Fraud methods continuously evolve
Fraud typologies are constantly changing as fraudsters adapt to evade monitoring systems.
Organizations will often look at activity, behaviors, companies and individuals in isolation, preventing them from seeing the bigger picture that is needed to detect fraud.
Without a contextual view, you’ll face limitations on what existing monitoring systems and investigation teams can achieve in the fight against fraud.
Outsmart criminals with contextual fraud detection software
Empower your teams to see beyond a payment, transaction, claim, individual or single company. Configure your systems to more effectively distinguish between legitimate and fraudulent behaviors.
Use our Contextual Decision Intelligence platform to:
- Prioritize focus on high-risk people, businesses, channels and losses
- Identify more instances of fraud
- Automatically discount non-fraudulent events and minimize false positives
- Reduce the time for investigation or the need for investigation at all
- Reward good customers with an exceptional customer journey
increase in accuracy
scale to over 50bn records
Stop fraud in its tracks
Give your teams the context to reduce investigation time and prevent false positives.
Use our platform to add context to:
Mule account fraud
Identify cases of recruited mules, account take-over and illegally obtained accounts used to disguise funds made through crimes like cybercrime and drugs.
Monitor the portfolio of ongoing lending relationships for early-warning signs of bust-out fraud or changes in customer context.
Assess the risk of new applications for potential fraud. And automatically take account of an applicant’s connections to existing customers.
Expose connections between involved parties to protect against fraudulent claims and refuse cover if appropriate.
Automate fraud detection to identify and prevent VAT carousels, tax evasion and corporate compliance issues.
Insider fraud and serveillance
Aggregate signals generated disparately across your operations to detect and prevent fraud, data leakage and unauthorized trading practices.
Explore data across the procure-to-pay process and evaluate the risks of fraud, collusion and corruption.
Rapidly assimilate case data and surface the key insights to support early case assessment and triage.
Trade finance fraud
Detect trade finance fraud earlier to prevent huge losses using contextual monitoring to reduce false positives and fraud risk.
How to use fraud detection software in insurance firms
See how adding context to your fraud detection approach helps you reduce fraud losses, improve customer satisfaction and decrease the risk of reputational damage.
The benefits of using CDI to detect fraud
Protect your organization, shareholders and customers against the corrosive impact of fraud.
Reduce fraud losses
Improve detection rates to flag illicit activity before money is lost.
Identify new risks
Track emerging trends and stay ahead of emergent typologies.
Reduce false positives
Discount explainable signals to allow investigators to focus on high-risk issues.
Enrich investigations with context
Gather everything you know about an individual or business, from shared identities to bank accounts and transactions.
Reveal hidden and subtle activities
Draw on a wider network instead of looking at isolated events to better understand risk.
Dedicate more time to real fraud
Identify and concentrate on high-risk issues rather than false positives.
Situational awareness of commercial customers
Find out how creating a contextual view of your customers and their networks will help you better understand them and their needs, during a time of such momentous change and upheaval.
Why use the Quantexa platform
Build once, use many,
ingest to create a single
view with networks
Apply your data to multiple use cases—without replicating data sets.
more accurate decisions
Use context to improve decision accuracy across the organization, find new opportunities and uncover risk.
Scale to billions of records
in batch or real time
Built on proven, scalable open source technologies like Hadoop, Spark and Elastic.
Future-proofed open architecture
Integrate seamlessly into your existing IT ecosystem, with flexible deployment options: native, or containerized for private and public cloud.
Ensure data transparency
Use explainable data linking, advanced AI and decision models for regulatory compliance.
Keep your data secure
Rely on granular security levels for dynamic control, with all activity audited.
Operationalize your data in a matter of months – not years.
Use entity resolution and data volume to overcome missing or poor quality data.
Get the latest thinking, advice and opinions
How can we overcome the threat of mule fraud during COVID-19? (Part 1)
The way in which criminals operate is shifting as a result of COVID-19. Financial institutions must adapt to change quickly to prevent criminals from using mule fraud to take advantage of the vulnerable.
How to Adapt to a Changing World Using Situational Awareness
Financial institutions that rapidly adjust to the changing world by developing situational awareness will be able to make better decisions, remain resilient and overcome the short-term and longer-term challenges stemming from COVID-19.
How Insurers are Boosting Their Fraud Detection To Stop Criminals
Insurance fraud is a well-known and long-established problem. It has many guises and ranges from tiny one-off opportunistic cases through […]
Investigators Need Context and Analytics to Detect Fraud Effectively
Fraud is a complex and far-reaching issue, having this year become the most commonly experienced crime in the UK. From […]
Webinar: Next Generation Data and Analytics to Fight Financial Crime
With more than $1.5 trillion lost to Financial Crime in 2018 alone, traditional ways of dealing with fraud and AML […]
Using the EU’s own trade rules against it: the scourge of ‘VAT Carousel’ fraud
Read the full article in Euronews.
Book a demo
See how our Contextual Decision Intelligence platform prevents fraud before it happens, creates a real-time view of your customers, and reduces false positives.