Case study · HSBC
A resilience proof of concept that won new work
At a glance
- Client
- HSBC, through Capgemini Invent
- Sector
- Banking
- When
- 2020 to 2022
- Security clearance
- SC (Security Check)
- Type of work
- AI on good data
- Tools
- Neo4j
- Graph data science
The challenge
HSBC needed to know what can happen across its operations when one component fails.
What we did
We built a proof of concept with graph data science. It shows the operations as a graph, so it can trace what can happen when a component fails.
The result
The proof of concept won work for Capgemini.
We did this work before we started Mithril.
Related case studies
Finding phished accounts across Facebook and Instagram
60,000+credential-theft incidents found each day
Read the story
- The challenge
- Phishing was growing on Facebook and Instagram. There was no infrastructure and no metrics to identify the phished population correctly.
- What we did
- We owned the architecture and delivery of a phishing analytics data product for both apps, with large language models. A separate pipeline of leading indicators, with anomaly and drift detection, shows changes in the figures early.
- The result
- More than 5,000 phished users and more than 60,000 credential-theft incidents found each day. The product supported an increase of about 800,000 in two measures of monthly active users: accounts not held at a security check, and accounts with no sign of abuse.
- SQL
- Presto
- Spark
- Dataswarm
- Daiquery
- M360
- NEST
- Dashboards
- Large language models
An AI agent that answers questions about phishing
12 stepsin the investigation protocol
Read the story
- The challenge
- Questions about phishing and account compromise had to go to an engineer.
- What we did
- We designed and shipped a 12-step investigation protocol for an account security agent, for the phishing problem. A structured metadata layer links each metric, task, pipeline and owner, so the agent can query lineage, definitions and runbooks.
- The result
- People now ask the agent the questions about phishing and compromise that used to need an engineer.
- AI agents
- Semantic modelling
- Metadata layer
- Dashboards
Talk to us
Do you have a data problem like this one? Email kel@mithrilcorp.co.uk.