We enable risk management
Learn More01October 2018 News Update
We have selected October's most relevant news within the fields of digital advice and balance sheet risk. To summarise, the global wealth management industry carries on expanding its offerings with automated financial advice solutions, while the end-customers become more price-sensitive and easily engaged into managing their funds themselves. On the balance sheet risk side, the industry continues to refine its compliance and operational practices in regards to MiFID II. Moreover, the large players are actively engaged in discussing the complexities of the upcoming implementation of FRTB. Last but not least, the regulators continue their work on defining means to mitigate cyber risks faced by rapidly digitalising financial industry.
Read More02September 2018 News Update
We have gathered the most exciting highlights from the digital advice innovation landscape as well as the latest news related to balance sheet risk. Overall, the news indicates positive ground for the growth of automatic financial advisers although the industry has been surprised by the large player's withdrawal from the emerging digital advice offering. On the balance sheet risk side, cyber risk is gaining prominence as an operational risk, while the IFRS 17 is increasingly viewed as a catalyst for business model innovation for the insurers. Additionally, the use of machine learning is penetrating accounting industry, though it is not expected to cause disruption in terms of massive unemployment.
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Automated Financial Advice
Financial advice is moving online and is increasingly provided on an automated basis, just like many other services. Read our guide to key development areas within this exciting field.
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In the second part of our "Asset and Liability Management Using LSMC" article series we conduct a comparative study between the performance of the LSMC and the full nested Monte Carlo methods.
In the first part of the ”Asset and Liability Management using LSMC” article series, we outline an ALM framework based on a replicating portfolio approach along with a suitable financial objective. This ALM framework, albeit simplified, is constructed to provide a straightforward replication of the complex interactions between assets and liabilities. Moreover, a brief introduction to the LSMC method used to generate all underlying risk factors is presented.
In continuation of our discussion of cyber risk, this paper investigates the issues of cyber risk management within financial industry. In particular, we look into the process of determining the optimal size of the investments in cyber security as well as the quantification of the appropriate cyber insurance premiums.
In continuation of our discussion of cyber risk, this article reviews different methods and models, which can be used to analyse and quantify the risks of information security breaches faced by the contemporary financial industry.
What we do
We improve decision making under uncertainty
Our work empowers millions of people to make, or benefit from, informed financial decisions under uncertainty. Asset liability management, capital requirements and automated financial advice - everything we do helps support our vision that everyone should have access to world class risk management tools.
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