Keys to a Successful RPA Roadmap for Financial Institutions

The current situation with COVID-19 has led to unforeseen challenges in the financial industry and at the same time created opportunities for the introduction of innovative solutions. One such solution that is gaining ground in the industry is the move to digital automation.

Financial companies in particular are mobilizing and taking steps to improve digital customer journeys and transform risk / regulation processes to achieve greater efficiency while reducing costs.

Previously, investments were primarily made in technology to support improvements in the front office space to drive growth, while the middle and back office (mid-back office) had little improvement in the labor-intensive paper-mixing processes, creating operational inefficiencies. This has resulted in increased operational risk, forcing companies to reevaluate their old mid-back office ecosystem and focus on disruptive low-cost technologies like robotic process automation (RPA), artificial intelligence and machine learning, collectively known as ” intelligent automation (IA) “. for solutions.

IA promises to achieve significant operational efficiencies by mimicking the behavior of end users in finding, evaluating, transforming, and entering data according to established rules. IA reduces the need to invest in large transformation projects while helping to reduce manual intervention.

Although companies are exploring more advanced forms of automation like machine learning (MI) and artificial intelligence (AI), RPA has been in use for a while. This is especially true for horizontal functions, the scope and acceptance of which is rapidly increasing in the mid-back office space.

Bill Gates once said, “The first rule of any technology in a business is that automating an efficient operation increases efficiency. The second is that automating an inefficient operation increases the inefficiency. “

To ensure that RPA is successful within the organization, financial institutions need to create a comprehensive roadmap that models RPA as a strategic platform that drives tactical change in four key phases: plan initiative, run pilot programs, implement robotic operating model (ROM), and scale to equilibrium.

1. Plan the initiative

First, a comprehensive plan should be established that will form the basis of the initiative based on clearly defined business objectives. This ensures that the goals of the roadmap are in line with the overall strategy of the company. This plan should contain

  • Enterprise automation vision
  • Definition of RPA governance
  • Strategy for building support within key stakeholders
  • Company-wide implementation approach

2. Run pilot programs:

Once a plan is in place, the initiative should move into the pilot phase. This allows the company to demonstrate the RPA value to stakeholders, identify pitfalls and gaps in the plan, and recalibrate expectations and schedules. At this stage it is necessary that companies:

  • Test on a scale that requires minimal investment
  • Work with a trusted vendor who is experienced and can understand the needs of the business. Guide them through tool selection, execution process, and successes / failures in the operational cost review to determine if business goals are being met as planned, and identify areas of improvement

3. Set up and test a company-wide ROM:

This is a critical step in establishing maturity, standardizing methodologies, and building a solid foundation for scaling. The ROM should contain at least the following:

  • A framework that is consistent with the expected business benefits
  • An established Center of Excellence (CoE) that defines an organizational structure to best support RPA deployment, including roles and responsibilities
  • A governance pipeline to optimize process selection
  • An engagement delivery model for fast and efficient development in a structured, controlled and reproducible format
  • A technical architecture that supports scalability
  • A training program that ensures qualification across key RPA competencies

4. Scaling to steady state:

The ability to develop organically should be the goal in this phase. By promoting coordination between business and technology teams through an established CoE, stagnation is avoided. Assisting operational teams with the tools needed to manage a mixed workforce of humans and bots, and engaging HR to redeploy the workforce retrospectively to alleviate the fears associated with this change.

Roy Amara, former President of the Institute for the Future, once said: “We tend to overestimate the impact of a technology in the short term and underestimate it in the long term.” As with many other roadmaps before, it is crucial for success to have the right expectations in relation to it to bet on what is to be achieved. However, companies must also acknowledge that the roadmap is not a solid silver bullet, but rather a strong foundation that should be flexible enough to evolve and mature over time.

The trade lifecycle process in the capital markets is in the transition phase, in which legacy systems can no longer sustain the complexity of today’s financial markets without major investments. Smart automation, especially in the post-COVID-19 work environment, has helped financial institutions effectively transform capital markets through an incremental, modular approach without the massive infrastructure costs typically associated with large technology projects.

They are already showing immediate ROI benefits in pilot use cases for early adopters in the industry, helping companies bridge the gap between increasing workload and reduced funding.

Imran Parekh is a senior consultant at Capco, a global business and technology consultancy.

April 8, 2021