Frequently asked questions
Browse our list of most relevant questions below.
Quantexa’s Entity Resolution is a data matching method that connects disparate and ambiguous internal and external data at scale with proven accuracies of up to 99%. Entity Resolution creates focused and complete views of people, organizations, places and other data. Quantexa supports Dynamic Entity Resolution, which gives unique flexibility across multiple use cases and enables granular and extensive security protocols.
Graph databases mostly store nodes and edges, let you query them, and let you run some standard graph algorithms.
But if your source data is siloed and inconsistent, your graph won’t reflect the real world.
Quantexa’s Graph Analytics technology is aimed at creating a graph worth analyzing, making the right connections for your data asset or business problem, and creating powerful context to support business decisions.
It can deliver tailored graphs for each request, meeting the differing requirements of multiple use cases – from the strictest of matches to the most speculative links. Because it does this without duplicating data, it can be a true enterprise platform.
Quantexa’s network generation is a graph analytics technique used to create a dynamic view of the bigger picture around an entity, automatically compiling the most relevant connections, entities and data for a specific decision. This context captures how people, organizations, events and places relate to each other to inform decisioning, so you can:
Drive efficient and effective automated decisions, investigations or analysis with relevant context,
Create connected data assets such as hierarchies, supply chains and families,
Use powerful graph scripting to find decision-specific hidden connections and filter irrelevant and unreliable ones.
Unstructured data, such as news articles, intelligence case files, or emails, accounts for 90% of all generated data and is growing at an average of 60% each year. Because of the nature of unstructured data, it’s harder than structured data to use and extract intelligence from, leading to extremely inefficient and ineffective investigation processes. Quantexa uses contextual search to link entities to unstructured data by using the context provided from the network, helping your teams spot meaningful information amidst masses of unstructured data. This contextual approach is resulting in more meaningful results and fewer false positives. Quantexa also applies natural language processing (NLP) to the world’s news, transforming 1.2M articles per day into AI-enriched news data, which can be filtered with high precision to find exactly the news relevant to your organization.
Quantexa uses Entity Resolution – a data matching method that reasons like a human, using all available data and many different ways of linking records.
That is why our solution can make connections between records and enrich your data, even when quality is poor. For example, our solution demonstrated 99% data matching accuracy in an independent test with Dun & Bradstreet. More about Quantexa’s Entity Resolution can be found here.
Our Entity Data Quality solution can help you improve data quality by identifying inconsistencies and flagging data remediation opportunities.
Traditional MDM has often fallen at the first hurdle, taking months to years to ingest data and match it accurately at scale.
Quantexa’s schema-agnostic data ingestion capability and Entity Resolution quickly create an accurate single view no matter the variety or volume of data, generating significantly more links between data.
Traditional MDM solutions find it hard to generate business value and ROI, because a single view of the truth is too constraining.
Quantexa serves flexible data products to multiple use cases. The platform goes beyond just MDM to host vertical business applications, and is both an analytical and operational data platform.
This is why organizations such as BNYM and HSBC have selected Quantexa.
Also, Quantexa does not need to replace your MDM, it canwork alongside it.
You can find out more here.
Quantexa works with your existing data integration and data governance software, integrating using streaming, API and batch approaches, building and distributing joined-up data assets such as a rich, connected customer view.
Quantexa integrates with data analytics and data science environments, including native support for data lake technologies and the Python ecosystem.
Quantexa’s cloud-native, but cloud-neutral architecture can be deployed onto all major cloud and on-premise environments, integrating with enterprise security, auditing and monitoring platforms.
Quantexa’s contextual data products and insights can be surfaced into business applications such as CRM, case management and workflow as well as digital and traditional interaction channels.
Organizations struggle to manage big data for decision-making, operational efficiency, customer experience and advanced analytical projects (such as AI and more).
The main things to look for in a data management solution are:
Time-to-value: how long will it take to deploy? Solutions that require your data to be transformed into a specific schema to be ingested may set your project back by months or fail before it started altogether if you run into issues. Solutions offering multi-source ingestion that is flexible and does not require data transformation on your end will accelerate time-to-value and require less resources.
Data matching accuracy: How are you going to fix data scattered across systems and data quality problems? An effective data management program will primarily focus on solving the data quality problem by joining data from siloed sources in the most accurate way, creating a trusted data foundation.
Analytics: will you have the right tools for data modelling and the AI use cases your data science team wants? By generating networks with graph analytics technology, you can uncover relationships between your data that can be used in decisioning models.
