How is Big Data Driving the Lending Industry?

In my last blog, I discussed how non-bank lenders are leveraging technology to offer innovative solutions to consumers, making banks more and more irrelevant. Innovation in Financial Services industry...

Snehal Fulzele 11th May 2015

In my last blog, I discussed how non-bank lenders are leveraging technology to offer innovative solutions to consumers, making banks more and more irrelevant. Innovation in Financial Services industry is happening outside banks, especially in the non-bank lending sector.

At Cloud Lending Solutions, we are developing the technology infrastructure to enable this innovation. We are proud to have built technology that enables unique lending models. We have launched marketplace and mCommerce/eCommerce lending platforms for variety of asset types including consumer, small business, real estate, leasing, purchase finance and auto across 18 countries.

big-data-lendingTraditional credit scoring models are giving way to innovative non-traditional credit models. Over 200 million Americans are assessed for their credit worthiness based on FICO score. However, things are beginning to change. Increasingly, non-bank lenders are looking beyond FICO score and are using big data from social networks, mobile, bank transactions and behavioral data as part of their credit risk analysis. Lenddo, a US based company gives a social-score based on behavioral data by scanning through different social networks such as Twitter, Facebook and LinkedIn along with mobile data. It has seen successful adoption in emerging markets. Cloud Lending’s origination module is integrated with Lenddo services that our customers can use in their credit risk model.

Alternative finance companies are adopting big data from social, mobile and online sources in their core processes and are transforming the way lenders operate.

Demand Generation: Traditionally, banks have relied on physical networks and local outreach to generate business. However, customer acquisition cost is high and is filled with negative selection bias. In order to gain customers faster and in inexpensive way, lenders are beginning to rely on social and online media. It won’t be long before you see loan applications floating around your social network.

Underwriting: Underwriting has been a manual and time consuming process. However, lenders are now using powerful algorithms that can analyze data from social media, mobile and bank transactions to come up with improved underwriting models. These models are easy to automate resulting in quick decisioning and minimize credit risk. For example, Cloud Lending has an in-built Yodlee integration to pull bank transactions, and can also verify a borrower’s identification within seconds using ID Checker’s API.

Servicing: An upcoming lender uses social media and peer connections to assess the creditworthiness of borrower. It is not far-fetched to think that during collections, they might enforce peer pressure through social media to collect on defaults. Think of it as the digitized form of a microfinance group lending model.

We see big data having a phenomenal impact on lending – resulting in better loan books as we build financial inclusion of underserved and unserved consumers.

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