Case studies

Professional services firms must often manage research and knowledge projects involving many different stakeholders working together. See how a major auditor used Researchstream to take control of knowledge problems.

Supervisory guidance note SR 11-7 mandates that all US-based banks must maintain rigorous governance mechanisms for model risk management. What can your bank do if your credit risk modeling functions are already overburdened or can only cover the highest-risk models?

Wealth and investment divisions: see how you can meet all targets while ensuring compliance with the BCBS 239 guidelines.

Wealth management and investment management teams are under increased pressure to perform combined analytics as part of operational risk management. This is due to demands for analytical rigor from regulatory authorities such as FINRA. How best to succeed at combined analytics, which involves broad leverage of data patterns?

Pitchready – our suite of PowerPoint-based productivity tools has been developed to make pitchbook creation efforts smarter and more efficient. This case study illustrates how Pitchready helped a major investment bank increase its formatting efficiency by 50%. 

Internal IP teams have the expertise and tools to handle a whole range of patent-related tasks. However, it can be challenging to meet the additional demand during special projects, such as the integration of new acquisitions. High-volume tasks like docketing can become overwhelming, meaning work on patent analytics and designing new services can suffer.

With the advent of social platforms, our opinions and comments are now more powerful than ever – with the possibility of going viral in a few minutes! How can organizations use social platforms more strategically?

Banks depend on fast, accurate financial spreading to process credit applications promptly and minimize risk, but existing manual processes can be cumbersome, inaccurate and slow.

For an investment analyst in the agrochemicals sector, meteorological data is an excellent resource for sales forecasts—but how to leverage such a large data set? Read this case study to see how the mind+machine approach provides end-to-end service from data collection to insight generation.

Make or buy? A simple yet challenging question that manufacturing companies must answer in today’s dynamic economy, where identifying the right partner can be difficult and time consuming. So how can a business implement a reliable system into place that can efficiently scan the global marketplace, analyze their capabilities and identify the optimal suppliers?

Discover how Evalueserve’s 360-degree framework, which provides a complete view of the market, customers, and competitors, has helped one of our clients gain thorough understanding of customer behavior, while achieving 4–6% new sales from competitor churn; find 5–7% cross-selling opportunities; identify 4–5% high-value, likely-to-churn customers .

Managing customer churn is vital to business performance, while understanding controllable and uncontrollable drivers is essential in order to increase customer engagement, and designing short- and long-term retention strategies.

Evalueserve’s process of data collection and insight generation helps you access insightful and competitive reports, while benefiting from domain expertise. Since all the recurring, timeconsuming work is gone, you can now focus on tasks that offer greater value-addition.

Evalueserve offers a unique combination of logistics domain knowledge, proven best practices for sales engagements and a mind+machine approach for scalability to deliver a comprehensive view of the various delivery & supply chain influencers such as warehousing hubs, demand hubs, transportation cost, cost per supply chain activity and more.

How do we improve logistics performance for next-day delivery?
Through our unique “mind+machine” analysis, enabling a deep understanding of overall logistics processes including end to end supply chain processes, inbound and outbound shipment characteristics, key needs and pain points, supply chain value movements and top attributes such as transit time, customs clearance, network coverage, technology support etc.

Proper use of customer data can inform effective cross-sell strategies. Discover how a system for generating individualized reports helped a U.S. retail bank improve their customer loyalty and share of wallet.

Customer-centric data analytics can help in the assessment of customer bases and construction of versatile frameworks for sales enablement and customer interactions.

With the huge volume of information on traditional and social media, it’s challenging to find the data needed to inform strategies for crucial tasks like customer communication, marketing campaigns and even risk mitigation. That’s where active online listening (AOL) comes in.