Fraud Detection & Prevention
Protect customer trust and company reputation
Fraud detection and prevention is about connecting the data points to discover potential fraudulent behaviour before it happens. This starts with finding interactions between products, locations, and devices and then mapping those data points to individual users, customers, and/or employees. This approach effectively connects together vast quantities of knowledge with all of the people who somehow interacted with that knowledge.
Primary Fraud Detection & Prevention Solutions
Version 1’s SPSS experts can consult and deliver a wide variety of Fraud Detection & Prevention solutions. Read more within the sections below.
Insurance Claims
Detecting insurance claims with greater certainty, streamlining claims processing and making claims reviews more productive is exigent. Insurers are interested in questions like:
- Are they getting the desired ROI?
- How much fraud is being uncovered
- How much loss is avoided
- How much time is saved?
Predictive analytics technology helps you to instantly determine which claims qualify for immediate approval, flag suspicious claims for follow up and discover which customer behaviour is potentially fraudulent.
Detecting Fraud
Fraud detection is about connecting the data points to discover potential fraudulent behaviour before it happens. This starts with finding interactions between products, locations, and devices and then mapping those data points to individual users, customers, and/or employees. This approach effectively connects together vast quantities of knowledge with all of the people who somehow interacted with that knowledge.
In the Insurance industry at least 10 % of all insurance claims are inflated or fraudulent – costing the industry as much as €30 billion annually.
Preventing Fraud
- Detect fraud consistently throughout the life of a claim or across your customer base.
- Predict and prevent fraud at each stage.
- Automatically detect new forms of fraud with analytics that “learn” from your data.
- Support the overriding claims adjusting goal of moving claims to closure quickly, keeping costs down while providing a high level of service.
Fraud Visualisation & Investigation
Fraud Intelligence Analysis solutions help reduce the time, costs and complexity associated with fraud detection and investigation. It allows you to quickly collate, analyze and visualize data from disparate sources and identify key people, events, connections, patterns and trends that might otherwise be missed.
This solution can be applied across a range of industries including insurance, banking, financial services, telecommunications, law enforcement and defence.
Version 1 Fraud Intelligence Analysis is designed to provide critical insights to aid in investigating complex incidents, producing actionable visualization of critical people and events and documenting results for potential litigation. Benefits include:
- Analyze and visualize complex cross-channel attacks.
- Uncover hidden patterns and relationships in data by performing advanced analytics.
- Identify and disrupt fraud errors and abuse.
- Faster implementation and returns, typically within weeks. Reduce the time, costs and complexity associated with fraud detection and investigation.
- Quickly collate, analyse and visualize data from disparate sources and identify key people, events and connections that might otherwise be missed.
- Flexibility: Data can be left on existing servers while the investigation can be delivered to the client.
- Security: Only appropriate information is available to users based on the title.
- Extensibility: Can be integrated with existing systems
Fraud Detection & Prevention Case Studies
Case Study – Insurance Bureau of Canada
The insurance industry is constrained by the manual and ad hoc approach to detecting and investigating potential fraud. To address its objective of automating the detection of potential claim fraud and the identification of possible fraud rings, IBC engaged IBM to perform a Proof-of-Concept project using IBM® InfoSphere® Identity Insight and IBM SPSS® Modeler. The benefit IBM POC quickly found suspects and their claims reducing investigation efforts; found a previously unidentified suspect fraud ring; and gathered more information against suspected fraudsters with a higher degree of confidence.
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Case Study – Bancolombia
Bancolombia needed to develop new approaches to analysing transaction data. In addition, an acquisition that substantially enlarged the bank revealed serious drawbacks in its old rule-based analytic tools. Bancolombia now uses IBM SPSS Modeler to mine transactional data and detect suspicious transactions that may have resulted from money laundering or terrorism financing.
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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.