How AI Is Transforming Lending And Loan Management

AI like blockchain is a revolution in technologies. It makes work of different industries easier and more effective. The development of AI leads to great revolutions in all industries but the most useful is AI in lending and loan management.

Frost & Sullivan consulting company specialists are sure that the market volume of AI-technologies will grow by 31% annually. It is forecasted that by 2022 this figure will amount to $52.5 billion, which is four times more than in 2017. Gartner experts believe that during the next few years income from AI will be 3 times bigger than now annually.

Automated systems cost banks 50–90% less than the work of hired employees. AI increases the quality and speed of service, in particular when analyzing the creditworthiness of the client.

Advantages of AI for the banking sector

The most useful and effective sphere where artificial intelligence solutions are using is customer service. These are chat-bots, round-the-clock support of users, analysis of their transactions, and loans.

Advantages of using AI-systems in the financial sphere:

  1. Routine processes are automated;
  2. The speed of service increases;
  3. Costs for the solution of standard problems decrease;
  4. Accuracy of processing of the big volumes of the data raises.

Majority banks use new technologies in their activities and introduce AI in all areas of business. Banks automate the work of the contact center for corporate clients. Robots answer clients’ questions thanks to which the speed of customer service has increased by 50%.

This does not mean that AI will take away a person’s work: bots are created to perform routine and uniform work, while bank employees will have more complex and creative tasks.

Given how AI is being introduced into the banking industry, the loan industry has taken on a separate role in the development of artificial intelligence and big data. For example, working with big data is used for credit analytics — scoring.

AI and Scoring

Credit scoring is an assessment of how solvent a client is and seeks to repay the debt. Conclusions about this are based on a lot of data: total income, credit history, transaction analysis, and even length of service.

In fact, scoring is a mathematical model based on statistical methods and taking into account a large amount of information. Artificial intelligence and Big Data help to cope with this task quickly and efficiently.

Uplift models

AI helps to assess debts and carry out a credit analysis of clients: now the solutions are being implemented in the work of different banks. For example, europian banks were one of the first banks to launch the machine learning technology to analyze retail delinquency.

Bank experts are building self-learning uplift models that predict the reaction of clients to recoveries. This allows banks to optimize the process and think over how best to communicate with individual borrowers. Uplift-models identify customers who are useless to call and remind about payments, form a list of those who make the payment, and those who need to be reminded.

Loans are issued by AI

Banks management announced plans to issue most loans to individuals based on AI solutions. With the help of the AI-system, the decision on lending is made within a minute.

Parallel testing is conducted with the participation of people who also make decisions on granting loans. This is necessary to assess how effectively the AI works. Soon all the questions on crediting will pass to the area of responsibility of AI.

The results of the work of AI are satisfactory: the level of overdue loans has decreased (compared to the period when only a person was responsible for the decision).

Smart scoring systems

Europian banks create their own innovative scoring systems. They are characterized by its extremely high speed of operation: within seconds, the system analyses 10,000 customer characteristics. Experts claim that the model was created for full automation of credit processes. It is also able to increase the profit on loans in general.

Powerful characteristic of the system is that for the analysis it uses the information not only of credit histories of the person, but also the behavioral data about him: how long he fills in the questionnaire, thinks out answers, how much time separate actions occupy. It helps to identify fraudulent schemes at the initial stages.

Belarusian startup GiniMachine created a similar system. They have created a system that provides a solution for credit scoring based on machine learning. It itself creates analytical models, calculates credit scores, and analyzes risks for specific borrowers. This algorithm can save weeks of human labor. The GiniMachine system is also capable of solving other business tasks related to forecasting.


Artificial Intelligence is a rapidly developing technological tool that influences many processes. Business, government representatives, and end-users of goods and services are benefiting from the implementation of AI in different industries. However, in the pursuit of high profits and market leadership, we must not forget that AI-products and solutions should work for the benefit of society.

Artificial intelligence in credit scoring can save time and total costs of the institution. Germany Aareal Bank was helped by the AI to increase own profit. Thus, now the decisions to grant a loan are made more efficiently, and the bank does not lose money on unscrupulous clients.

AI significantly increase profit in any sphere. If your business has not enough money for developing your own AI, you can take personal online loans and create your own system for increasing profit.

AI technology for lending to both individuals and businesses is becoming more popular in large financial institutions. Active development of this area is taking place which increases the total profit of the loan sphere.

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Digital Anarchist

Digital Anarchist

Blogger, writer, enthusiast from Ukraine. Everything I publish is worth your time.

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