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How is Artificial Intelligence transforming the Lending Sector?

Ashish M. Shaji

| Updated: Oct 20, 2020 | Category: Digital Lending

Artificial Intelligence

Artificial Intelligence (AI) has been a revolution in technologies. The adoption of AI leads to great revolutions across industries but the most useful one has been AI in lending. In this article we shall look how AI is transforming this sector.

How does AI work?

There are two types of AI:

Supervised and Unsupervised.

  • In case of supervised AIs, humans create rules and software sorts data depending upon the set rules. The AI learns the underwriting rules of lender. AI can examine numerous applications in short duration.
  • In case of unsupervised AIs, humans don’t create rules in the beginning instead a data scientist feeds a massive amount of data to it and lets AI identify patterns across millions of variables.

Digital footprint Analysis and Risk Reduction with Artificial Intelligence (AI)

With AI, information about an applicant’s digital behaviour can be known including the people’s profiles on social media that they frequently associate with. Earlier such processes were too time consuming and labour intensive. It was challenging for a loan underwriter to manually compile and assess all data points.

With AI in the loan origination system of banks, it helps in reducing the likelihood of human errors in processing of a loan application or overlooking important factors in if a borrower would default on a loan. AI has also helped in the bank’s loan management system to know the patterns of behaviour that tells if a customer is close to declaring bankruptcy or if they would completely default on the debt. This ability of knowing beforehand will stem costly losses and preserve credit availability for borrowers who will be full-fledged economic participants.

In which areas have Artificial Intelligence benefited the lending sector?

The following are the areas where AI has made it more convenient in the lending sector:

Artificial Intelligence
  • Preliminary Screening

By screening loan applications based on different credit models, helps in reducing the huge amount of clerical errors that makes loan management challenging. As the operational tasks are taken over by the AI, the company saves time which allows teams to concentrate on more essential aspects of the lending process.

  • Credit Scoring

Lending institutions relied on single credit score in order to assess the repayment abilities of the loan applicants. However, with the introduction of AI, alternative credit scoring methods analyzes through a smartphone and gives an insight into consumer behaviour and their spending patterns. Due to this feature, the transaction time to process loans has reduced significantly.

  • Fraud Detection

Loan stacking is very common in the lending business among all cyber crimes[1]. (Loan stacking means taking multiple loans from multiple lenders). With AI, suspicious activities and unusual pattern of behaviour of loan applicants can be identified which helps in taking preventive action.

  • Due Diligence costs

AI can comprehend billions of data in seconds while updating the data as well. This allows lending institutions to reduce their expenditure on due diligence. Lending institutions would otherwise require sweeping through various records to arrive at a decision if he or she is eligible for the loan and if they have the capacity of repaying of loan.

  • Know Your Customer (KYC)

AI can assist lending institutions to better know their clients. By assessing individual customer data, customer behaviour patterns can be known and the loans can be tailored to meet the requirements of customers thereby raising profitability.

 What has been some of the pressing issues with Artificial Intelligence in lending sector that needs to be addressed?

There certainly have been some concerns with AI in lending that requires immediate attention:

  • AI is expensive

As AI is enabled with limitless capabilities, it can be highly expensive for companies or institutions that are just coming through the ranks. The expenses of AI are high considering that it needs constant updates and may require hardware replacements frequently. In case of a severe system crash, it may cause hardships to the company as restoring the system would be costly and time consuming.

  • Strips people of jobs

Another cause of worry for many is that someday AI would completely strip people of their jobs. Due to the efficiency of AIs, some companies have reduced the number of people they employ thereby cutting costs. This is a significantly worrying development as more and more tasks are being taken up by AI.

  • Dehumanization

Sometimes there are tasks that require human touch to it. In some instances AI can take bad judgements in approving or rejection of loans. There is always a requirement of human intervention especially in situations where rational thinking and morality is required.

The Future of Artificial Intelligence in Lending

As far as the future of AI is concerned, it is expected to undertake many manual tasks like reviewing forms and data input thereby allowing the team to concentrate on other important tasks.

We may witness faster response time, more granular product offerings, improved customer service and globalisation of offerings and sources of lending. Moreover, larger loans that required more intensive reviews would be completed in just a matter of few hours and not weeks or months.

There could be time where there are complex AI stimulation models that incorporate many technologies. The future of AI in lending can help deserving people secure loans like never before therefore its future is vast in the lending sector.

Conclusion


Artificial Intelligence in Lending sector has definitely streamlined the lending process, benefiting both customers as well as lending institutions. Now the decision to grant a loan is taken more efficiently and proficiently.

Read our article:How to use Artificial Intelligence in Lending

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Ashish M. Shaji

Ashish M. Shaji has done his graduation in law (BA. LLB) from CCS University. He has keen interests in doing extensive research and writing on legal subjects especially on criminal and corporate law. He is a creative thinker and has a great interest in exploring legal subjects.

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