AI decision-support case study
AI risk scoring and company verification system
An AI-assisted counterparty verification workflow consolidated company, credit, debt and reputation data into one structured risk assessment, reducing verification from several hours to a few minutes.
Project at a glance
- User profile
- B2B sales and finance teams
- Engagement
- AI-assisted counterparty risk scoring
- Data sources
- Company, credit, debt and reputation data
- Outcome
- Counterparty verification reduced from hours to minutes
Business context
Challenge
Business counterparty checks depended on manual searches across multiple data sources followed by time-consuming analysis. A single verification could take several hours, delaying the point at which sales and finance teams had sufficient evidence to assess a potential business relationship.
Delivery response
Solution
MPED built an AI-assisted counterparty verification workflow that consolidated Companies House records, credit data, debtor-register signals, online reviews and business history. The system analysed these inputs and produced a structured risk assessment with a risk score and report for review by sales and finance teams.
From data to decision support
How company verification and risk scoring worked
External company data → validation and analysis → risk score → structured decision-support report.
- Retrieving Companies House records and other external company data
- Consolidating credit data, debtor-register signals, online reviews and business history
- Analysing financial indicators and debt levels
- Assessing reputation through sentiment analysis of online data
- Using Machine Learning to identify patterns relevant to business cooperation risk
- Generating a risk-scoring output, with an example scale of 0-100, and structured reports for sales and finance teams
Platform detail
Technology stack
The delivery combined Azure services, .NET machine learning and third-party company-data integrations.
Operational impact
Results
- Reduction of counterparty verification time from several hours to just a few minutes
- Company, credit, debt and reputation signals consolidated into one verification workflow
- A consistent risk-scoring output and structured report available for operational review
- Less repeated manual collection of information across external sources
- Clearer decision-support output for sales and finance teams assessing potential counterparties
Summary
Faster counterparty verification through automated data analysis
The delivery converted a manual, multi-source counterparty-verification task into an AI-assisted workflow that produced a risk-scoring output and structured report in minutes rather than hours. The outputs supported review and business judgement by the responsible team; they did not replace it.
Related capability
Planning a company verification and risk-scoring workflow?
MPED combines Azure engineering, machine learning and external-data integrations to build tailored verification and decision-support workflows for sales and finance teams.