Transparency and explainability: how confident will you be in your analytics and decision-making? Make sure you are using open and transparent models that are fully accessible to end users and the data team.
Open architecture: How flexible it is to use the models and data how and where you want to.
Scalability and ROI: Is your data management future-proof and matches your organization’s ambitions? It is important to think about scalability and ROI and that’s not only about the number of data points or data sources you are able to ingest.
Flexibility: Most platforms will provide you with one view for your use case and that limits your flexibility in achieving granular user-level privacy and security settings as well as expanding to other use cases.
Learn more about Data Management solutions and how Quantexa can help.
Rules-based transaction monitoring systems have several limitations and challenges, which have historically hindered their effectiveness in detecting and preventing financial crimes.
For example, the rules and thresholds need to be manually created and updated, making the system less adaptable to evolving and emerging threats. Similarly, rules-based systems also typically analyze individual transactions in isolation and may not provide a comprehensive view of customer and counterparty behavior or relationships. They may miss the connections between seemingly unrelated transactions or accounts, which can be crucial in identifying more complex fraud networks or money laundering schemes.
In contrast, by combining multiple internal and external data sets all at once, Contextual Monitoring transforms the view of risk to a gain clearer understanding of customers, counterparties, their relationships and behaviors in real time. Using advanced entity resolution and network generation techniques, Contextual Monitoring focuses on holistic relationships rather than transaction risk in isolation.
This added context helps to identify hidden risk and generates fewer, more accurate alerts. Institutions can reduce rising compliance and operational costs and conduct more effective and efficient intelligence-driven risk processes without replacing existing systems.
Quantexa is a best-in-breed solution built by professionals with decades of experience across the financial-economic crime, compliance, intelligence, law enforcement and analytics space, underpinned by a technology that maximizes multiple data sources to support more effective and more efficient risk identification and investigation and is battle tested with organizations globally.
Building in-house technology can be a viable option for many companies, depending on their specific needs, circumstances and skill sets. However, there are several factors to consider when deciding whether to build in-house technology or use best of breed third-party solutions such as Quantexa. These factors include employing cutting-edge technology such as entity resolution and advanced network analytics. Considerations related to time-to-market and the complexities involved with executing on such projects. Very often, process delays can interrupt time sensitive initiatives and hinder a company’s agility. Using best in breed technologies like Quantexa come with lower risks compared to building entirely new technologies. Our solutions have gone through extensive testing, updates and iterations which reduce the likelihood of major vulnerabilities. Our streamlined best practices enable organizations to stay the course with a continued focus on core competencies that drive revenue and growth.
Similarly, through its Community program and user forums Quantexa clients have collaborative access to peers in comparable roles, facing and overcoming similar challenges.
Our approach can also provide bottom line benefits that demonstrates quantifiable improvements that support budgeting now and in the future.
Whilst the use case and risk coverage will largely determine the data needs, to generally better detect and investigate financial crimes, you would need access to various types of data from multiple trusted sources – consolidated into a single source for monitoring, detection and investigation purposes.
Here are just some key data types that can be valuable in detecting financial crimes. However, as part of any engagement Quantexa will help guide you to ensure you use only the data that’s required:
External / third-party data (corporate registries, government databases, watchlists, sanctions lists, public records, adverse media, etc.)
Market data (related to market conditions, assets, prices, trading volume, trends, etc.)
Risk scoring data
It's worth noting that while access to these data sources is beneficial in detecting and investigating financial crimes, it is always essential to adhere to legal and privacy regulations when collecting, storing, and processing personal and sensitive information.
Quantexa Financial Crime solutions are built with flexibility, agility and self-sufficiency in mind and can be implemented incrementally. We integrate seamlessly with existing systems and can augment technology and processes already in place. We can iterate our approach with more capabilities and use cases to yield consistent, substantial value across your enterprise as our relationship evolves. We also design solutions for seamless integration to industry standard case manager tools including Oracle Mantas, Appian and Actimize.
Know Your Costumer
Yes. Leading companies are either on a calculated journey to pKYC with us or are already there. Leveraging our Decision Intelligence (DI) platform which is underpinned by world class entity resolution and network generation, enables us to transform the approach to KYC for our customers. By connecting all available internal and external data and assessing behavior, we create a unique, holistic view of customers to detect risk and opportunities automatically and continuously. We simplify the analysis of complex relationships and corporate hierarchies by overlaying risk attributes to seamlessly uncover hidden connections between customers, counterparties and their behaviors which are often impossible to see in isolation. This dynamic approach helps transition from 1,3,5-year reviews to a dynamic trigger-based KYC process that improves inefficiencies and facilitates a continuous, informed, realistic understanding and accurate review of these risks through perpetual monitoring.
