Move Faster and Smarter Toward Digital Banking with Process Mining

  • By Nigel Adams, Hetton Advisor.

Financial institutions are accelerating digital efforts to meet rising consumer expectations for speed and convenience, lower operating costs, and adapt to increased competition from fintech startups, big tech firms and non-traditional banking competitors alike.   

However, navigating the complexity of digital transformation is challenging and expensive. Some banks are spending over 10 percent of yearly revenue on technology investments. And yet, according to an Oliver Wyman investor survey, only 25 percent of investors are confident digital transformation strategies will be effective and 38 percent were skeptical.  

The root of the friction is that mature organizations must digitize before they can become digital. And yet, many banking leaders responsible for digital transformation and optimization struggle to gain an accurate picture of existing business processes and the potential impact of change. This lack of hard data increases the risk of failure for digitization efforts and puts the financial institution at a disadvantage against the competition in a rapidly changing marketplace.   

But there’s hope. Process mining is emerging as a strategic, analytical discipline that allows financial institutions to analyze the structure, performance and conformance of business processes based on the data produced during their execution.  And, the benefits of process mining are key to enabling financial institutions to take a data-driven approach to digital transformation and operational improvement.  

 

Here are seven ways process mining helps enable successful digital transformation and profitable digital banking strategies:  

 

1. Understanding the “As-Is” 

One of the most time-consuming and critical stages of any digital transformation is understanding and documenting your current processes. With processes distributed across multiple departments from bankers and the branch network, through the contact center and into multiple back-office teams, getting the right resources in the room to document current processes is a challenge. Even more challenging is the number of variants that seem to have evolved. Add to that, years of restructuring and the chances of getting all the right people, with the right subject matter expertise in the room are limited and the chances of really understanding what goes on is negligible. 

 

Process mining allows you to “discover” what really happens by analyzing the data from your existing applications It’s usually faster, more comprehensive and far more accurate, covering all variants. It is invaluable for understanding the current flow of customers through the process and customer migration and will provide you with a clear baseline from which to work. 

What’s more, the data-driven analytics will highlight those areas of the process that are ripe for re-imagining. 

 

2. Reimagining the “To-Be” 

While the focus of the transformation may be to re-imagine the entire process, there are frequently parts of the process where current constraints may remain, particularly around controls. Beyond analyzing the performance of the “As-Is” process, process mining can help identify where the bottlenecks are, where the biggest queues and backlogs are, how long it takes to move through part of a process, which steps consume the most resources, where the re-work loops are, where the process breaks down and potentially breaches key controls. This is critical input to designing the “To Be” process and further, the “What If” scenarios. What if process mining is data-driven process simulation: The ability to automatically discover high-fidelity process simulation models based on execution data. Traditionally, process simulation has been a highly time-consuming task, which requires highly specialized knowledge about probability distributions and statistical analysis. Process mining software automates this task; discovering, tuning, and validating simulation models and ensuring that these models faithfully capture the observed process and drive more informed decisions.  

 

3. Variant Testing  

It’s rare for a process mapping workshop to identify all variants. They tend to identify the “Happy Path” and common variants. This presents a significant risk that certain scenarios and use cases will be missed. The data generated in a process mining exercise can help identify the more infrequent variants and then inform the use cases for testing design. Moreover, by comparing use cases that passed testing with those that did not, variant analysis can identify the gaps and potential failure points, thereby accelerating issue remediation. 

 

4. Compliance Checking 

The same approach can also be used to tackle one of the most critical tasks – ensuring that the re-imagined processes are compliant. By defining a compliant process model and then comparing the output from the “To Be” processes against the model as part of the testing cycle, potential breaches can be identified and remediated prior to “Go Live”. 

 

5. Migration Approach 

Probably one of the biggest challenges will be which customers to migrate, how and when. It’s highly likely many customers will have to co-exist on the old and new platforms for example their secured lending on the legacy platform and their deposits on the new. It may be a bumpy ride for customers and introduce new risks for whole of customer processes like Know Your Customer (KYC) and Anti Money Laundering (AML). Using process mining techniques to analyze and compare variants, particularly less common variants, can help segment customers for migration phasing based on their more unique needs and reduce risk at the same time. 

 

6. “Go Live” and Post-Implementation 

“Go Live” for any project is a nerve-wracking experience, but with so much riding on the success of a digital transformation it takes on a new level of intensity. Finding and fixing production defects rapidly within the warranty period traditionally depends on fast and reliable customer/user feedback. However, asking customers and users to explain precisely what happened doesn’t always provide the level of detailed analysis to address the issues. Process mining’s conformance checking capabilities are a reliable way of identifying where a process has deviated from the intended model. 

 

7. Ongoing Monitoring 

Ongoing process monitoring can significantly enhance the value of the overall transformation. While business activity monitoring (BAM) has been around for some time, it is not process aware. To gain the full benefits of monitoring it’s important to understand the way the process flows – both the steps a transaction has been through and those to come. Integrating process mining’s native capabilities with other technologies such as machine learning can not only give you a far greater level of comfort in predicting whether your processes will be executed in line with their objectives but also the ability to automate decision making at key checkpoints or at least escalate transactions at risk. 

 

Tools for the job 

At least a dozen commercial software vendors specialize in process mining software, as well as a few quite impressive open-source solutions supported by a community of researchers and professionals.  Innovation abounds in the space with solution providers expanding automated process improvement capabilities, including advanced machine learning for predictive and prescriptive improvement models. Some of the most exciting advancements, quite simply, are in usability and what is often described as the “democratization of process mining.” Tools are evolving to be more accessible and easier to use across organizations, providing intuitive point- and-click interfaces, and rich graphical visualizations with secure controls that require no coding and no support from IT or data scientists.    

In closing, digitizing a bank goes to the very heart of how banks create and deliver value. But after decades of institutional evolution and regulatory intervention, delivering value today is built on thousands of process fragments, stitched together by a tangled web of legacy systems.  Process mining allows banking leaders to get an in-depth and precise picture of what’s happening in their organization, serving as the foundation for enhanced process performance, increased customer satisfaction, and successful digital transformation initiatives. 

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