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The Investigator

Algorithmic Forecasting to predict future high harm crimes and solvability of high volume/low harm crimes, 13 May 2026

 

Latest in our Analysis in Action series aimed at crime and intelligence analysts and intelligence staff that explores the concept of Algorithmic Forecasting to improve crime screening decisions.

We’ll provide operational best practice around:

  • building an algorithm to predict future high harm crimes

  • building an algorithm to predict solvability of high-volume low harm crimes 

 

Our expert

The workshop will be led by intelligence specialist Simon Rose BSc, MSt, MBA, PhD who is Chief Exec of the Cambridge Centre for Evidence-Based Policing.

Simon is a retired Detective Chief Superintendent who served for the 30 years in the Met. His last role was the OCU Commander for Met Intelligence.

Simon has been proactive in developing algorithmic forecasting as a discipline. The application of algorithmic forecasting for triaging volume crime according to solvability was the subject of his PhD. He is keen to provide operational best practice to analysts and intelligence staff.

 

Benefits of Algorithmic Forecasting

The workshop will explore the benefits and limitation of Algorithmic Forecasting in enabling analysts and intelligence staff to make more effective decisions, prioritise resources, help reduce crime rates and enhance efficiency and accuracy.

We will explore how Algorithms can process massive, complex datasets much faster than human analysts, uncovering subtle patterns and connections that might otherwise be missed during investigations. This includes identifying links between disparate criminal activities.

The data analysis can help identify community vulnerabilities or specific environmental factors that correlate with higher crime rates allowing for targeted interventions.

While challenges regarding data bias, privacy, and transparency must be addressed, the core benefit lies in using data and technology to create safer communities through a more intelligent and proactive approach to crime prevention and investigation

 

Outline of the day

Session One: Introduction to algorithmic forecasting and its benefits for investigations

  • Examples of actuarial and non-actuarial algorithms and uses and a history that goes back to the Sanford (USA) in the 1960s

  • Different types of errors (false positives and false negatives)  

  • Different software and tools that are currently in use, eg Soze (to screen large quantities of intelligence data), DASH, DARA and DAAT (for domestic abuse forecasting), e-BIT (crime solvability), and Upland’s “Rant and Rave” for customer sentiment analysis.

  • The business case for algorithmic forecasting

 

Session Two: Building your own algorithm   

  • building an algorithm to predict solvability of high-volume low harm crimes and exploring the limitations and pitfalls.

  • building an algorithm to predict future high harm crimes and exploring the limitations and pitfalls.

 

Session Three: Governance and oversight and the limitations

  • Governance and oversight mechanisms, ALGOCARE – a decision-making framework for the deployment of algorithmic assessment tools in policing

  • ICO (information Commissioner’s office) and Sec 49 DPA (right not to be subject to automatic decision making)

  • Equalities impact assessments 

  • Bias 

  • Evaluations 

  • A devil's advocate approach to algorithms

  • The future

 

Held online via Teams

Certificates of CPD available.

HOW TO BOOK

Cost: £209 + VAT (GBP) per delegate per workshop (LEA and Government Agency rate).  £249.50 + VAT (Industry rate), per delegate 

Group bookings: We offer various discounts for group bookings depending on numbers, please contact us for details.

Booking: Please send the delegates name(s), email address(es) and purchase order (made out to The Investigator) to booking@the-investigator.co.uk or telephone +44(0)844 660 8707 for further information. 

Payment can be made by PayPal/debit/credit card. ​The meeting link will be sent out 7 days before the event.

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