We are not trying to replace the work your operations teams are currently undertaking but will enhance it with automation and intelligence. With our entity resolution and network generation, we can build a more complete picture of material risk for targeted reviews and enrich your existing approach with the detection of risks linked to the customer behavior and related counterparties. This enriched view can integrate into existing models to drive better risk detection and automate ownership structure building.
The comprehensive journey to pKYC can be incremental and focused on significant challenges to start. Many of our customers take a phased approach based on priorities such as increased risk monitoring or improved efficiency. Along this journey, you will more clearly identify material risk that will help to manage the overall KYC process more effectively.
Also, through seamless, open architecture your teams can continue to use the tools they are using today (e.g. CLM, Risk model, Python, R) with limited interference.
Through advanced entity resolution and network generation capabilities, we can automate the use of internal and external data sources to monitor for changes against current KYC profiles, including ownership structure. This provides enriched context and changes the way customer information can be used to automatically detect risk and opportunities.
These advanced capabilities drive the automatic recalculation of profiles by identifying new direct and indirect material risk, reducing unidentified risk and reputational consequences and narrowing the focus to significant, relevant risk to investigate further.
Our collective, enhanced capabilities enable a more dynamic, comprehensive understanding of a customer which drives a unique, proactive and dynamic approach to KYC.
Fraud and Security
A new contextual approach is required to improve fraud prevention, detection and investigation - Market participants have raised challenges with using real time capabilities which are missing risk and blocking legitimate payments or adding friction which is impacting the customer experience.
However, Quantexa can detect suspicious transactions in near real time and alert to ensure high risk transactions can get immediate attention. Quantexa can also augment with existing technology to provide additional context to illuminate high risk transactions or provide confidence through mitigating factors that the transaction is legitimate and non-fraudulent.
Detection Packs for fraud deliver higher true positives, lower false positives. For additional coverage we have knowledge and IP but will work with your teams to develop using your own data.
Banks, Insurers and Public Sector organizations are using Quantexa to uncover previously undetected fraud.
Even where our clients already have a system in place to provide a single view, we have still provided deduplication rates of up to 20%.
Our ability to ingest internal and external sources means we have greater breadth and flexibility in the view.
Our ability to perform automated network (entity powered graphs) enables you to go beyond the customer view to look at relationships, associations and hidden connections.
Our dynamic entity resolution enables tailored views for different fraud and value-chain needs so that you aren't constrained to a one size fits all - which is both useful operationally but also from a security control perspective.
Our analytics and visualization platform enables transparent models to be built in conjunction with your teams and improved operational efficiency in complex triage etc.
We are not trying to replace the work your client analytics teams are doing, but to enhance it. We can provide a richer 360 view with networks that they can use as inputs to their models to drive better performance. We have an open architecture which means they can continue to use the tools they are using today (eg. Python, R, TensorFlow).
The output of Quantexa can be integrated within existing systems – including other fraud solutions or in-house developed tools. Quantexa can send signals to other tools which can then give users the options to use Quantexa to perform the investigation or look at the network in more detail.
The network UI does not need to be presented to business users – a simplified view with only the pertinent information can be integrated within existing systems. Quantexa can cater for all levels of investigator within the fraud team to support them in their role and to determine the best course of action.
In addition, Quantexa has a training academy to enable users to get the most from the tool and learn new ways to help them investigate and achieve better outcomes.
We enhance the work your teams are already doing by providing more efficiency and effectiveness. With market-leading technology, we connect internal and external data for a single view of the borrower furthering your understanding of their direct and indirect relationships including customers and suppliers in the supply chain. With these advanced capabilities we can continuously monitor profiles for longstanding risk even beyond a single entity.
Quantexa Risk solutions consist of Portfolio Monitoring – Early Signals and Holistic Counterparty Risk Profiling. Unlike most early warnings solutions that focus on financial / behavioral and event-driven drivers only, our platform goes beyond this and adds supply chain, transactional behaviors, news and industry views to accelerate warnings 18-24 months in advance. Counterparty Risk Profiling analyzes assessments across sales, legal and credit structures for a broader understanding of the borrower and counterparty networks to help accurately identify risk.
