Banking Transformation Starts with Process Intelligence

The lines between banks and banking are blurring more and more. From credit cards to lending, trading products to cryptocurrency, fintechs are now providing sophisticated apps and tools to consumers who are demanding omnichannel services, low to no fees, and 24x7 on-demand customer service. Traditional banking and financial services firms have been slow to react. However, to remain relevant (or merely survive) you must adapt your bank to the technological and social changes that have created our new normal.

Transforming From the Outside In and the Inside Out

An effective enterprise banking transformation must be informed by the external forces causing change while considering the deeply entrenched internal forces standing in the way. Your external customers, regulators, consultants, and experts are the ones who understand the direction of the market. But to implement changes and be a leader in your industry is akin to steering a mighty ship in a new and unfamiliar direction. Moving that mass and overcoming institutional inertia requires an in-depth knowledge of internal systems, people, processes, data and their collective interconnectedness.

Successful banking transformation requires placing equal importance on both internal and external forces. Transformation is also not a one-time exercise. Instead, think of it as a constant and consistent effort to improve the functions that are critical to running your organization. Your need to be effective and efficient in the transformation effort requires comprehensive data and insights into how your bank operates.

The challenge for banks is in being effective and efficient in finding, implementing, and sustaining organizational improvements in effectiveness and efficiency. Yes, it is a circular reference, but one that can be overcome.

Initiating Your Banking Transformation

Almost every financial institution has a transformation already underway. A recent study found that 8 in 10 banks are currently in the midst of transformation, yet only one-third say their efforts are more than halfway complete. Regardless of the slow pace, those efforts include:

• Expanding cloud usage to minimize infrastructure and increase scalability,
• Deploying robotic process automation (RPA) to automate processes (with apps called “bots”),
• Building connectors and APIs to integrate data and processes, and
• Leveraging processing mining software to discover processes using system and event logs, and then to reconstruct those processes and find efficiencies.

All of these initiatives start with great enthusiasm and promise, but it takes significant time and effort to implement banking transformation at scale. That’s especially true in larger FSIs as the scope keeps changing and deadlines pass by.

Answer These Critical Transformation Questions

Consider the following questions whether you are in a transformation journey or planning to embark on one. These topics apply to many areas within the organization, from front office and global business services (GBS) to compliance and risk management. The intent is to evaluate the breadth of your processes, people, systems, and data involved in each and every action your firm takes. Only then can you grasp the scale—and potential—of any transformation effort.

• How many systems and applications (whether legacy, web-based, mainframe, or productivity apps) are used to initiate and complete a specific process?
• How much effort do workers put on each system and application during each process, and where are the bottlenecks? Is the organization adequately training and upskilling employees?
• How much time do workers spend toggling between different applications to complete their day-to-day tasks?
• What and where are the operational risks lurking in the background, whether it be making costly calculation mistakes in liquidity and cash management or reporting incorrect regulatory information that can attract high fines and penalties?
• How well do your enterprise resourcing planning (ERP) and customer relationship management (CRM) systems support the products and services you’re providing to customers today and intend to provide tomorrow?
• How much time, effort, and resources are required to map business processes and update process documentation when processes change?
• What are your golden sources of data, and is the data being used efficiently by your artificial intelligence (AI) and machine learning (ML) systems to give you the insights you need to manage your business?

These questions cannot be answered with manual exercises, or by bringing in an army of consultants, or using traditional BPMN processing mining software. To understand your complex and overlapping universe of enterprise systems and processes requires more intelligence, computing power, and speed than any of these traditional solutions can possibly offer. Unless, of course, you have years to wait for your transformation to take hold.

Why Process Intelligence Plays a Key Role in Banking Transformation

Traditional methods of understanding processes are process mapping, process mining, and process discovery. However, each of these methods returns an incomplete view of processes based on a snapshot of how the process was executed at a single point in time. Additional uncertainty comes from manually monitoring processes, which will undoubtedly disrupt workers and provide inaccurate results.

More technical approaches avoid this disruption by analyzing application log files, but they miss steps performed manually or outside of a limited set of applications. Finally, these methods only show what happened today, but that data is then stale tomorrow. Not a good foundation for an enterprise-scale transformation.

Process intelligence overcomes all of these shortcomings by automatically and continually acquiring process data at scale across any system in your firm. It uses AI and computer vision to provide clear and accurate visibility into the current state of your processes, and captures data from across regions, shifts, departments, and more—all without disrupting workers. This provides an accurate and comprehensive foundation from which to automate processes, drive digital transformation, and optimize workflows.

Rahul Talwar is a Solutions Director at FortressIQ. In this role, he works with a wide variety of companies to support their strategic business and transformation initiatives by leveraging AI, Machine Learning and other emerging technologies. Prior to joining FortressIQ, Rahul worked at Cantor Fitzgerald, Societe Generale Corp & Investment Banking, and Deloitte & Touche in different capacities.