Powering AI innovation

The helpdesk handled around 11,400 queries monthly from suppliers and business users. Manually responding to queries by email after due diligence led to an average response time of 3 days.

We implemented a helpdesk solution powered by gen AI and supported by robotic process automation (RPA). Gen AI extracts query details from the tickets and formulates responses while incorporating sentiments from the query email and the organization's communication guidelines. RPA extracts relevant data from multiple systems to complete the response.

Our work saved the equivalent hours of 8 full-time employees and generated savings of approximately $1.09 million over 5 years. This transformation improved resource allocation and helped the company respond faster and more accurately to global queries, setting a new standard for helpdesk operations.

The client faced financial leakages of $200 million annually in North America, requiring over 470,000 transaction reviews by more than 40 full-time employees.

We will deploy 6 AI-driven modules to streamline coding, validation, recovery tracking, bill back, and insights. These modules will reduce deduction leakages, improve recoveries, and allow the team to implement best practices on processed transactions.

The solution will help the firm achieve potential annual recoveries and preventions exceeding $9 million thanks to actionable insights and improved recoveries on closed deductions powered by AI.

The client struggled to manually process thousands of pricing and trade promotions management (TPM) disputes, resulting in delayed resolutions, customer dissatisfaction, and limited visibility into cash flows.

We introduced a gen AI-powered solution for end-to-end processing of pricing and TPM disputes. By integrating RPA for file management, Power BI dashboards for recommendations on dispute validation, and gen AI for dispute processing, the solution streamlines upstream and downstream processes.

Our work aims to reduce customer wait times for the approval and validation steps by 30% and accelerate €1.5 million of cash flow thanks to an improved turnaround time across all countries. Customer Net Promoter Scores also improved due to decreased waiting times and greater customer satisfaction.

• Data was scattered across multiple documents and in multiple formats
• Data came in multiple languages
• Manual geocoding via Google
• Manual data cleansing and policy coding

• Automated smart data scrubbing and cleansing
• Enriched geolocation via Ecopia for precision underwriting
• Enhanced geocoding to standardize coding practice across submissions, improving accuracy and insights

• Up to 30% reduction in cycle time
• Up to 4% improvement in GWP through enriched geocoding
• Up to 50% efficiency in data scrubbing

The bank faced challenges due to fragmented risk and finance data, resulting in poor data governance and inefficiencies in regulatory reporting. They needed a unified system of record, improved process efficiency, and robust data management practices.

Genpact used advanced AI technologies to integrate risk and finance data, simplify business processes, and establish a comprehensive data foundation. Implementations included SAP S/4 HANA for legacy system consolidation and robust data governance frameworks to enhance data quality and lineage.

• Single source of truth: Established business-critical data elements across the enterprise
• Enhanced regulatory reporting: Comprehensive metadata management ensured compliance and traceability
• Improved data quality: Implemented controls and monitoring rules to maintain high data reliability
• Strengthened data governance: Robust practices improved data integrity, supporting enterprise-wide risk and finance initiatives

Product managers and QAs were manually creating user stories and test cases, leading to human error and bias, creating incomplete, unreliable, and inaccurate testing scenarios. As the complexity of each application grew, the time and effort required for testing also grew. The testing life cycle and test generation process also lacked traceability.

Genpact stepped in to redesign the BDD testing process and introduce gen AI to create automated user stories and test cases based on user requirements.

Automated BDD testing led to quicker turnaround times, an almost 30% increase in productivity, and better traceability of user stories and test cases to their respective requirements.

The company's server build team was facing challenges with manual provisioning, difficulty adapting to dynamic requirements, time and resource constraints, and complex infrastructure management.

Genpact helped the client generate Ansible Playbooks using gen-AI-powered prompt engineering that automated infrastructure orchestration, enabled dynamic scaling, and facilitated continuous integration and deployment.

Enhanced efficiency and time management by reducing operations time by 42% (from 420 minutes to 180 minutes) and improved productivity by 45% in the development effort. Over the entire year this initial venture saved the client over $30,000. More significantly, it opened up the possibility of much larger projects that can utilize gen AI to efficiently do code conversions and end to end business enhancements.

The company needed greater agility to face market shifts, drive efficiencies, and create capacity that it could reinvest in its core capabilities to accelerate growth.

