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Traditional Credit models have a certain predefined metrics that need to be taken into account when determining the creditworthiness of a client. These same metrics are used to calculate the Credit score to determine the eligibility for a certain kind of loan (mortgage, car loan etc.). Before taking a look at these metrics it should be noted that this model has certain limitations. It does not show the bigger picture for people who are apparently not part of the system – For example – People who have always done cash transactions, a student with a limited credit history or an immigrant from another country where is no such credit system.

The traditional model takes the following factors into account. Two of the major credit companies (here in North America) that base your credit score on these metrics are Equifax & Transunion. Every individual is given a score in the range of 300-900.

  • Payment History (35%) – Biggest percentage of your credit score is based on how your pay your bills. Determines your spending practice.
  • Debt Burden (30%) – Your total debt burden determines if you are able to afford any more credit & more importantly if you will be able to make payments on it. A higher credit utilization would not only lower your score but lower the chance of getting any more credit.
  • Length of Credit history (15%) – Basically the longer you have had a credit file with these credit bureaus the better it is. People with skinny or no credit history are unlikely to receive any credit from the mainstream financial institutions
  • Types of credit (10%) – Varied credit like mortgage, student loan & car loan etc. is considered better than being heavily leveraged in any one trade like a huge credit card loan only.
  • Requests of new credit (10%) – And finally how frequently you are applying to receive new credit determines whether you are in need of one or you are a habitual credit seeker.

As evident from the metrics, the model is pretty biased in favor of people who either already have an established good credit or the ones who don’t need one. Over the past decade or so, however, the advancement in technology has brought inclusiveness to the so called outcasts to this credit system. It has also helped creditors get the full picture of the creditworthiness of clients with the availability of massive amounts of data being created.

The emergence of game-changing technologies like Big Data, RegTech (personal data control given to the consumer), AI (Machine Learning & Deep Learning), Digital IDs (Biometrics, facial recognition) & the FinTech startup boom (integration of finance with technology) is reshaping the global ecosystem with the financial sector seeing the biggest digital disruption in this regard. The FinTech companies have brought great innovation to this field with alternative forms of lending (P2P, microlending), accessibility & customer-centric approach.

With the availability of cutting-edge technologies, valuable data insights & innovative products these companies can provide customized financial services like consumer credit at the touch of a finger-tip to their clientele’. The following infographic details how the future of consumer credit is shaping up with a combination of all the factors discussed above.

How Technology is Shaping the Future of Consumer Credit

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