Powering AI innovation

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.

The life insurance company struggled with multiple legacy systems, complex products, and a heavy reliance on undocumented knowledge that hindered its ability to provide optimal customer experiences and meet regulatory requirements.

Genpact is implementing a cutting-edge gen AI solution that aims to serve as a single natural language interface. This will allow the company to focus on customer, employee, regulator, and investor outcomes, simplifying processes and enhancing efficiency.

It's expected to dramatically reduce the operating time for processes that have a high-information collation and processing time, such as for legal and actuarial tasks. This will result in improved productivity, faster time to action, and better overall performance.

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.