About

We are a truly hybrid consulting and technology firm

Most of us are ex-MDs from banking and finance or ex-Partners from established consultancies

Our USP is combining deep domain experience with specialist ART skills (Analytics, Risk and Technology)

Our software is designed by users for users (not by technology professionals for domain experts)

Basinghall – at a glance

Focus areas

Analytics, Risk and Technology

Engagement types

Advisory, software, technical assurance, specialist interim resources, and complex delivery

Target geographies

UK and Ireland, Nordics, and Central Europe

Strong academics

Most of our consultants hold advanced degrees from prestigious universities

Average work experience

Many of our consultants have in-depth industry experience (15+ years)

Our slogan “best practice in action” is the consulting equivalent of “show, don’t tell”
Show best practice via a prototype or a software, in action i.e. implemented
This makes complex concepts more concrete, easier to understand, and faster to implement
For example, show how to automate model validation or climate stress testing via a prototype

Standardization in the context of hybrid consulting/technology means construct solutions from combining off-the-shelf components
We have created many off-the-shelf components as part of our
homework
For example, model monitoring can be implemented using a subset of pre-selected set of metrics, along with commonly used thresholds, which then feed into standardized reports with defined content
The two main benefits of standardization are faster delivery and lower implementation risk
In general we aim to deliver in 25% less time as compared to the accepted market norm

Given our goals and services a significant amount of IP gets created on an ongoing basis
This is held in our sister company The Model Vault
Currently our IP includes (but is not restricted to) the following:

1.
A model risk quantification methodology, corresponding algorithms in Python, and a prototype running on Jupyter Notebooks
2.
A stress testing experimental tool
2.
An industrial-strength stress testing application running on AWS using microservices architecture and executing computations in Spark
3.
A scenario-based financial planning tool
4.
Synthetic data, e.g. evolution of a mortgage portfolio
5.
300+ banking book (credit risk, IRB /IFRS 9) models, trading book models, finance models, etc
6.
A very large library of business rules (written in JSON) required in stress testing (Bank of England’s STDF, EBA, ICAAP), recovery planning, and scenario-based financial planning

Strong quant and technology implementation skills
Specialist risk and regulatory expertise with reliable project delivery
Highly educated staff (90% postgraduates, more than half of partners have a PhD)