In the first blog in this series, we looked at how intelligent automation solutions are delivering faster time to market for new products and data-driven cross-selling opportunities to drive business success in the Financial Services sector.
Quicker response times with RPA and operations transformation
Elimination of manual processes with the help of automation can result in significant reduction of response time.
Capgemini partnered with a North American electricity transmission and distribution utilities company to deliver a reduced cost-to-service, and increased delivery consistency through strengthened controls. We achieved this transformation by implementing 20 business processes, 200 robotic artifacts, and over 50 SAP scripts. Straight-through processing (STP) capabilities, in combination with other digital capabilities, such as online claims reporting and management, enabled the company to provide an improved customer experience.
We also helped another leading bank to rapidly process claims using a rule-based algorithm. The system uses STP technologies to quickly process certain types of claims based on set rules, enabling the bank to handle the claims efficiently. The initiative resulted in 35% reduction in the number of FTEs required, 30% reduction in overtime, and a 90% reduction in idle capacity. The bank’s system now handles 50% of its claims through STP.
Optimizing pricing and underwriting
Training ML models with large volumes of data can help with accurately categorizing variables such as insurance premiums.
Capgemini partnered with a European bank to improve customer service in its contact center processes across cards, collections, fixed term, international personal finance, line of business (LOB) administration, and the creation of IA business cases. We leveraged a unique framework using a combination of Blue Prism and .NET software, which led to 55% reduction in AHT and a 90% reduction of errors.
We also worked with a multinational insurance firm that used a neural network algorithm to classify customers who could be involved in large loss traffic mishaps during their coverage period. During the proof of concept phase, it predicted traffic accidents with 78% accuracy. Scaling such a system for underwriting their future insurance offerings enabled the multinational insurance firm to optimize their pricing and implement real-time pricing at the point of sale.
Data-error proofing and correction for claims
Errors spawning from human activities and due to lack of automation can result in endless lost hours to identify the source of the problem before the error can even be debugged.
A multinational European insurance firm was spending time gathering basic information such as postal codes, causing the system to be error-prone. Capgemini leveraged RPA to automate several mundane and repetitive programmable tasks. These changes reduced the process time from 120 to 15 minutes, freeing up time for claim handlers to devote their time to higher value activities.
Data-driven solutions prioritize the client
If there’s one takeaway message from the case studies in this series of blogs, it’s this: leveraging a digitally augmented workforce that prioritizes the client at the heart of operations will always reap unprecedented benefits for your Financial Services organization. IA can transform your operations across every dimension and at scale in sustainable and ethical ways.
To learn more about how Capgemini’s Intelligent Process Automation (IPA) can help you unlock value through IA at scale, helping you transition to – what we call – the Frictionless Enterprise, contact: email@example.com