Genpact is building an AI-enabled and experience-led digital platform to automate back-office processes, including order to cash, contract management, trade promotion management, vendor-managed inventory support, call-center services, electronic data interchange, and data synchronization.

This platform will create scale, flexibility, and adaptability by streamlining processes, reducing complexities and expenses. And it’s enhancing collaboration and efficiency across organizations too.

Tech distribution supply chains are often complex and fragmented due to their many shipment methods, minimal inventory strategies, and unclear processes. This led to revenue prediction challenges, customer experience (CX) issues, and missed opportunities for sales reps.

We developed an AI-powered virtual assistant to help supply chain agents determine the right action and communication strategies at specific fulfillment stages. By synchronizing the finance, supply chain, and sales teams, we improved overall efficiency, too.

• Up to 20% increase in accuracy on revenue recognition
• 10%-20% improvement in CX and customer satisfaction scores
• An enhanced control environment for backorder fulfillment
• Less dependency on business SMEs, increased first-pass yield resolution, and fewer rework/friction points

• Customers faced long case-handling and resolution times, resulting in a drop in customer satisfaction, more equipment downtime, and risks to patient safety
• With low rates of remote resolution, increasing field service dispatches added to engineers' workloads
• Technical support agents had to manually search documents to find answers

Our gen-AI-powered solution for technical support agents identifies and resolves issues faster with:

• A scalable solution built on volumes of technical information, expertise, and knowledge
• The ability to collate and tailor answers to customer queries in multiple languages
• Intelligent auto-fill functionality on a vast library of FAQs
• Feedback functionality that keeps humans-in the-loop and tunes the models for accuracy

• NextGen Support cuts agent onboarding time, enabling them to be effective faster
• It can deliver productivity gains of up to 20-25%, improve dispatch avoidance by 15-20%, and increase medical device up-time by up to 10%
• Most importantly, it delivers an improved and consistent customer experience

In this client's team, around 90% of agent mistakes are due to knowledge and communication gaps, and about 20% of cases have extended handle times because they rely on experts. What's more, new hires typically take roughly seven weeks to reach proficiency.

Genpact deployed an AI coach and digitized training-needs identification to improve pre-interaction training. During interactions, LLM training and virtual SMEs provide appropriate responses and product knowledge. Post-interaction, automated tests and performance nudges offer personalized evaluations and insights.

Customer satisfaction has increased by 3.6 percentage points, while efficiency, measured by average handle time, has decreased by 1%. Additionally, customer effort, indicated by repeat contacts, has dropped by 1.2 percentage points.

A manual-intensive process was leading to low productivity and multiple spreading requirements for a high annual volume of about 23,000+ financials. Moreover, dependence on individual analyst interpretation led to inconsistency across periods, portfolios, and analysts.

Genpact implemented Cora LiveSpread, an AI-powered solution that extracted and interpreted financial statements. The solution uses natural language processing (NLP) to scan notes to accounts and incorporate analyst-specific adjustments. The tool's microservices-based architecture allows users to create customizable templates with agile deployment cycles, offering a robust and scalable framework capable of handling multiple users simultaneously.

The collaboration with Genpact led to significant benefits for the client, including annual cost savings of around $100,000, a 45% reduction in touch time, faster loan processing, automated spreading with 100% accuracy, increased internal capacity, process standardization, and improved customer satisfaction.

The client's manual process of capturing actions and information searching led to backlogs and escalations due to untimely actions. Significant time was wasted on nonanalytical tasks like consolidating actions and assigning owners.

We automated the actions file to capture actions using gen AI. We also implemented a digital query-based chatbot to search for information faster by asking simple questions.

Created a data repository of the information taken from client meetings to enable the use of a chatbot, decreasing the time spent searching for information by 50 hours per month on average (calculated based on usage of about 20 to 25 people in total, 2 to 3 times a week).

Improving the effectiveness and productivity of financial advisors and customer service in addressing client queries by providing accurate, timely, and relevant content by embedding an employee-facing chatbot with gen AI.

The client partnered with Genpact to implement an OpenAI-powered virtual assistant as well as improve the assistant's performance.

Enables financial advisors to increase assets under management by freeing up time for client-focused interactions. It improves efficiency in addressing generic client queries through human-like conversational responses, incorporating expertise from research analysts, product experts, and portfolio managers to offer dynamic answers beyond traditional FAQs.