iso certified

Regulatory Compliance

Graph-based Fraud Detection & Prevention

Anti-Money Laundering

High Volume Transaction Monitoring

Customer Retention Management

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Transaction monitoring, fraud prevention, AML, CFT features

Tx monitoring of raw / curated data streams
Streaming analytics
No code rule authoring – stream & system
Rule testing environment: transparent & auditable
Static and dynamic rules
Integrated graph pattern analytics – real-time
Graph visual analytics
Event / rule break analysis for ML modelling
Advanced reporting & next best action orchestration

Bringing graph intelligence to financial services

The financial services industry has a greater requirement for regulatory compliance as it is a major target for nefarious digital activities. The sophistication and ingenuity of modern online criminals means they are operating under the radar of conventional systems to defraud and money launder at an alarming rate. More capable, next generation technologies are required to counter these ever-evolving challenges.

Our financial services solutions have a proven track record in highly complex transactional environments for compliance, AML and fraud detection, as well as for providing advanced analytics.

Our graph intelligence platform, Locstat LightWeaver®, is perfectly suited to support your advanced analytics, data intelligence and regulatory compliance needs across a range of solutions including:

  • Next generation fraud prevention, AML, prevention of terrorism financing and regulatory compliance powered by graph technology.
  • Big data transaction monitoring and streaming analytics leveraging graph-based AI and machine learning to augment our dynamic and probabilistic rules engine.
  • Graph-based behavioural account monitoring and anomaly detection.
  • Customer retention and churn mitigation.
For banks; payment gateway providers; transaction switching gateways; voucher-based vending technology; fintech organisations; and insurance providers

Regulatory compliance

With the explosion of widespread digital and e-commerce transactional activity, compliance is increasingly becoming a key determinant of risk and success.

Regulatory mandates imposed by institutions, governmental bodies and Reserve Banks, require FSPs to comply rapidly and in detail in order to continue operating. This capability is provided by regulatory compliance technology (RegTech). As the transaction complexity and the sophistication of criminal online activity increases, legacy technologies struggle to provide the right levels of compliance support.

Locstat LightWeaver®, our graph intelligence platform, with its unique ecosystem of graph database technology, complex event processing, ML and high-performance computation framework and data orchestration capabilities, provides an efficient, light touch with a powerful RegTech solution for FSPs.

Fraud detection, prevention and investigation

“Understanding that fraud is an uncommon, well considered, imperceptibly concealed, time-evolving and carefully organised crime” (Baesens et al: 2015) in many types and forms, makes it a difficult problem to solve without the appropriate technology.

Graph database technology, supplemented with rules, event processing and a machine learning framework, provides a powerful capability for monitoring and preventing fraud in real time.

The Locstat LightWeaver® graph intelligence platform provides next generation fraud detection, prevention and investigation solutions across Gartner’s 5 layers of fraud.

Case Study for Real time high volume transaction monitoring

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You can’t hide from graph!

Anti-money laundering and prevention of terrorism financing

Graph technologies and analytics are game changers in Anti-Money Laundering (AML / CFT) operations and solve many of the problems created by the use of legacy technologies e.g. RDMS. Mining a directed transaction graph for specific patterns provides important indicators to money laundering and the hidden financing of terrorism.

Graph visual analytics displays the connections and flow between entities, parties, customers, accounts and transactions to rapidly facilitate sense-making within complex financial systems for AML / CFT analysts.

Graph models can be primed with third party datasets such as: Politically Exposed Persons (PEP) Lists, OECD Sanctions Data, Interpol Red Notice lists, public registries and leaks databases.

Locstat LightWeaver® combines graph-based ML, complex event processing, graph visual analytics and extensive reporting capabilities within a comprehensive graph intelligence platform. This enables AML / CFT analysts to monitor for patterns and illicit behaviour shifts within a complex transactional environment.

High volume transaction monitoring

Financial services data predominantly consists of structured transactions, which need monitoring in real-time. Locstat LightWeaver® has powerful transaction monitoring and streaming analytics capabilities that span multiple, different data streams.

Screengrab of high volume transaction monitoring

Our ability to pipeline and process raw data streams and create new, curated data pipelines expands this transaction monitoring and event processing capacity. Equally powerful is Locstat’s feature engineering of data streams, which facilitates the creation of enriched data streams for further monitoring, event processing and analytics.

Capabilities include: Stream operations and transformations; event stream windowing; tumbling and sliding; event time; processing time; ingestion time; time stamps; counting and various operations including Join, Output, SQL and ML.

Create, define and manage transaction data pipelines and rules


View and access all native data and transaction pipelines streaming into CEP / rules engine.


Engineer features and create and view curated data pipelines for streaming into Locstat LightWeaver®.


Define, build, test, simulate and deploy complex rules in a no-code intuitive interface without interfering with operational systems.


Leverage graph-based AI and ML to augment dynamic and probabilistic rules engine – embed ML models into the rules engine.

Graph visual analytics

Complex financial systems are easier to understand when visually represented. Graph visual analytics rapidly facilitates sense-making and allows analysts to drill down for a granular perspective.

Mining a directed transaction graph for specific patterns provides important indicators to money laundering and in certain instances can also indicate market manipulation within a trading network.

Screengrab of Graph visual analytics

“Human-in-the-loop” and automated event responses

Fraud and compliance teams can engage with interactive rule-break dashboards and individual or group rule-break dialogues to provide a “human-in-the-loop” response with rule breaks. This interaction can close, add notes / context, elevate, forward or follow additional links to rule breaks. The full process is logged for audit requirements.

You can also model and capture responses and action lists to complete when interacting with rule-break tiles.

Any automated responses can be pushed back into the technology architecture via APIs and message queues to close accounts or trigger required responses.

360° situational awareness through dashboard environment

Screengrabs for rule breaks situational awareness a through dashboard environment

To learn more about graph powered, contextual recommenders and segmentation

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Customer retention management

Having a strong customer understanding and retention strategy in any financial services industry is as important as a retailer keeping their consumer on brand.

Increasingly, with the variety of financial services products available, knowing, understanding, engaging with and retaining your customer is becoming crucial to maintain a competitive advantage.

Our ability to unify multiple, disparate data sets and graph a customer’s transactional activity allows you to create a customer 360° paradigm. Combine this with features such as dynamic segmentation, recommender and NLP engines, message sequencing and ML model operationalisation, all working in tight conjunction with the graphed transaction data and CEP engine, and you have a powerful customer analytics and retention tool for FSPs.

Case study


distributed graph database


data Tx per day


data pipelines and streams


additional curated data pipelines and streams

Case Study for Real time high volume transaction monitoring

View Case Study