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Case Study

Robotization of Credit Risk Assessment for one of the largest Eastern European Banks


Case Study

Robotization of Credit Risk Assessment for one of the largest Eastern European Banks

Our Client

Our Client is one of the TOP 10 banks in Eastern Europe. The Bank provides a wide range of banking, financial, investment products and services to corporate and private clients, financial institutions, institutional and private investors.

Challenges

  • A high number of manual operations

  • Long Processing Time

  • Document Management Challenges 

  • High request queue time

One of the TOP 10 banks in Eastern Europe didn’t automate one of the key stages of corporate lending process - credit risk assessment.
  • At least five bank specialists were involved in the collection and preparation of registry monitoring; reserve adequacy assessments and the process of making loan decisions, while a significant number of routine operations were performed manually.
  • The processing time of funding applications increased and eventually ceased to meet customers’ expectations and market requirements.
  • A large number of manual routine operations, document management challenges didn’t allow the Bank to speed up loan processing.
  • While the number of customers increased, the staff remained the same, which led to an increase in the request queue. In order to process all applications and make loan decisions in a timely manner, a two-fold increase in staff was required, that did not conform with the Bank’s strategy and current service level requirements.
Objectives
To overcome the challenges encountered, the Client decided to automate the credit risk assessment process. The project objectives were:
  • the standardization of data collection and preparation,
  • the development of universal guidelines and document templates,
  • as well as human-robot communication channels and terms of cooperation.
In addition, it was necessary to create a tool for analyzing robots’ performance and to train the Client's team to work with robots.
Project Implementation
Our team analyzed all operations performed during the credit risk assessment process and developed a solution that allowed the Bank to automate the ones that don’t require human intervention.
1

At the initial stage of the project, our team, together with the customer's representatives, standardized the entire business process. At the same time, the variety of incoming loan requests was reduced and brought to a single format.

2

UiPath was chosen as the most appropriate RPA vendor, which provides an intelligent and multifunctional development environment for automation in any industry. The UiPath platform interacts with other IT systems through user interface (UI), simulating the end user, unlike traditional computer programs that work through the API (Application Programming Interface) or the integration bus (Middleware).

3
The operations performed during the loan application review process were grouped as follows:
  • Data Collection from various sources, electronic documents and information systems
  • Collected Data Aggregation and Analysis
  • Generation of credit risk assessment documents based on templates
4

Next, scenarios were developed for robots to collect required data and prepare Bank's internal documents required when reviewing loan applications by credit specialists.

Results

  • 50%
    The cost of employees 
    decreased by 50%
    Robotization of credit risk assessment process allowed the Bank to avoid staff expansion, achieving significant savings. The Bank was able to plan staff capacity given the number of incoming customers’ requests and seasonality.
  • 5 minutes
    Loan processing does not
    exceed 5 minutes
    Another result of robotization is faster loan processing. Previously, the process could take an hour and a half, depending on the complexity of the loan request.
  • 8 months
    The payback period
    was 8 months
    The payback period of the customer's investment in the project was 8 months from the moment the system was put into commercial operation. Today it is used to process all loan applications received from legal entities – clients of the Bank.
As a result, our Team automated the following processes:
  • Search and collection of required formalized data in electronic documents of the Bank's information systems
  • Loan Review Document generation based on the obtained data

The analysis of the Bank's interaction with legal entities revealed that e-mail is the most convenient form of submitting an application. Now a client just need to send a loan application to a specific e-mail address. Further processing of the request is done automatically by a robot.

Our Team also created rules for robots that determine the execution order of requests from the queue. For this purpose, they identified key features, according to which each request is automatically assigned a certain priority.

Along with this, our experts developed and implemented a robot monitoring system, that allowed the Bank to analyze robot errors and glitches.

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