A logical and proven sequence in business transformation
Many people reading this article won’t need to imagine the challenges facing global organizations. The new world is meeting the old world head on with visions of an fully automated, manual touch-free service model.
In most global organizations, the scale and complexity of operations creates obvious issues in terms of business and geo-diversities, technology adoption, infrastructure, change management, ethics, and cultural change in the people managing these tasks for many years.
A sequence and method to this madness is key to deriving maximum value from digital business operations.
Issues of scale, fragmentation, and change complexity
Many of our clients face these pressures. One of them, a global leader in wealth management, investment banking, and asset management, recently found several processes that are mission-critical for its traders, risk reporting, and the business as a whole were in need of attention. These processes cater to over 20 million securities – including equities, fixed income securities, and derivatives – and are sourced from a large number of data providers and consumed by over 500 business consumers in the bank.
A highly fragmented technology and operations landscape, changing regulatory pressures in different geographical jurisdictions, data quality and governance challenges, and most importantly the client’s operations and IT detachment from business laid bare the stark reality and provided an opportunity for the client to carry out a sense check across the board.
In an attempt to address some of these issues, the client had already introduced some robotic process automation (RPA) elements to its business functions, but these were piecemeal, tactical, and had been limited in their success. What was needed was a comprehensive operations’ transformation program with a more holistic approach.
ESOAR in action
The approach based on ESOAR that we described to our client was clearly applicable to the case, and the client saw the benefits of the linearity of ESOAR. Introducing robotics early on was suboptimal, as bots only really add value once processes have been cleaned up.
We leveraged ESOAR to assess the entire date operations function across investment banking and wealth management – including over 200 tasks and procedures – helping the client to better understand their operations. This assessment enabled us to identify 61 opportunities for ESOAR improvements, including eliminating redundancies, standardizing processes across business units, optimizing the allocation of tasks across the operating model, automating iterative tasks, and finally robotizing functions where human input adds no value.
As a result, we were able to pinpoint significant savings potential, reduce the risk of redundant processes, and improve the data quality in many aspects.
Elimination of manual interface monitoring, index updates, concurrent audit of manual instrument setups and amendments, temporary instruments amendments once process is automated or robotized, concurrent audit of data quality checks, and funds term sheets and prospects watermarking
Standardization of manual entering of instrument setup and amendment request details, setup and pricing templates and the request channel
Optimization of instrument setup request templates, setup and update of accurate report rules, the trace function for the creation of instruments, and the knowledge database to support queries resolution
Automation of non-term sheets instruments setups, BTS bonds setups, EQ setups, instruments temporary amendments processing and reversal, instruments setups and amendments, and municipal bonds, report generation, priority and agent assignment,
Robotization of end-of-day pricing for improved accuracy and shorter turnaround time, and license cost reduction
We implemented the plan for our client in two sequences:
- In the first sequence, we identified processes for elimination, and acted on them within a month. This enabled us to tweak the operating model and optimize efficiency against higher and lower cost centers, thereby achieving quick wins and savings. Processes were then standardized wherever possible across the client’s business units, and the legacy technology on which they were operating was at the same time improved and in some cases automated or robotized. This entire process sequence is now largely complete
- The second sequence is all about intelligent automation. A large team has been revisiting all the processes, looking for transformation opportunities of various kinds, including optical character recognition (OCR), supervised machine learning, unsupervised machine learning, cognitive processing, and pure RPA.
The tools we are using are Automation Anywhere for the basic RPA, and WorkFusion for the cognitive processing elements. We first conducted a proof of value (PoV) exercise on implementations in these areas and tackled the challenge of integrating these two tools simultaneously.
This PoV extended to a proof of concept (PoC) that was successfully delivered with machine learning and RPA combined for a complex term sheet process in the bank. We were recognized as the FIRST service provider to implement cognitive plus RPA in the bank with visibility at the CXO levels.
Building on this success, we have gauged the wider potential benefits that might be achieved in the next couple of years. In some geographies, cost efficiency improvements of 30–40% look possible, alongside other benefits, including reduced risk and improved quality.
