19 October, 2017
This report takes a closer look at use cases for how next-generation tools like robotic process automation (RPA) and cognitive intelligence are increasing the efficiency of banking data conversions and accelerating the M&A life cycle.
Quick and efficient consolidation
The value of an M&A deal hinges partly on the quick and efficient consolidation of systems and processes to capitalize on cross-selling, synergistic opportunities, and cost efficiencies. And with most anything else, time is money.
While setting out to understand what makes conversions lengthy and complex, we uncovered the following trends:
- Data mapping from the original sources to the new systems is time consuming and nuanced
- Extracting data from various original sources (custom or standard, electronic or manual) is challenging
- Increased regulation and reporting standards require data remediation
- The manual nature of data entry and management often results in human errors
- New required functionality and system enhancements are difficult to prioritize and build
- Business processes aren’t aligned and products aren’t rationalized
- Extensive testing is required to determine conversion readiness
The introduction of next-generation tools, specifically cognitive intelligence and robotic process automation (RPA), can help to combat these issues and create an opportunity to reduce risk and accelerate the M&A life cycle.
Cognitive intelligence versus robotic process automation
Next-generation tools increase the level of automation and efficiency across the following three components of a conversion:
- Data sourcing and extraction
- Data remediation and transformation
- Data entry and staging
Cognitive intelligence is used for processes that require judgment, such as contract or loan reviews. Cognitive intelligence, leveraging tools like Deloitte’s proprietary technology D-ICE, can be used for predictive decision making.
Meanwhile, RPA is used for automating rules-based and operational processes, such as data entry or exception processing.
For each of these three data-conversion components, use cases have shown how cognitive intelligence and RPA can enhance:
- Speed. Reduce the amount of time required for conversion activities.
- Accuracy. Improve the accuracy of data and remediating gaps.
- Cost. Reduce costs depending on the functions selected for automation.
- Flexibility. Reuse tools to automate ongoing processes, rapidly scale
Maximizing transaction value
The benefits of next-generation tools include reduced costs, increased speed, and improved data accuracy. These tools also serve as the foundation to automate ongoing business processes. The application of these technologies can improve the quality of the conversion, but also has the potential to reduce timelines, including the post-conversion stabilization period.
Furthermore, next-generation tools allow organizations to refocus attention on core applications, business processes, and products to create a better experience for customers and associates.
Overall, continuing efforts should be made to leverage next-generation tools throughout the M&A life cycle to help maximize transaction value.
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See also link to the original source here.
A Chinese law firm and a member of the Deloitte Legal global network, we are well positioned to provide integrated solutions to address your business and legal issues within and outside China. "Deloitte Legal" means the global network of legal practices which are affiliated with Deloitte Touche Tohmatsu Limited member firms. Shanghai Qin Li Law Firm, a licensed Chinese law firm, is the China member of that global network.
For further information, please contact:
Jolin Song, Partner, Qin Li Law Firm, a Chinese law firm and a member of the Deloitte Legal global network.
jolsong@deloittelegal.com.cn
Mark Schroeder, Qin Li Law Firm, a Chinese law firm and a member of the Deloitte Legal global network.
marschroeder@deloittelegal.com.cn
