Showing posts with label # Risk Intelligence. Show all posts
Showing posts with label # Risk Intelligence. Show all posts

Wednesday, November 6, 2019

Enhancing Credit Risk Management

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It is common knowledge that large volumes of data are being constantly generated and a good portion of this can be used to better understand a potential borrower. This profusion of data has only provided greater depth and reach to lenders. The emergence of alternative data as a catalyst in expanding credit delivery and financial inclusion is unmistakable. It not only expands the scorable population but also deepens the understanding of their payment behavior.

The popular saying “the only thing that is constant is change” applies to the way lenders use technology and scoring solutions to understand the creditworthiness of applicants. Credit Risk Management has come a long way from the days when banks used one credit score cut off to decision loan applications. Risk managers now have a plethora of solution options to craft a credit policy that hits the right balance between risk and reward.

Traditional vs. Alternative Data Defined

Traditional data typically refers to data that credit bureaus maintain on their files. This includes data from loan applications, credit lines, loan repayment history, credit inquiries, and public information like bankruptcies. Traditional data is FCRA compliant and the acid test is that it must be verifiable and disputable by the customer.

Industry research has shown that scoring solutions that use traditional data cannot score a significant section of the population. According to the Consumer Financial Protection Bureau (CFPB), these ‘credit invisibles’ number over 45 million people1. It further points out that although this segment of the population may not have a regular loan payment track record, they may still be paying their other bills regularly. And for this reason, it is very important to track this payment history – e.g. utility payments – to estimate their credit risk.

Definitions of alternative data may vary, depending on where you look. But in a broad sense, it pertains to data that includes, but is not limited to rent payments, mobile phone payments, cable TV payments as well as bank account information, such as deposits, withdrawals or transfers.

The Pros and Cons of Alternative Data

While alternative data has a very important role in financial inclusion, it also has other important benefits. In addition to improving the assessment of the risk of the customer, it can provide timely information to lenders on activities that may not be reflected on bureau data. Further, it enables lenders to provide enhanced customer experience. For example, when they share an online bank account, the loan application processing may be faster.

Like traditional data, alternative data is susceptible to inaccuracies. Consumers may not be able to readily review and correct alternative data although the standards governing it are constantly changing and evolving to meet customer and regulatory expectations.

 

 1 Kreiswirth, Brian. “Using alternative data to evaluate creditworthiness.” 2017. //www.consumerfinance.gov/about-us/blog/using-alternative-data-evaluate-creditworthiness/

## Risk Intelligence #CreditRiskManagement   #AlternativeData   #Bank  #CreditCard

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