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Senior Manager - Operational Resilience

London
£65000 - £75000 per annum
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SENIOR MANAGER - OPERATIONAL RESILIENCE

£65,000 - £75,000

LONDON

This is a great opportunity for an analyst to lead projects in the operational risk team within a retail bank based in London. If you have experience working on the development of operational resilience frameworks and have strong stakeholder management skills, this role would be suitable for you.

THE COMPANY

The company is an established retail bank, they are an employer that is known for its staff wellbeing and flexible working environment. The company prides itself on its investment in the development of their employees and there are clear paths to progression for employees. They provide the opportunity for you to work in fast-paced environment with a lot of control over your projects

THE ROLE

The role is an Senior Manager position and reports directly to a Director in the business. The role will involve work on the creation and optimisation of the operational resilience frameworks in the business. There will also be a lot of emphasis on the way in which you develop and manage your team.

SKILLS

  • Experience working in 1st or 2nd line operational risk teams
  • Understanding of operational resilience frameworks
  • Exposure to senior stakeholders
  • Good communication skills
  • Strong management ability

SALARY AND BENEFITS

  • £65,000 - 75,000 base salary
  • Standard benefits

HOW TO APPLY

Please register your interest by sending your CV to Dapo Agiri via the Apply link on this page.

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Mitigating Risk In The Financial Services Sector With Machine Learning

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In this space, the evidence for the effectiveness of ML is overwhelming. Khandani et al. found that FIs using ML to analyse and review credit risk can lead to a 25 per cent cost saving for the FI involved.   These ML models come in various shapes and sizes, with the most common being instantaneous apps or websites which allow users and their banks to have access to real-time scoring, data visualisation tools and business intelligence tools.  The risk of risk management with ML Like with any AI or ML application or tool, there will always be cause for concern and real need to always remain vigilant. While ML has shown to be an invaluable tool across lower risk areas, the complexity of more statistical areas of banking, such as loans, has proven to be an Achilles heel for the technology. This usually stems from bias, a perpetual problem for AI and ML across all industries.  Technology Review notes that “There are two main ways that bias shows up in training data: either the data you collect is unrepresentative of reality, or it reflects existing prejudices.”  Data, analytics, AI and ML are notoriously non-diverse working sectors. The person behind the screen creating learning algorithms tends to be white and male, and very unrepresentative of the whole society that the machine learning tool will serve. Over the years, we have heard numerous accounts of unfair and unjust machines, which have learned from a very narrow and unrepresentative dataset, which stems from the lack of diversity amongst the employees within the Data & Analytics industry. 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