Technology

Case: RPA implementation in a bank

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Client

The client is one of the leading banks in Ukraine with a network of 300 branches across the country. The Bank provides a full range of financial services for both individuals and legal entities. The bank has a client base of over 800,000+ customers.

Situation Description

The company found serious problems due to a lot of manual work, especially in document processing. This caused numerous errors, delays and customer complaints. In addition, the cost of maintaining a large workforce was significant.

In response to these challenges, a strategy was developed to automate routine processes in the bank. The main objective was to increase productivity and reduce errors. The way to achieve this goal included implementing advanced technologies and optimizing workflows.

After implementing this strategy, the bank recorded a marked improvement in productivity as well as a significant increase in customer satisfaction. In addition, staff costs were significantly reduced, which helped to address costs and efficiently utilize the company’s resources.

Supplemental Data:

  • The bank processes more than 1 million transactions daily

  • 600 employees are engaged in manual processing

  • Average time to open an account – 2 days, target – 20 minutes

  • Annual IT and data processing maintenance costs – $25 million

  • 10% of customers file complaints due to slow data processing

  • New product introduction takes 3-4 months on average

  • It takes an average of 15 minutes to process one document

  • Goal is to reduce manual data processing by 80%

                                          Exhibit 1

Problem

  • 80% of account opening transactions were performed manually, taking up to 3 days per customer

  • More than 50K documents were processed manually by tellers on a daily basis

  • Due to human error rate of up to 10% in manual processing

  • Data processing staffing costs were over $5M per year

  • Due to transaction processing delays, the level of customer complaints increased by 20% over the last year

  • Time to market for new products increased due to lengthy data verification processes

Dictionary

Marrbery Research

Our team conducted a thorough analysis of the bank’s existing processes to identify opportunities for optimization through RPA:

  • Audit and measurement of all key business processes in the bank

  • Analysis of the level of process automation and staff time utilization

  • Estimating the cost of manual document and data processing operations

  • Prioritize processes for automation based on volume and cost

  • Benchmarking of RPA best practices in the financial sector

  • Developing the concept of the bank’s target operating model based on RPA

This comprehensive research provided us with the data we needed to design the optimal RPA implementation solution for the client.

Additional technical details of the solution

Purpose

  • Automating manual routine processes with RPA to improve the bank’s operational efficiency

  • Implement robotic process automation to optimize data processing and reduce bank costs

  • Build a digital automation platform based on RPA to transform the bank’s operating model

  • Increase data processing productivity by 2x with robotic automation implementation

  • Reduce manual labor in the bank’s key business processes by 70% by implementing RPA

  • Accelerate document processing by 3 times and reduce errors by 50% by implementing digitalization

Solution development

After defining the problem and its scope, the next step is to develop a solution to solve it. In the case of a bank, this means developing an RPA implementation plan.

The RPA implementation plan should include the following key steps:

  • Analysis of existing processes

  • Prioritizing processes for automation

  • Robot development

  • Introduction of robots

  • Robot support and maintenance

    Analysis of existing processes

The first step is to analyze existing processes to determine their suitability for automation. This analysis includes the following tasks:

  • Measuring the volume and cost of manual operations

  • Analyzing the level of process automation

  • Identify problems and challenges associated with manual processes

Prioritizing processes for automation

The second step is to prioritize the processes to be automated. In doing so, it is necessary to take into account such factors as:

  • Volume of manual operations

  • Cost of manual operations

  • Level of business impact

  • Automation capability

Automation capability

The third step is to develop robots to automate the prioritized processes. This process includes the following tasks:

  • Defining robot scenarios

  • Developing robot code

  • Developing robot code

Introduction of robots

The fourth step is to implement the works in a real environment. This process includes the following tasks:

  • Customizing robot operation

  • Training of robot personnel

  • Transition to working with robots

Robot support and maintenance

The fifth step is to support and maintain the robots. This process includes the following tasks:

  • Monitoring robot performance

  • Developing new functions for robots

  • Making changes to robots

Here’s an example of an RPA implementation plan for a bank:

Step 1: Analyze existing processes

  • Measuring the volume and cost of manual operations

  • Identify problems and challenges associated with manual processes

  • Identify problems and challenges associated with manual processes

Step 2: Prioritize processes for automation

  • Volume of manual operations

  • Cost of manual operations

  • Level of business impact

  • Automation capability

Step 3: Robot development

  • Defining robot scenarios

  • Developing robot code

  • Robot testing

Phase 4: Robot implementation

  • Customizing robot operation

  • Training of robot robot personnel

  • Transition to working with robots

    Step 5: Robot Support and Maintenance

  • Monitoring robot performance

  • Developing new functions for robots

  • Making changes to robots

Decision tree

Decision tree for a case study on RPA in a bank

What’s the problem?

