Simplified lending processes for entrepreneurs

Damu Fund together with the First Credit Bureau (PKB) intend to start automating the credit rating for partners in implementing support programs: second-tier banks, microfinance organizations and leasing companies.   

Recall that in 2019 FRP Damu JSC and PKB launched a joint project of automated credit rating of entrepreneurs, which allows optimizing the process of obtaining SME loans and improving the quality of risk management. 

Calculation of the final, forecast rating, which determines the likelihood of a default and a rating category (rating) equivalent to the international scale.  In order to improve CMS under the program of partial guarantee of loans of second-tier banks, a scoring model was implemented for the guarantee instrument for projects of less than 20 million tenge for private entrepreneurs (not including start-up). “The introduction of risk assessment and validation automation tools has reduced the time required to draw up a risk management report on a project by three times. Today we set even more ambitious goals and start implementing a project to automate a credit rating for partners implementing support programs: second-tier banks microfinance organizations and leasing companies. This will qualitatively improve the service of the fund as an operator and optimize lending processes, "said Gaukhar Buribaeva, chairman of the board of Damu Entrepreneurship Development Fund JSC.  

According to the Director General of the First Credit Bureau Ruslan Omarov, the company provides market participants with specialized credit modules and conveyors, taking into account their specifics (MFIs, pawnshops, credit partnerships).  “The MFI loan module now makes it possible to correctly account for credit operations (portfolio), providing deferrals, conducting mass operations, reporting to the regulator, automated uploading to the credit bureau and other options. All business processes are customized to customers and take into account the specifics of organizations' activities,” he explained.  The design bureau noted that prior to automation, a lot of analytical work is being done to develop models - a lot of expertise in predictive analytics. Models in the design bureau are developed using machine learning technology for each segment and product. This approach is of the highest quality compared to providing one type of credit bureau scoring. Today in the design bureau there are more than 20 different scoring cards and more than 400 consumers - credit organizations.


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