Motion

Build, align, and maintain AI that gets better over time.

Capabilities
Manage in production
Manage models in production

Operationalise control and maintain performance metrics across all your models.
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Learn new capabilities

Expand and augment model capabilities to perform new and related yet distinct tasks.
Ensure ther Safe Use of AI
Use AI safely

Understand, visualise, and explore the history of your models’ decisions.

The only way to scale AI

Research has shown that 91% of models decay after the first year as new data is introduced, and the world continues to change. Retraining underperforming models helps, but incurs significant operational costs and doesn’t scale efficiently.  Solutions built on the Mind Foundry Platform are different. They continuously integrate data and AI agents to improve performance.
 
Motion spans the post-production lifecycle of your models and ensures responsible AI governance across your entire portfolio.


Part of the Mind Foundry Platform.



CML how it Works

 

 

Reducing the cost of fraudulent
claims with Aioi Nissay
Dowa Europe

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A platform for hosting and scaling AI


Model governance of today is time-consuming, expensive, requires hard-to-find expertise, and does not guarantee a performant model at the end of the process. Motion addresses these challenges by offering a solution that simplifies your governance program.

  • Management of model performance, ensuring that it remains as performant, or more performant than it was at the point of deployment.

  • Assure that fairness and bias metrics are still met in production, given the changes that can happen with new data inputs.

  • The ability for your model to learn new, distinct, yet relevant intelligence in production by utilising meta-learning techniques.

  • A centralised history of your models, including data provenance, enabling proper audits and a full chain of accountability for model behaviour.

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Benefits of Motion

 

  • Assurance that an evolving, in-production model remains responsible.

  • Automatic alerts when new trends are detected.

  • Continuous monitoring of models to ensure that performance remains consistent, or improves, with safeguards built to protect against performance degradation.

  • Explainability and transparency of the origins and subsequent operations of all the models in production, including lineage and provenance of the data and models.


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Case Study_ Reducing the cost of fraudulent claims

Case Study: Reducing the cost of fraudulent claims

 

Mind Foundry built a unique fraud detection and prediction solution based on Aioi Nissay Dowa Europe's specific requirements that could not be met by any off-the-shelf solutions. The Mind Foundry Platform empowered claims experts to identify, prioritise, and investigate fraudulent activity.

As new patterns emerge, using Motion, the solution automatically and continuously integrates data back into the model to improve performance over time rather than suffer model failure. New risks can be effectively governed while enabling the model to learn new types of fraud in production, meaning no manual retraining is needed.

Results include:

  • Increased referrals retained by the fraud department by 800%, so handlers spent less time on false positive cases.
  • Increased the detection of fraudulent claims by 120% compared to the legacy system.
  • Saved 2% on capped indemnity spend in 2022 and tracking to double that in 2023 with a 4% saving.
  • All of this plays back to that important piece of keeping premiums down for customers and opening up more opportunities for Machine Learning.

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"We get excited when we see the results of our models in production, but it doesn't stop there. The models need to continue to be trained, enhanced and tested to ensure they’re not biased, and that they continue to predict with the level of accuracy that we expect. Continuous Metalearning is really critical for any business and for anyone using AI and machine learning."

Nika Lee
Chief Underwriting Officer

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Learn more about what drives us

View Resources
5 min read
Why AI Governance Matters in the Fight against Insurance Fraud

 by Chris Andrew

Fraud is one of the most pervasive threats in the insurance industry. Insurance fraud is estimated to cost insurers £1.1 billion in the UK alone. As...
4 min read
7 Steps for Scaling AI Governance in Insurance Pricing

 by Selim Cavanagh

The complexity of modern pricing models, coupled with the regulatory changes that are due to come into effect this year, means that insurers need to...
6 min read
Why Insurance Pricing Needs AI Governance

 by Selim Cavanagh

Insurance is an incredibly competitive industry. The sheer number of customers, competitors, and small margins make for an adversarial landscape....

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