Mid-Cap Broker phases in Blue Curve to manage complete investment research process

The Client

The bank is an independent, specialist international banking group that provides a specialised range of products and services to its select clients. One of the key focuses of the bank is Investment Banking and central to its success is Research.

The Research operation of the bank focuses on a number of sectors where they have established a leading position. Focussing on over 300 mid-cap companies the investment banking operation provides both corporate and institutional clients with valuable insights. Using its international position the bank delivers the comprehensive local coverage to a global readership.

The bank produces and distributes a range of Research products ranging from flash notes and morning meeting notes, 4 and 8-page company reports to sector and market periodicals. While the final documents were professional and presentable the whole lifecycle of research, involving over 50 analysts, was inefficient and problematic.

The Problem

Inconsistent and Inaccessible Data
Analysts each maintained their own business models on their own spreadsheets. The analysts' spreadsheets were fed individually by a variety of market feeds. Each analyst had their own models, their own calculations and their own terminology, which led to differences in financial modeling approaches, even within the same sector.

This decentralised practice led to inconsistent and inaccurate data between analysts. As these spreadsheets were the original source of information for all final formats of research the final products risked being published with inconsistent data, terminology and calculations. Although these errors were often ironed out by editing staff in the research department, taking time and effort, any inconsistency undermined client confidence and the investment view of the bank.

Research is a fundamental marketing tool for the sales team and a key catalyst for stockbroking transactions. However, in securing the business a salesperson may be challenged and questioned on the business rationale. With all the data inaccessible to the salesperson, the sales team was often unable to successfully conclude some transactions.

To solve these problems, the Research department decided to agree on common models and terminology across all their analysts and then implement a solution to maintain one central consistent store and view of the data.

Inefficient Production Process
The bank had some basic templates for each of the research products. Analysts were responsible for authoring the text and supplying editors with the relevant data. This production process was detailed and laborious and as a result the publications included inconsistencies in layout, branding, fonts and data content. The bank spent a long time proofing and re-editing each document that led to a lengthy and inflexible production process.

As a result of inefficient production processes the business were unable to introduce new research products and ideas, the costs of production were unnecessarily high due to the labour-intensive process and the business profile was weakened by inconsistent layout and branding.

The bank needed to build standard publication templates and automate as much of the document from a central data store. Any ad-hoc content needed to be controlled to ensure the consistency of the branding.

Multiple Distribution Activities
The bank was in the process of rolling out a global CRM solution that maintained all the client information as well as basic information on their research preferences. This one central store of information guaranteed a consistent data view but wasn't flexible enough to accurately reflect clients' detailed preferences for research nor was it designed to respond to clients' changing requirements.

The CRM system was storing basic client preferences, but was not actually performing the distribution. This meant a manual process was performed for each channel of distribution. Email lists were generated, the file attached and then distributed, often by different people. Printing formats and address lists were produced separately. And distribution to 3rd party networks was carried out separately for each vendor.

All these separate process got the job done but, once again, it was labour intensive and also gave the business no true record of which clients had received or read which research. This meant the business had no information to measure the effectiveness of the research they were producing or whether clients were satisfied with the service offered.

The bank needed to automate the distribution of research to save on costs and more importantly, improve customer service by only giving clients the research they wanted in the format they preferred.

The Solution

Many solutions were considered ranging from outsourced development houses, consultancy houses, data vendors and all the available software products. The client chose Blue Curve RMS and a single data vendor as the solution to all their problems with research production and distribution.

Centralised earnings and forecast data
Blue Curve insight is configured to reflect standard data items, terminology and calculations within all sectors. Analysts have the flexibility to perform scenario modeling and when they are happy with their forecast data they simply update the database directly from their spreadsheet. Coverage of new companies or changes in data items to existing companies is simply achieved through the analysts existing spreadsheet.

With all analysts updating to one centralised earnings database there is now a master source for all data and an audit trail of any changes. The central data store, viewable over the web, has improved the confidence of the salespeople and clients in the integrity of the data. A central database also means that salespeople can promote the transparency of the models that gives clients greater confidence in the integrity of the analysis.

Integrated publication templates
Blue Curve create has been used to link a suite of 8 research products using standard templates, linked to the Blue Curve insight database, with template tools, such as chart, structure and table wizards. The templates and their tools ensure that analyst can spend their time analysing and not worrying about the layout and format of the document. All the analysts have to focus on is producing their valuable content, as all the tools are at their disposal to insert any standard structures without adversely affecting the rest of the document.

Analysts and editors do not have to concern themselves with the accuracy of the data as the documents are all linked to the Blue Curve insight database and can be updated at any time. Analysts can also amend data item names in the database direct from the document if they feel the standard names do not reflect their clients' expectations.

Clients of the bank will be receiving a more consistent product but the real benefits lay within the time and effort saved in producing research. A periodical that would previously have taken weeks to produce is now completed in a day. This is possible as Blue Curve create focuses on the re-use of existing content so that analysts only have to input their content once. Its re-use within other products is then automated. This flexibility means that the bank can now consider extending the range of products without impact on the limited resources.

Centralised and automated distribution
The banks sales team manages the detailed research preferences of all of their clients using Blue Curve reach. When new research content is published Blue Curve reach dynamically generates the distribution lists and files for printing and emailing (as HTML and text) and automatically delivers to all 3rd party vendors. This means that the bank can ensure their clients receive exactly the research they want in the format they prefer. Blue Curve reach keeps an audit trail of each document and its recipients, which means the bank can now measure the effectiveness of their research.

The real benefit of Blue Curve reach is offering better customer service, if the clients know that you can deliver of their changing requirements they are more likely inform you of them. The savings in time and resource have also been hugely beneficial in terms of cost savings.

Overall

The Blue Curve solution for Sell-Side Research has successfully streamlined the whole research lifecycle from data collation through to production and distribution. The bank has saved considerable amounts of money in reducing errors and manpower but more importantly, has significantly improved the product and service that they offer to their clients.

The bank will continue to improve its processes as Blue Curve continues to improve its core functionality and introduce new products. Indeed, recently the bank has undertaken the implementation of workflow and comply.