
Advanced Predictive
Analytics & Deployment
Version 1’s Advanced Predictive Analytics & Deployment Solution covers the entire data analytics process from conception design through to analytical deployment and refinement
Extract information from existing data to discover usable insights and predict future outcomes. Output is then deployed to your operational systems in a secure and effective environment.
Combining multiple data sources, Version 1’s APAD solution can extract information from existing data to discover usable insights and predict future outcomes. These insights can be deployed directly into your operational systems to make data driven decisions and improve business processes.
Primary Advanced Predictive Analytics & Deployment Solutions
Version 1’s analytical experts can consult and deliver a wide variety of Advanced Predictive Analytics & Deployment solutions. Read more within the sections below.
Customer Analytics
Version 1 Customer Analytics Solutions use predictive modelling to target the right customers, identify dissatisfied customers by uncovering patterns of buying behaviour, and address customer service issues faster by correlating and analysing a variety of data. This offers you deep insights into what is important to your customer and can help you establish a dynamic, comprehensive view of individual customers and segments, understand what makes them high lifetime value customers, and ensure customer engagements are consistent, personalised and contextual across all touchpoints.
- Understand the way your customers behave and let this understanding help drive your decision making.
- Connect the right product with the right customer.
- Listen to what your customers are saying and use this information to improve services and become more efficient.
Claims Management
Claims management solutions use predictive analytics to help you reduce cycle times and minimize costs while improving the productivity, accuracy, and consistency of your claim-handling process and minimising the risk of fraud.
Claim fraud is increasing and the focus on claim fraud is increasing as well. How do you spot those before a hefty payout is made? Most fraud solutions on the market today are rules-based. Predictive Analytics uses a combination of rules, modelling, text mining, database searches and exception reporting to identify fraud sooner and more effectively at each stage of the claims cycle.
- Combine risk profiles with business rules to resolve legitimate claims in as little as one phone call.
- Streamline claims processes and decision-making, and implement continuous process improvement.
- Make better use of skilled investigators by enabling your staff to focus only on complex claims or high-value suspicious claims.
- Minimise claim payments and reduce fraud with real-time alerts of suspicious activity.
- Improve customer service and keep costs down by streamlining the claim handling process; for example, industry studies show that fast-tracking legitimate claims reduces customer frustration and minimises the likelihood that policyholders will take negative action.
- Decrease the amount of time it takes to process a claim by several days on average by improving claims routing, providing adjusters with suggested tasks and real-time assessment of adjuster statistics.
- Improve subrogation results by focusing on the claims more likely to pay you back.
- Build and use methods for scoring claims particular to state differences, lines of business, or times of catastrophe.
Predictive Maintenance
Predictive Maintenance and Quality solutions access multiple data sources in real-time to predict asset failure so that your organization can avoid costly downtime, reduce maintenance costs and improve operational efficiency. Driven by predictive analytics, these solutions detect even minor anomalies and failure patterns to determine the assets and operational processes that are at the greatest risk of failure or that can result in an increased number of faulty products and warranty claims. This early identification of issues helps you deploy limited maintenance resources more cost-effectively, maximise equipment uptime and enhance quality and supply chain processes, ultimately improving financial positioning, customer satisfaction and brand value.
Predictive Maintenance solutions will enable your organization:
- Predict when and where asset failures are likely to occur
- Leverage from the Internet of Things (IoT) sensors readings on instrumented assets
- Combine external data with internal data, such as environmental and weather data with data from Asset Management and Supervisory Control Systems
- Avoid asset downtime and reduce maintenance cost
- Perform root-cause analyses of asset and process failures
- Mine maintenance logs to determine the most effective repair procedures and failure patterns
- Visualize maintenance and operational insights and ensure Operational Efficiency through alarms prioritization and recommendations
Predictive Quality
Predictive Quality solutions will enable your organization:
- Detect emerging quality problems and reliability issues early enough
- Avoid costly callbacks and lost production
- Reduce scrap work, Inspections effort and Warranty claims
- Make adjustments to predictive maintenance schedules and corrective actions
- Maximise shipping rates cost-effectively
- Improve Brand Value and After Sales Support recommendations
Innovative companies consistently look for ways to achieve their goals more efficiently, quickly respond to market changes and take advantage of emerging opportunities. Predictive Maintenance and Quality solutions can help your organisation continuously improve Operational Efficiency by optimizing existing processes and turning operational data into actionable insights. Opportunities to improve operational efficiency, reduce operational costs and maximise productivity, exist in various operational areas, including:
- Workforce and Resources Scheduling
- Equipment and Spare-Parts Inventory
- Capital and Strategic Planning
- Supply Chain Management
- Building Management
- Energy Efficiency
- Facilities Management
Advanced Predictive Analytics & Deployment Case Studies

Case Study – OTP Bank
OTP Bank wanted to improve the speed and efficiency of its mortgage, loans and lease application processes, and make accurate, evidence-based decisions more rapidly than the competition. Upon implementing IBM SPSS Modeler, they can now uncover patterns and predicts risks associated with each applicant. As a result, the bank can quickly identify and approve those with low risks, accurately assessing borrowers’ credits to develop more precise revenue forecasts.

Case Study – APEC
To fulfill its role as a public service organization, APEC produces an extensive collection of case studies and market intelligence reports relating to professional employment.

Case Study – Medway Youth Trust
Medway Youth Trust is a charity that exists to improve the life chances of young people and has current contract responsibility for delivering the Connexions service in Medway.
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Discover More Industry-Specific Solutions
Version 1’s SPSS experts can consult and deliver a wide variety of analytics solutions across a broad range of industry sectors. Find out more at the links below.