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KLP empowers the front and middle office with advanced risk analytics
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Finance & Insurance
Applicable Functions
- Discrete Manufacturing
Use Cases
- Predictive Maintenance
Services
- Cloud Planning, Design & Implementation Services
The Challenge
KLP, Norway’s largest mutual life insurance company, was facing a challenge in embedding sophisticated risk modeling technologies into its day-to-day decision-making process. The company had two existing risk modeling solutions, but they were not user-friendly and lacked flexibility in presenting results in an easily accessible or understandable way. This made it difficult for portfolio managers and risk analysts to get hold of the data they needed. KLP's senior managers decided to investigate cloud-based solutions to address this issue.
About The Customer
KLP is Norway’s largest mutual life insurance company. It is dominant in the public-sector pensions space, with more than 700,000 members from municipal and county authorities, health trusts and other publicly owned companies. Its subsidiary KLP Kapitalforvaltning is responsible for managing NOK 278 billion of the group’s total assets, which in 2013 totaled NOK 375 billion. The company’s 58 employees manage 33 mutual funds in various asset classes. The majority are index funds; the remainder are either passively or actively managed fixed-income funds.
The Solution
KLP adopted IBM Algo Risk Service on Cloud, a single, cloud-based solution to model risk across all asset classes. This solution provides each user with instant web access to key risk measures and timely, personalized reports. The IBM Algo solution supports multiple models for different asset classes, allowing KLP to have a single solution for all its risk modeling needs. The solution also allows the company to monitor “pure alpha” and “pure beta” exposure across its portfolio, and easily track the risk for each group. The project team worked closely with the most demanding users to ensure the solution could deliver what they wanted.
Operational Impact
Quantitative Benefit
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