A UK investment management company enhances performance and risk monitoring

Published on 04-Jan-2013

"One of our thoughts in choosing IBM was that if we got this risk analytics capability in place, we would have the ability to respond to new product strategies and put in place the appropriate levels of risk monitoring that investors expect to see." - Head of Risk Analysis

A UK investment management company

Financial Markets

Deployment country:
United Kingdom

Algorithmics Solutions, BA - Business Analytics, BA - Risk Analytics, Big Data & Analytics, Big Data & Analytics: Risk


This IBM client is one of the oldest and largest active investors in the UK. It looks after investments for several hundred thousand investors, and has more than £200 billion in assets under management invested in equities, fixed income and property on behalf of a wide variety of investors across the UK, Europe, Asia, the Americas and South Africa.

Business need:
The management of investment risk is at the heart of this IBM client’s business. The company wanted a robust, comprehensive and flexible platform to manage risk across a broad range of financial instruments.

The company implemented IBM® Algo Risk® and used it to develop sophisticated analytical models for risk management, product management, independent valuation of investments, and many other applications.

Single risk system with the flexibility to adapt to multiple use-cases in line with business requirements. Capable of modelling risk for even the most complex derivatives. Scales to process huge volumes of data on multi-asset based funds worth £80 billion (as of 2012). Delivers business-critical risk analyses on a daily basis with total reliability.

Case Study

This IBM client is one of the oldest and largest active investors in the UK. It looks after investments for several hundred thousand investors, and has more than £200 billion in assets under management invested in equities, fixed income and property on behalf of a wide variety of investors across the UK, Europe, Asia, the Americas and South Africa.

The company offers a retail open-ended investment company (OEIC) range distributed across the UK, Europe and, increasingly, Asia. In addition, the company provides pooled and segregated solutions for the world’s institutional investors – principally in fixed income.

Finding a solution for risk management
The delivery of investment performance and the management of investment risk are at the heart of the company’s business. Both of these factors are fundamental to the day-to-day decision-making process. Given the breadth of its business and the complexity of instruments in some parts of it, the company decided to find one system with multiple uses that would be capable of managing its risks across a wide range of business areas.

The company was not only looking to its present needs, but saw that its risk monitoring requirements were likely to escalate in the near future, and was wary of ad hoc in-house developments. “A lot of the risk monitoring capability we needed could have been built on spreadsheet-based applications, but that would not have given us a robust business platform,” says the company’s Head of Risk Analysis.

The need for flexibility
An essential requirement of any risk system was flexibility – the company wanted to be able to add its own models to the system, and to manage risks according to its own methodology. These requirements excluded a number of third-party risk management systems that were on the market at the time. After careful evaluation of a short-list of potential vendors, the company chose IBM as the vendor most likely to satisfy its needs.

“One of our thoughts in choosing IBM was that if we got this risk analytics capability in place, we would have the ability to respond to new product strategies and put in place the appropriate levels of risk monitoring that investors expect to see,” says the Head of Risk Analysis. “One of the business areas under consideration was alternative investment strategies, where the client required specific risk limits to be applied across a number of hedge strategies. The risk department, as an independent function, would then provide regular reporting on whether those funds were in compliance with the risk limits that had been set.” The limits would include value-at-risk limits, stress tests, scenario tests, and other more basic parameters like sector allocation and geographical diversification among others, and the risk management system would have to be able to perform these functions.

The company implemented IBM Algo Risk, a solution specifically targeted at fund managers and other buy-side clients. “One of the things we liked about Algo Risk was the fact that it has an open architecture that can integrate information feeds from a wide range of data providers,” says the Head of Risk Analysis.

The company was one of the earliest adopters of Algo Risk, and its initial implementation was a major success. The company has now been using the solution for more than 10 years. Over this period, it has worked closely with IBM to develop a wide range of risk models and solutions on the Algo Risk platform. As a result, all the multi-asset based funds that it manages – with a value of approximately £80 billion – are now analysed by the IBM solution.

Modelling risk for complex instruments
Unlike most organisations that introduce new technology, the company decided to use Algo Risk to develop risk models for its most complex instruments and portfolios first, with a view to adding its vanilla products later.

“We focus a lot of our time and effort in risk management on the more esoteric funds and investment strategies,” says the Head of Risk Analysis. “We look at liability matched funds, spread books, convertible bond portfolios, and so on – in other words, not the standard offerings that we have traditionally provided. This was our initial aim within the risk department – to provide senior management with information on those portfolios where the risks are less transparent.”

Flexibility to develop risk models
While most of the instruments that the company uses were already supported in Algo Risk, some were not. For example, the company trades inflation-linked swaps – retail price index (RPI) and limited price index (LPI) swaps. The Head of Risk Analysis comments: “These swaps are fairly well-used in the annuity business, where you are offering an inflation-protected annuity to a client, and you need to hedge that position.” The problem is that there are not many inflation-linked assets out in the market. “There are some index-linked gilts and a very limited number of index-linked corporates, but not enough to support the inflation-protected annuity market.”

The company worked with a few select investment banks to create the inflation swaps it required to meet its hedging needs.“We did a lot of work on building new models to support this aspect of our business,” says the Head of Risk Analysis. The company’s specialist financial engineers build the models in Risk++, a component-based development language supported by Algo Risk.

