Machine Learning

Artificial Intelligence (AI) is the development of models or systems that are able to perform tasks that normally require human intelligence.

Ultimately, AI is an attempt to replicate process and problems where sequential decisioning is involved.

AI adopters have significantly higher profit margins across all sectors. Companies investing in this area are already experiencing faster growth than their competitors thanks to more automation, more information and quicker responses to changes.

Machine Learning is often thought of as a subset of AI, a way of achieving complex results without writing large volumes of code. ML can be seen as the code learning from experience, where the code adjusts itself based on new data.

What are the advantages of ML?

  • Based on Non-linear Optimisation, ML allows for the establishment of much more complex relationships between features and outcomes than traditional models

  • It can handle a much wider variety of data sources such as big data and transactional records

  • Allows for exploration of more subtly predictive features

  • Well suited for anomaly detection or recommendation systems

  • Online-learning models allow you to adapt quickly to changes in the patterns of your data and underlying business conditions.

4most is consulting with financial institutions across UK on how to use these advanced techniques for:

  • Underwriting: Use of Natural Language Processing (NLP) and ML techniques allow for structuring of underwriter logs and augmentation of the data in order to describe it in such a way that a machine can be made to simulate decisioning

  • Customer scoring: Unsupervised and supervised learning techniques can be overlaid onto traditional techniques to improve discrimination. This helps businesses to target their customer base more accurately and manage portfolios with greater insight

  • Transactional Data: ML can be used to structure transactional information and create additional variables that can enhance customer assessment and predictions. This enhances key variables such as affordability, profitability, risk, marketing etc.

Our approach is to offer pragmatic solutions that add tangible value to the business, in particular:

  • In-house research and innovation: the application of techniques to differing real-life problems are constantly being investigated internally within 4most - we do the studying, clients get the benefits

  • Make it understandable for all parties: no blind trust in technique nor the modeller

  • Comparison of approaches: add complexity only when needed

  • Multiple validations: get confidence around both accuracy and interpretation

  • Flexibility of development & implementation: make the solution viable for the business.


For further information on Machine Learning, please contact our Head of Data Science, Fabrizio Russo:


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