Process Mining in Banking: Top 12 use cases & case studies '24
It is estimated that banks will adopt automation for bank functions, capacity enhancement and manual lower-value tasks by 10 to 25% in next few years.1
Process mining in banking can manage and optimize the bank product processes, improve process key performance indicators (KPIs) and increase customer satisfaction by discovering automation opportunities, managing the change and complying with regulations.
In this article, we provide 10 use cases and case studies to help financial service industry leaders and financial institutions to deploy process mining software in finance and banking sector.
1. Optimize mortgage process
Process mining can help banks to optimize mortgage processes by discovering repetitive steps and reworks. Thus, process mining provides insights to optimize banking operations and communication flow (e.g. communication flow between all branches & headquarters) involving mortgage process.
In a process mining case study, an anonymous bank investigated their mortgage approval processes and found out that delays in the approval processes are related to the communication problems between front and back-office. Consequently, the bank prepared a new strategy to organize the work and communication flows across these offices.
2. Advance invoice processing
Process mining can be employed to discover and visualize invoice processing in order to detect the deviations in invoice process flow. Process mining also provides insights on root causes of these deviations. In a real-life process mining example, a Dutch multinational banking and financial services company implemented process mining to invoice processing in order to detect the bottlenecks in the invoice payment delays. The findings showed that employees lose time by doing tasks manually (e.g. writing reminder emails) which can be automated.
Another problem process mining helped detecting was the exclusion of dispute status of the invoicing process. The invoices that registered correctly receives a new status, dispute and these disputes were not considered as a part of the invoice process flow with no certain deadline. Therefore, employees would prolong processing these disputes longer depending on their workload. By including the dispute in the process and defining a deadline, invoices were prioritized and the delay problem was tackled.
3. Enhance loan processes
Process mining can help banks discover issues in loan processes, which are complicated process as they run through multiple systems. By discovering workflows in loan processes, financial institutions can manage loan processes and take actions to decrease the high lead time problem.
For example, in a process mining case study, Piraeus Bank analyzed their loan processes and detect variations in the application processes. Therefore, they shortened their application processes from 35 minutes to 5 minutes on average.
4. Refine credit card process
Process mining can help banks with card issue process analysis to find bottlenecks and time consuming activities. For example, a process mining case study from KB Card (South Korea) show that firm defined improvement points by analyzing card issue delays, work efficiency per employee and optimum task amount for the departments.
5. Discover automation opportunities
According to process mining trends, organizations used process mining software as an automation enabler by 25% in 2022. Process mining enables banks to understand the multi-level processes that include interactions among employees of front and back offices. By doing so, the financial institutions can identify areas where they can automate to increase efficiency, such as repetitive tasks and human error-prone activities.
Moreover, process mining can streamline deployment of robotic process automation (RPA) by revealing insights about the ongoing automation projects. With process mining, businesses can generate a digital twin of an organization (DTO) to simulate automation scenarios, estimate the expected ROI, predict failure points and improve their success rates.
For instance, Credem Bank from Italy leveraged a Process Mining to discover automation opportunities and measure the expected ROI. 2 The bank generated a DTO to simulate an automation scenario for their back office (BO) activities for the next 8 months. As a result, the bank could decrease the time employees spend on loan processing by 70% and saved around 1.4 million by automating 91 business processes.
6. Monitor real performance
Process mining can help financial institutions evaluate employee behavior and measure overall performance in regions, branches, departments, teams and time periods by automatically measuring process KPIs. Based on the results, banks can set data-driven benchmarks and improve their banking operations and employee performance to align with these goals.
For example, a multinational bank process mining case study showed that bank could capture as-is processes in their back office operations in Eastern Europe offices. Bank could optimize their business processes by an average of 16%.
7. Support innovation
By discovering real-time processes, process mining constantly provides insights on process innovation and opportunities which decreases the risk in transformation.
For example, in an academic study, researchers analyzed loan processes of a bank and found out that clients took longer time to complete their applications. 3 Based on these insights, bank innovated their communicational flow by adopting a different communicational strategy.
8. Manage change
Process mining can help banks update processes when it is required and assess the effectiveness of any potential change in the system. Once the change is implemented, process mining continue monitoring the systems to re-design changes with undesired outcomes.
For example, in a case study, the Rabobank has been applying process mining over the past years to drive change and continuous improvement.
9. Build cost control
Process mining allows banks to visualize the money flow across processes so that banks can decide in increasing or decreasing expenses in a data-driven manner. With process mining, banks can trim their cost or invest in capabilities.
According to process mining case studies, VTB Bank, the second-largest Russian bank, implemented process mining to achieve cheaper, faster and the best products for their customers.
10. Achieve compliance through audit
Process mining allows banks to monitor external transaction or any internal process from beginning to end. By discovering the ways business processes are executed, banks can identify fraudulent and abusive behavior like suspicious transactions to take precautions.
For example, with process mining, banks can detect the points that require a compliance response and explore solutions to mitigate them. Fraud mitigations solutions could include anti money laundering software, RPA for reporting issues and automating, cybersecurity measures, and workload automation tools to generate process data for further reporting and audit.
11. Improve customer journey
Process mining can help banks to improve customer journey by understanding customer behavior and change the way they operate based on customer experience. With process mining, banks can control potential customer drop outs, improve customer experience and find new improvement opportunities (e.g. payment methods).
For example, ING bank Australia branch process mining case study shows how the bank improved their website and call center to improve customer journey while interacting with the bank.
Check out 4-steps guide on process mining customer journey.
12. Accelerate sales process
Process mining help banks to analyze variation, repetitions, waiting times and service levels in sales processes. Based on these findings, banks can improve call center, front and back office services.
According to a process mining case study, a global mortgage insurance company with offices in the US, Canada and Australia leveraged process discovery for their call center operations, back offices activities. The insurance company claims that by implementing strategies based on the insights they gained through process discovery, they achieved 33.6% more process efficiency in less than 3 months.
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