Last, but equally important – implementation of ESOAR further highlighted the need for cultural change in the way our people considered and embraced automation. We have further initiated and accelerated an augmented workforce initiative to upskill our operations and IT staff to embellish the ESOAR model in order to embed a continuous ESOAR culture into our teams.
The work we’re conducting with our client is still in progress, but it’s already clear that the sequential application of ESOAR methods is achieving significant improvements. It’s also clear that the scope for implementation is both considerable and continuous. With operations on this scale, that is perhaps inevitable.
The implementation of our ESOAR methodology is set to contribute to a range of benefits, including:
- 30–40% potential improvements in cost efficiency
- Reduction of over 50 FTEs
- Improved risk reduction and regulatory compliance through remediation of redundant processes
- Improved data quality.
Preetham Kamesh is responsible for Capital Markets Business Services with a focus on integrated data management services (IDMS).
How to keep a challenging customer promise
In business, as in life, it can be good to set yourself a significant challenge. But sometimes, that challenge can become even more daunting than you expected – especially when it also involves keeping a promise.
One of our US clients recently found itself facing this predicament. This major insurance company has a single focus – supplemental health insurance for product lines such as critical illness, hospital indemnity, and disability. For example, upon diagnosis of a condition such as cancer or heart disease, the policy pays out a lump sum to the policyholder, to be used entirely as the policyholder wishes.
Customer service – the next level
Although organizations pay great attention to their customer service, our client prides itself on its client service, turnaround time, and best-in-class payment time. However, as claims continue to grow, they face a number of challenges around economies of scale.
In particular – and this is the significant challenge in this case – the company has made a name for itself not merely by promising to respond to claims within 24 hours, but by allowing those claims to be made in a number of ways. Yes, there were claims forms, but claimants were not required to use them. As business was growing, so was the pressure. With literally tens of millions of documents passing through the system every year, how was our client going to maintain simplicity for its customers, make the process more manageable, scalable, and streamlined for itself – and still react quickly to new documents, templates, or changes in volume to honor its commitment to a one-day response?
In addition, our client wanted to harness the buzz around intelligent automation, but didn’t know where to start. Ultimately, they needed to digitize the entire function, as a precursor towards implementing automation. Our ESOAR methodology proved to be just the ticket.
ESOAR in action
We started by absorbing as much information as we could about claims value chain. We observed the process from end to end, examined the claims forms that were integral to it, and made sure we also understood the variety and content of the many different unofficial applications people were submitting.
One of the first things we established was that our client was capturing more information on the forms than it needed. This made claims processing cumbersome for the claims processors, and even discouraged some claimants from using the form in the first place. The key information was there, but it was buried.
Our understanding of the supplemental health insurance industry and claims processing proved both relevant and useful. It enabled us to partner with the client and then leverage our own cognitive data processing techniques to extract the key information we’d identified on each claim.
The application of this technology, backed by the insights we brought to the process, enabled us to create what was effectively a “data-extraction-as-a-service” operation, providing relevant, digitized data from our client’s pages annually, and identify up to 45 key fields from each claims packet. Armed with this information, adjudications could be made and obligations to customers could be met.
The journey ahead
What is emerging from our application of ESOAR principles in this case is effectively a holistic approach to digital transformation. It’s a project that constitutes work in progress. The journey – and benefits that will come form it – are still evolving and growing. Now we have digitized the client’s information and created a set of defined fields, the next step is to build an intelligent bot to automate the process, to a point where the claims team will only need to handle exceptions.
Importantly, we’re demonstrating that it’s possible to continue to meet an expectation, even when it becomes more of a challenge – as long as you assess and plan carefully, and you act in accordance with what you learn.
And that, too, is a lesson for life, as well as for business.
Despite being a transformation journey, the results our solution and the application of ESOAR methodology continue to deliver include:
- Enhanced operational efficiency
- Improved customer experience
- Increased quality and compliance
- Enhanced agility.
Aashish Jain is responsible for driving go-to-market strategies, strategic solutions, and alliance ecosystem to facilitate growth of Capgemini’s Insurance Services unit.
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An effective intelligent automation approach that creates the foundation for AI