Case Study

Loan Workflow Automation

for one of the largest Eastern European Banks


Case Study

Loan Workflow Automation

for one of the largest Eastern European Banks

Our Client

Our Client is one of the TOP-5 Banks in Eastern Europe. The Bank works with corporate clients and financial organizations, including government agencies and enterprises. The key activities also include fundraising and lending to the population.

Challenges
  • Slow customer service 

    Slow decision-making process restrains the process of new customers engagement

  • Slow time-to-market

    Lagging behind the competitors in terms of new services launch

  • A high number of manual operations

    Increase the time and cost of business-processes, lead to additional errors, downtime and inefficient use of resources within the organization 

  • Disparate IT-systems

    Not having a single information space with a unified user interface slows down applications processing and increases the error rate

  • Lack of transparency and performance management tools  

    No ways to properly measure and manage the actual process metrics

  • Paper-based document management

    Increases the additional OpEx and poses significant security risks

There is an urgent need to upgrade the existing Microsoft SharePoint solution:
  • The system does not contain the key functionality to reduce labor costs
  • The system is not expandable and can't handle heavy workloads
  • The system cannot be used for loan automation and cannot be integrated with key automated bank systems
Objectives
  • To reduce Loan Processing Time for legal entities

  • To reduce the volume of overdue debt by segment
  • To increase the productivity of your customer support team and point of sales

  • To reduce time-to-market (time for new products to enter the market)

  • To reduce document storage cost and paper document destruction cost

To create a targeted solution, our experts chose Pega Platform 7.3.1., a BPM platform for creating enterprise-class applications and continuous adaptation to business requirements using low-code tools.
Project Timeline
MVP
September 2017 – March 2018

Processes:

"Decision of the authorized body" (RUO)

"Decision of the authorized person" (RULE)

First Stage
March 2018 – December 2018

Processes:

“Preparation of credit and security documentation”

“Collateral Examination”

Second Stage 
January 2019 – July 2019

Processes:

“Loan issuance”

“Loan support services”

Third stage
August 2019 – January 2020

Processes:

“Loan monitoring”

“Loan closure”

All processes were performed in the following order: Analysis, Design, Implementation, Testing, Integration.
Implemented Integrations
  • Electronic document storage system
  • Automated contract registration and cash handling system
  • CRM system for storing customer information and records of customer interactions
  • Remote Banking System (E-banking system)
  • Credit risk management system
  • Notifications module

Results

  • Faster decision making
    Reduced Loan Processing Time by
  • On-Time Product Launch
    Accelerated time-to-market by
  • Reduced the risks
    Reduction of overdue loans by
  • Increased Productivity
    Reduced the time of document and application management by
  • Reduced the cost of document management
    Reduced document storage and records destruction costs by
Benefits
  • A unified workspace with intuitive and user-friendly interface
  • Flexible business rules and directories configuration without the need for further releases and improvements 
  • Automated Document Production & Generation
  • Employee Workload Optimization
  • Quick search of applications on the key parameters
  • Regulatory Deadlines Monitoring
  • Notification System (E-mails, chats, subscription to the colleagues’ applications)
  • Creating and Managing Electronic Documents in Document Builder
  • Automation of the document control and management processes
  • “Tree view” attributes - structured data entry and hierarchical data structure
  • Simplification of daily routine operations for working with tabular data
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