Stay Competitive, Comply with Regulations

AI in Banking & Finance

The financial services industry is adopting AI at an unprecedented pace to supercharge revenue growth, minimize operating expenses and risk, and improve customer experience. According to Accenture, banks could increase revenue 34% by 2022 if they invest more readily in artificial intelligence. Operating in a highly regulated industry, financial institutions often have to trade-off between model performance and explainability. TurinTech helps organisations navigate this optimally; enabling the building of AI at scale with minimum effort, while meeting financial regulations by enabling full transparency and explainability of processes and models.


Top AI use cases in Banking and Finance

Use cases include but are not limited to, improving trading strategies and portfolio management, assess credit worthiness of loan applicants accurately, detect fraud and misconduct, deliver a hyper-personalised customer experience.

Risk and Compliance
  • Detect transaction fraud faster, at scale
  • Reduce false alerts in anti-money laundering
  • Individualise credit scoring to increase revenue and minimise risk

Investment and Trading
  • Generate trading signals in real time for optimal decisions
  • Optimise asset portfolio to increase profitability
  • Accelerate algorithmic trading speed and improve accuracy

Customer Experience
  • Predict customer churn and recommend effective customer retention initiatives
  • Prioritise customer complaints and recommend the right actions
  • Anticipate client needs and recommend the right offer

Get started with evoML today

Our team will guide you through a demo of how you can achieve
optimal models and accelerate implementation with evoML.


We are pleased to work with amazing partners

We worked with our partners to deliver ever more innovative, effective and successful solutions. Their support has been vital in achieving the new generation of AI.


What do companies
say about us?

“A first and essential step in doing this (deploy optimal ML in production) is to optimise ML models and integrate them using scalable production code into the rest of the IT stack. Companies like TurinTech are early pioneers offering this capability.”
Ed Stacey

Managing partner at IQ Capital, Forbes Contributor

“This partnership signals an exciting opportunity to combine the forces of TurinTech and Exasol to help more enterprises scale AI and unlock its full potential.”
Stuart Power

Partner Manager, UK & I at Exasol

“TurinTech’s state of the art technology is now using AI to improve the way software itself is actually crafted. This represents one of the first steps in the exponential impact that AI can have. In the context of cloud it will materially improve efficiency costs and running speeds”
Jason Kingdon

Chairman & Chief Executive Officer of Blue Prism