Extending the solution to standard products
Following the success of the initial deployment for its complex portfolios, the company also brought its more standard products into the Algo Risk solution. Algo Risk provides a hierarchical view of all the company’s portfolios and sub-portfolios, enabling the risk management team to assess risk at different levels.

“It is a useful attribute of Algo Risk that you have the ability to analyse as many portfolios in the hierarchy as you want, and are able to aggregate the information back up to review it at the portfolio level,” says the Head of Risk Analysis.

New applications for Algo Risk
1. Product development
In addition to assessing risk for its existing instruments, the company uses Algo Risk in its product development process. When a new opportunity emerges and a potential new product has been designed, the risk management team is able to use Algo Risk to model its risk profile. Based on the analysis of this profile, the company can then decide whether to bring the product to market.

2. Risk assessment for UCITS funds
The solution is also useful when regulatory requirements or market situations change, and different risk management standards need to be applied to existing classes of instruments. For example, the company manages investments in a number of Undertakings for Collective Investment in Transferable Securities (UCITS) funds. As the regulatory framework around UCITS funds continues to evolve, the risk management requirements are increasing. With Algo Risk, the company is able to adjust flexibly and meet the market and investment risk analysis requirements.

3. Enhanced analysis of collateral risk
Another recent trend within the industry has been the increased profile of collateral management in the wake of the banking crisis. The Head of Risk Analysis comments: “There is more concern about the strength of the banks and bank counterparts, so it has become more important to understand and communicate the attendant risks. We use Algo Risk to perform sensitivity analysis on potential future exposure to bank counterparts on a given OTC book, and we can do this on an aggregated basis or at the level of individual funds.”

4. Risk reporting for new audiences
The risk analysis team has also been working to increase the transparency of risk within portfolios for a range of new audiences, who are generally not involved directly in fund management – for example, senior managers, clients and regulators. To improve visibility and help these non-specialist audiences understand the impact of risk more easily, the company has used Algo Risk to develop standardised suites of reports that present the relevant information in an intuitive manner.

5. Independent valuation of private asset classes
For private asset classes where no market valuation is available, the company uses Algo Risk as a pricing engine, using sophisticated financial models to provide an independent valuation, in accordance with accepted industry best practices.

Building on a strong relationship
As a long-term user of the Algo Risk software, the company has built a close and mutually beneficial relationship with the IBM team.

“We were an early adopter of Algo Risk, and over the years we have gained a lot of experience in developing our risk modelling environment, both independently and with support from IBM,” comments the Head of Risk Analysis. “We recently upgraded the Algo Risk engine, and everything went very smoothly – we completed the implementation on time and under budget.”

The company’s expertise in risk modelling is now being shared with other group companies, especially those that need to meet the requirements of the Solvency 2 directive. “The lessons we’ve learned, particularly in terms of data management, are proving to be very helpful for our colleagues in other parts of the group,” comments the Head of Risk Analysis.

Realising the benefits
“We have now been using Algo Risk for nearly ten years,” says the Head of Risk Analysis. “It is such a flexible tool that we can use it to analyse risk for anything from simple bonds to complex alternative investment strategies. We have found that it can provide almost all the capabilities we need, and we have never had any problems with its reliability either: it provides new risk data every day, without fail.

“The other important benefit is its scalability. We started out with a few portfolios, but now we’re using it to analyse £80 billion of funds across hundreds of portfolios, with many thousands of calculations taking place each day. The fact that Algo Risk can handle such large volumes of data across such a broad range of instruments is a significant advantage, because it gives us a single comprehensive solution for risk analysis across the whole business.”

About IBM Business Analytics
IBM Business Analytics software delivers data-driven insights that help organisations work smarter and outperform their peers. This comprehensive portfolio includes solutions for business intelligence, predictive analytics and decision management, performance management, and risk management.

Business Analytics solutions enable companies to identify and visualise trends and patterns in areas, such as customer analytics, that can have a profound effect on business performance. They can compare scenarios, anticipate potential threats and opportunities, better plan, budget and forecast resources, balance risks against expected returns and work to meet regulatory requirements. By making analytics widely available, organisations can align tactical and strategic decision-making to achieve business goals.

For more information
For further information please visit ibm.com/business-analytics

Products and services used

IBM products and services that were used in this case study.

Algo Risk

Legal Information

© Copyright IBM Corporation 2012. IBM United Kingdom Limited, PO Box 41, North Harbour, Portsmouth, Hampshire, PO6 3AU. Produced in the United Kingdom. January 2013. IBM, the IBM logo and ibm.com are trademarks of International Business Machines Corporation, registered in many jurisdictions worldwide. A current list of other IBM trademarks is available on the Web at “Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml. Algo and Algo Risk are trademarks or registered trademarks of Algorithmics, an IBM Company. Other company, product or service names may be trademarks, or service marks of others. References in this publication to IBM products, programs or services do not imply that IBM intends to make these available in all countries in which IBM operates. Any reference to an IBM product, program or service is not intended to imply that only IBM’s product, program or service may be used. Any functionally equivalent product, program or service may be used instead. All customer examples cited represent how some customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics will vary depending on individual customer configurations and conditions. IBM hardware products are manufactured from new parts, or new and used parts. In some cases, the hardware product may not be new and may have been previously installed. Regardless, IBM warranty terms apply. This publication is for general guidance only. Photographs may show design models.