  • Routine processes in the bank are done manually, resulting in low productivity, high number of errors, delays and customer complaints.

Internal tree nodes:

Why is this a problem?

  • Manual work is inefficient and leads to these problems:

  • Low productivity: employees spend a lot of time doing routine tasks that could be automated.

  • Large number of errors: people are prone to errors, especially when performing monotonous tasks.

  • Delays: manual work can delay processes, leading to customer dissatisfaction.

  • Expenses: the bank spends money to maintain staff to perform routine tasks.

What can be done to solve the problem?

  • Implement RPA to automate routine processes.

External tree nodes:

How do you measure the success of RPA implementation?

  • Reduction of manual labor

  • Acceleration of processes

  • Reducing the number of errors

  • Increased productivity

  • Cost reduction

  • Increasing customer satisfaction

Recommendations:

  • Conduct a detailed analysis of existing processes to identify opportunities for automation.

  • Develop an RPA implementation plan that includes the following steps: analyze existing processes, prioritize processes for automation, develop robots, implement robots, support and maintain robots.

  • Create a team with experienced RPA experts to implement the project.

  • Train personnel to work with the robots.

  • Implement RPA in phases, starting with the simplest processes.

  • Monitor the robots and make necessary changes.

Additional Recommendations:

  • Analyze the experience of other banks in implementing RPA.

  • Utilize RPA best practices in the financial industry.

  • Ensure participation of top management in the project.

  • Develop a communication strategy to inform employees about the project.

These recommendations will help increase the chances of a successful RPA implementation in the bank.

appendix 1

The root of the tree is the main issue that needs to be addressed. In this case, it is the question of what problem exists in the bank. The internal nodes of the tree are the answers to this question.

Calculation of the effect of implementation

The effect of implementing RPA in a bank can be calculated by evaluating the following factors:

  • Reduction of manual labor: RPA can replace manual labor, resulting in reduced labor costs.

  • Process acceleration: RPA can perform tasks faster than humans, resulting in shorter process times.

  • Reduced errors: RPAs are less prone to errors than humans, which will lead to higher quality of work.

  • Increased productivity: RPA can increase productivity as employees will be freed from routine tasks.

  • Cost reduction: RPA can lead to a reduction in the cost of maintaining IT systems and data processing.

  • Increased customer satisfaction: RPA can increase customer satisfaction because processes will be completed faster and with fewer errors.

  1. Calculations of the effect of RPA implementation in the bank:

  2. The Bank spends UAH 100 mln on labor remuneration of employees who process documents. RPA can automate 50% of these processes, which will reduce labor costs by UAH 50 million.

  3. In addition, RPA can speed up document processing by 20%, resulting in a 20% reduction in process turnaround time. This can lead to a 20% increase in labor productivity.

  4. RPA can also reduce document processing errors by 10%, resulting in improved quality of work.

As a result of RPA implementation, a bank can gain the following benefits:

  • Decrease in labor costs by UAH 50 mln

  • Increase in labor productivity by 20%

  • Reduction of errors by 10%

The total effect of RPA implementation may amount to UAH 100 mln.

Details

Description of the implementation process:

Decrease in labor costs:

Before the implementation of RPA: 600 employees are employed in manual data processing.a:

  • After the implementation of RPA: Tasks Automated, the number of employees involved in manual work was reduced to 300.

Calculating Labor Cost Savings:

    • Average monthly salary of an employee: $2000

    • Employee’s annual salary: $2000 * 12 = $24000

    • Salary savings: $24,000 * (600 – 300) = $9,600,000

      Increased productivity

    • Workers can now process transactions faster through automation. For example, each employee can now process 20% more transactions per day.

  1. Calculation of productivity growth

    • Number of processed transactions per employee before RPA: 100 transactions/day

    • Productivity growth: 100 transactions/day * 20% = 120 transactions/day

  2. Minimizing errors:

    • After the implementation of RPA, the number of errors in manual processing decreased significantly. For example, the number of errors decreased by 50%.

