Home Technology AI Big Data Disrupts Credit Applications As We Know Them

Big Data Disrupts Credit Applications As We Know Them

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Convergence is the latest buzzword in finance, and thanks to the relationship between payments and loans, we are now seeing the emerging point of sale (POS) lending. Just a few short years ago, POS lending would have been unheard of, as there was just not enough data to make a decision of that nature fast enough. We simply had a relationship with the bank and a FICO score to look back on, but sound financial decision-making needs more than that. This is where big data comes in. It bridges the gap between the known and unknown to provide a holistic picture of an individual’s financial position that stretches beyond the FICO score.

Banks Are No Longer The Only Option 

While banks have traditionally been the major source of finance for individuals, big data bridges the gap to other institutions that want to get in on the action. This is because big data scrapes together all the information, and with the help of artificial intelligence (AI) and machine learning (ML), works through the data to provide a clearer picture of the borrower. This allows companies such as mobile networks to gain sufficient data to extend credit to the customers – all without the transaction history from the banks. Mobile carriers might have a relationship with the credit bureaus, however, which assists in the decision-making process.

More Than A Credit Score 

Big data allows credit providers to have a big picture idea of a customer, which will afford students who have just graduated and started a job with the opportunity to apply for a mortgage. It will also provide those who are wishing to rebuild their score with access to the right providers. Instances, where this would work, are where you would apply for a credit card with a low balance or a secured card, or when you consolidate your loans. While derogatory information such as missed payments or legal action on a credit profile does point to obvious risk for lenders, there are instances where a low score does not necessarily point to risky or reckless financial behavior. These include a lack of financial products or early payment of loans.

Fast, Fraud-Free Applications

Perhaps one of the biggest wins for consumers when it comes to the role of big data in credit applications is the speed. Applications make use of information already available on the credit provider’s system, along with other information available on the web. This requires very little input from the consumer, and virtually no paperwork. Applications can take place within a day, with the funds disbursed on the day of approval. It’s not unusual to apply one day and receive the funds by the end of the business day. The accuracy of big data and the analysis through AI also ensures that these applications are done securely, which reduces the amount of fraud.

For banks, big data can prove disruptive as the traditional way of assessing financial eligibility changes. This provides easier access for a large portion of consumers who may previously have been overlooked.

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