Artificial Intelligence

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Knowledge Base Articles

Part II - Artificial Neural Networks as a Substitute to LSMC and Nested Simulations

In this article series we present a machine learning-based approach to solving a common problem in financial modelling where one is faced with the task of estimating the value of a function which requires a significant amount of computation to evaluate. More specifically a function that corresponds to a so called nested simulation aimed at for example estimating a capital requirement for a financial institution or the risk associated with a structured product for a retail investor.

Part I - Introduction to Artificial Neural Networks

In this article series, we present a machine learning-based approach to solving a common problem in financial modelling where one is faced with the task of estimating the value of a function which requires a significant amount of computation to evaluate. More specifically, a function that corresponds to a so-called nested simulation aimed at, for example, estimating a capital requirement for a financial institution or the risk associated with a structured product for a retail investor.

Part I: An Introduction to Self-Normalizing Neural Networks

Machine learning applications have become more prominent in the financial industry in recent years. Our new article series is exploring the benefits and challenges of using self-normalising neural networks (SNNs) for calculating liquidity risk. The first piece of the series introduces the main concepts used in the investigative case study for the Swedish bond market.

Blog Articles

Forecast: The Core Ingredient of Engaging Financial Experiences

It has been a few years since digital transformation appeared on the priority list of the financial industry executives. While the evolutionary process of tapping into the latest technology is continuous, the pandemic has accelerated it dramatically. Even the most conservative branches, such as wealth management, now contemplates transforming their businesses into more digitalised operations. Some financial advisors embrace innovation wholeheartedly, reaping all the benefits and facing all the risks of early adoption, while others take a more cautious strategy. OutRank® advocates an incremental, forecast-driven approach when building digital journeys for your customers or financial planners, regardless of where your competitors are in their digital transformation efforts. At Kidbrooke®, we provide Forecast, the module of OutRank®, which delivers predictive forecasting functionality applicable to various financial planning use cases and digital journey elements.

WealthTech Trends for the Third Quarter 2021

Every quarter, we summarize the three most prominent trends in WealthTech and we are excited to share our latest summary with you today! In the third quarter of 2021, we noted that it's increasingly important to acknowledge the environmental, social and governance aspects of companies' performance as the sustainability reporting matures. Second, accessing digital capabilities through partnerships is one of the most efficient ways for incumbent financial institutions to deliver competitive services to their customers. And third, customer engagement is one of the most important activities that a financial services firm can undertake. Not only does it build customer loyalty by developing relationships with customers, it will ensure they choose you over the competition.

Economic Scenario Generators: What Matters?

It is often a good idea to start simple when embarking on a challenging implementation project. Financial institutions usually strive to build simple, intuitive solutions that their customers would easily understand. However, choosing simplicity in your digitalization strategy could lead to both good and bad outcomes. When designing OutRank, our financial simulation engine, we chose a more realistic scenario-based approach over the simplistic models based on Modern Portfolio Theory. Today we discuss one of the core functional units of OutRank in more detail, outlining the implications of its features on the resulting customer journeys.

Kidbrooke qualifies as an AIFinTech100 company

Kidbrooke is named as one of the world’s most innovative solution providers developing artificial intelligence (AI) and machine learning technologies to solve challenges or improve efficiency in financial services in FinTech Global's annual AIFinTech100 list – a list that highlights tech companies transforming the global financial industry by leveraging AI and machine learning.