIN VALUABLE CUSTOMERS.”
The way ahead
Predictive analytics can play a pivotal role in driving efficiency in the lending industry. With the huge growth of data, firms can gain a strategic advantage by using predictive insights to make improved lending decisions. More and more firms start looking at predictive analytics models as the ability to see even a tiny piece of the future can lead to happier customers, improved efficiency and productivity, and more successful business decisions
How can Insight Consultants help you?
Insight Consultants specializes in digitizing the lending ecosystem. From general to specialized, prime to sub-prime, we have helped firms operating across the lending landscape reap the benefits of digitization. We provide 360-degree solutions starting with business consulting, solution creation, identify insights and generate predictive models to take advantage of all the data collected by lending firms. So, if you are looking for ways to harness the power of predictive models or would just like to know more, you can request a FREE CONSULTATION by filling the form OR Contact Us