With open architecture, we seamlessly integrate with existing systems, allowing teams to input connected networks to their existing models and continue to use their current, preferred tools to enhance performance.
You’re correct in that our market-leading technology was originally designed for financial crime detection. However, the challenges for financial crime and enterprise risk users are comparable. Both need a single view of the customer, a single view of counterparties as well as an understanding of relevant context around them. With our unique, connected context built through advanced capabilities, we can leverage the success in financial crime and apply this to a more advanced approach to enterprise risk that ultimately facilitates enhanced risk management.
In addition to our solutions which drive early warning signals and strengthen your regulatory approach to counterparty profiling, we improve risk data hygiene and support immediate and long-term resiliency strategies enterprise wide. With advanced capabilities and our enriched view of the borrower’s ecosystem we enhance credit models and portfolio performance by monitoring and identifying second order risk impact through a context-driven understanding of connected exposures / indirect borrowers, we can automatically aggregate and assess market sentiments. With context, we clearly identify counterparties to offboard and pinpoint risky exposures that align with a given risk appetite.
Our modernized, data-driven processes position Quantexa as your partner to not only strengthen risk resiliency but also improve client experiences and growth across your organization long term.
Quantexa provides access to over 80,000 news publishers from around the globe, averaging ~1.2M news articles per day. Every article is enriched using industry-beating AI to transform unstructured news articles into structured news data, which includes granular category, industry, and entity tags. This enables you to easily configure sophisticated queries that pinpoint relevant news and proactively monitor warning signals related to your specific risk landscape.
Quantexa uses Entity Resolution - a data matching method that connects disparate and ambiguous internal and external data at scale with proven accuracies of up to 99%.
Quantexa’s Entity Resolution was designed to work with poor quality and sparse data and has proven time and time again to be much better than traditional matching approaches, e.g., demonstrated 99% data matching accuracy in an independent test with Dun & Bradstreet.
We also have data quality tools in place to improve data quality by identifying inconsistencies and flagging data remediation opportunities.
Even where our clients already have a system in place to provide a single view of customers, we have still provided deduplication rates of ~20%.
Due to our approach to entity resolution, we are able to bring together a much broader range of internal and external sources than is typically possible, creating a more enriched view. In addition to that, because we uniquely support dynamic Entity Resolution, your data can be used across multiple use cases.
Quantexa is not trying to replace the work your analytics teams are doing, but to enhance it.
We can provide a richer customer view with networks that they can use as inputs to their models to drive better performance.
Also, we have an open architecture which means they can continue to use the tools they are using today (e.g. Python, R, TensorFlow).
Quantexa CI provides a truly trusted view of all and any data (internal and external) using best-in-class entity resolution including complex relationships such as corporate hierarchies and supply chains. We provide a scoring framework to support custom and advanced analytics.
A CDP does not reach the level of sophistication and accuracy when it comes to making sense of complex data.
Quantexa Customer Intelligence can power an existing CDP or similar system or used independently.
Fragmented data leads to fragmented experiences for customers, and is a barrier to upselling, service and effective decision-making.
A Customer Intelligence solution connects internal and external data to provide a holistic, trusted view of B2C and B2B customers and extends this capability with relationships (social, family, corporate hierarchies and supply chains) to provide the full context and enable better decision-making. The result: uncovering hidden patterns in data that dramatically increase the value of insights.
A Customer Intelligence solution can:
Make you more customer-centric and data-driven
Accelerate revenue growth
Learn more about Customer Intelligence solutions.
Organizations typically start with fragmented and duplicated data, resulting in heavy reliance on manual work and guess work from Sales and Relationship teams, Customer Service and Marketing to drive revenue and ensure good customer experience (CX).
The Customer Intelligence process typically will be the following:
A true single view of all people, businesses and places is built by connecting all data.
Relationships between customers and non-customers are uncovered through contacts, directorships, investors, corporate hierarchies, supply chains, households, etc.
Analytical models are applied to score networks and identify insights. This can be done either with built-in Customer Intelligence platform capabilities or by your own analytics and data science teams using the resolved customer data and networks from the steps before.
That enables you to achieve your customer objectives such as push prioritized lists of leads into your CRM, send high propensity cohorts to your marketing automation software, dynamically personalize a customer’s online experience and more.
Learn more about Customer Intelligence.