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Payments & Transactions - Robolitics

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20 Birchin Lane +44 (0) 203 006 6405
For Custodian Banks the process of performing checks on payment to meet to ensure the legitimacy of the ultimate beneficiary is a common but time-consuming practice.  

For more conventional Retail, Investment or Fintech organisations wishing to avoid becoming the platform of choice for criminal gangs to carry out money laundering or being used as a conduit for terrorist funding; the process of understanding who your customers are doing business with is becoming increasingly important.

Failure to deliver this flexibility can result in massive reputational damage and regulatory fines. 
Robolitics™ in combination with Dokstor can perform real time monitoring of inbound or out bound instructions. Performing real time checks to insure you comply with faster payment regulations or PSD2 without breaching AML requirements.

Robolitics™ Payment Monitoring Module can auto checking payments against FATF Countries, PEP and Sanction listed individuals and internal black and white lists to ensures that you are monitoring appropriately.

In addition, you can send a KYR (Know your Recipient) request through Dokstor asking for the other side to share identity data. This confirmation then enables future payments to be automatically whitelisted unless there are breaching other rules related to aggregation of payments layering or suspicious transaction.

The challenge for any senior transaction monitoring compliance manager is clear how to provide increasingly sophisticated, flexible and dynamic monitoring in real time across asset classes, and across communications channels whilst reducing cost.

Robolitics™ is a sophisticated real time monitoring platform. It uses basic rules for different types of reportable abuse. We keep these rules simple but then use A.I and neural networks pattern recognition techniques to identify potential issues and alert these to the compliance team.

We also allow you to tune the sensitivity of these alerts to align them to the real risks in the business. So that you can focus on the real risks rather than losing them in a myriad of False Positives.


Robolitics™ has been built around this problem. Focusing on leveraging the best of the old and the potential of the new. Providing Cross asset class and cross regulation monitoring for suspicious behaviours.  Designed from the bottom up to deliver a step-change improvement. Robolitics™ uses: 
Rule based behavioural model
We have a number of standard alerts based on typical risk behaviours. (Note: We can also create new alerts as new behaviour and risks become apparent through our RDK (Robot Development Kit)). These alerts can then be adjusted in real time to understand sensitivity of the rule; this we call “Machine Supported Learning”.  
Machine Learning Model
The Machine Learning model is a “trained module” that learns on the job. It provides the base functionality of alert reduction – e.g. not surfacing repetitive or repeat alerts.
Artificial Intelligence Module 
Looks at the Compliance Officers responses to alerts and again learns on the job. It Compares similar types of alerts either pre-classifying and removing, suggesting categorisation and making a recommendation, next best action, or creation of clusters of alerts so that multiple alerts can be managed faster.
Deep Learning
Neural Networks / Deep Learning focuses on looking for patterns across the all transactions and or alerts. These often appear as previously unseen issues or co-incidences.
These can then be surfaced to the Compliance Analyst rather than a simple compliance officer for investigation to identify if this is a real risk in which case the “DL” algo is retained, or if not relevant the suggested alert is removed. This process is especially good at identifying new risks or uncovering unexpected patterns.
Robolitics™ is a Monitoring, Alerting (GUI workflow) and Report platform.  It contains a complex data model, over which multiple, easily tuneable “Robots” search to identify issues aligned to traditional models of “best practice” and then uses AI to further filters, cluster and categorise these events to remove false items. 

Traditional solutions use cascading filters to monitor for behaviour whilst manage down a set of alerted transactions to a manageable set of alerts. Often these rule sets become so complex and intertwined that no one understand how they works. They become fossil histories of risks the business has faced, rather than addressing current business’ threats.
Robolitics™ contains over 30 standard ROBOTS that monitor for patterns of behaviour. This set rules can be extended using our RDK (Robot Development Kit) which simplifies the process of creating and tuning rules, enabling you to quickly create and tune rules. You can also tune these rules according to the nature of your business and market conditions to provide risk-based monitoring.

The ROBOTS then “learns on the job,” looks for transaction patterns, surfacing hidden relationships, linking alerts between parties and understanding client risks to improve the identification of real risks.

If you suspect a behaviour you can quickly create a new alert based on suspicions or identified behaviours of either clients or staff. As a result, you can be sure that repeats behaviour is identified and addressed quickly. Over time these alerts mature as the AI identifies and removes repetitive tasks.

You can also tune these rules according to the nature of the your business and market conditions to deliver risk based monitoring.

Robolitics™ also cuts investigations time on alerts by
  • Surfacing a comprehensive data set – Covering the transaction, the market, and historical behaviour. 
  • Clustering similar issues – Uses AI to group together alerts enabling them to be handled more efficiently 
  • Propose best action - based on previous responses to similar alerts. 
  • Delivers customer sensitive compliance enabling you to tune alert sensitivity to the client or staff risk profile. 

Financial Crime

Discover how Artificial Intelligence (AI) and Machine Learning can transform banking AML process. Reduce the false positives

Wealth Management

Focused on meeting the specific compliance requirement within the wealth management sector. Integration with AML Edition

Technology Overview

Its available as a Cloudera Stack based on Hadoop for high volume and real time mission critical solution with hot failover.