    Calculating savings on error correction:

    • Average cost to fix one error: $50

    • Average cost to fix one error: $50

  3. Accelerating data processing:

    • For example, the time to open an account has been reduced from 2 days to 20 minutes.

  4. Reduced IT and data processing costs:

    • Once RPA is implemented, the bank can reduce equipment maintenance and support costs as processes are automated.

Conclusion

Implementing RPA technology in the bank was an effective solution to streamline routine processes and improve overall productivity. This step contributed to significant cost savings, increased data processing speed and reduced errors.

Results of RPA implementation achieved:

  • Decreased labor costs by $9.6 million annually.

  • Increased employee productivity by 20%, resulting in processing more transactions per day.

  • Minimized errors by 50%, which improved the quality of data processing and reduced the need for error correction.

  • Significant acceleration of data processing, particularly account opening, from 2 days to 20 minutes.

  • Reduced equipment maintenance and support costs.

The implementation of RPA led to a significant improvement in the bank’s efficiency and was an important step towards operational optimization.

Result

The implementation of RPA technology in the bank has brought significant positive changes to the organization. Key achievements include:

  • Transaction efficiency: Reduced document and transaction processing time by 30%. This resulted in a significant acceleration of internal processes and improved customer service.

  • Transaction efficiency: Reduced document and transaction processing time by 30%. This resulted in a significant acceleration of internal processes and improved customer service.

  • Cost savings: Reduced labor costs by $9.6 million annually by automating routine tasks and freeing workers from monotonous work.

  • Minimize errors: Reduced data processing errors by 50%, improving service quality and customer confidence.

  • Increased productivity: Increased employee productivity by 20%, allowing the bank to process more transactions and applications.

Overall, the implementation of RPA has significantly improved the bank’s efficiency and contributed to its competitiveness in the financial services market.

Recommendations

  • Continue scaling RPA: Consider expanding the implementation of RPA technology to other departments and processes of the bank. This will further optimize operations.

  • Staff training: Ensure employees are trained to manage and use RPA to support and optimize operations. This will help to maximize the capabilities of the technology.

  • Monitoring and updating: Continually monitor the performance of the RPA system, identify optimization opportunities, and make necessary changes to improve performance.

  • Adopt other technologies: Consider combining RPA with other automation and digitalization technologies to improve results even further.

  • Continually analyze results: Continuously monitor the performance metrics of RPA implementation and analyze their impact on the bank’s business processes.

  • Strategize for the future: Consider developing a long-term strategy for using RPA to achieve the bank’s strategic goals.

Forecasting based on 3 scenarios

Scenario 1 (Conservative):

  • Automation of 30% of routine processes, involving the use of robots to process documents and other operations.

  • Reduction of document processing time by 40%.

  • Increased machining accuracy by 20%.

Scenario 2 (Realistic):

  • Automate 50% of routine processes, including document processing operations and other administrative tasks.

  • Reduction of document processing time by 60%.

  • Increased machining accuracy by 30%.

    Scenario 3 (Optimistic):

  • Automate 70% of routine processes, covering most of the administrative tasks and document operations.

  • Reduction of document processing time by 80%.

  • Increased machining accuracy by 40%.

These scenarios provide different projections depending on the level of automation and the impact on the efficiency of banking operations.

The bottom line of the work we did was:
  • Automation of routine processes: A significant number of routine operations were successfully automated, which improved the efficiency of document processing and reduced the probability of errors.

  • Reduced processing time: The implementation of RPA resulted in a significant reduction in document processing time, resulting in faster workflows.

  • Improved accuracy and reliability: Automated processes have shown high accuracy and reliability compared to manual processing, reducing the likelihood of errors.

  • Efficient use of resources: Thanks to automation, human resources were freed from routine tasks, allowing them to be used in more interesting and strategic directions.

  • Cost reduction: The implementation of RPA has reduced the cost of maintaining a large staff, simplified processes and reduced document processing costs. 

ABOUT THE AUTHOR(S)

Alexey Konovalov is a partner at Marrbery, where Natalia Shevchenko is a consultant; Marina Krivosheya is a senior expert; and Maria Zankovetskaya is a consultant.

The authors would like to thank the following individuals:

Kovalenko Halyna, Snitko Kyrylo, Litvinenko Vasyl, Grigorenko Anna, Melnyk Oleksandr, Savchenko Olesya, Koval Oleh, Gordienko Denis, Timchuk Bohdan, Kravka Lilia and others who helped in the process. 

Moving into the future together!

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