Regulatory supervisors mandate the need for the ongoing review of customers to assess all clients’ activities and behaviours over time.
Fundamental to this is the ability to bring together disparate sets of customer-related data so that there is a ‘single view of the customer’ - not just at a snapshot in time but across the entire customer lifecycle.
Napier Client Activity Review efficiently brings together transaction data and customer profile data from Know Your Customer (KYC) onboarding systems into a single easy-to-use platform to measure risk and detect suspicious financial behaviour.
Customer behavioural analytics then give our clients a 360-degree view of every customer and the ability to analyse their behaviour in real-time, with view to identifying new suspicious patterns.
Providing convenience and the assurance of risk mitigation, Napier’s Client Activity Review (CAR) doesn’t require the complete re-architecting of a company's data infrastructure.
Napier’s Client Activity Review is designed to provide a 360-degree picture of the customer.
By drawing on KYC onboarding data, transaction data and client screening data as well as transaction monitoring outcomes, the Client Activity Review allows the analyst to determine whether the client’s observed behaviour is out of line with expected behaviour.
For example, a customer may be on-boarded as low risk but then start to exhibit behaviour more suggestive of nefarious activity once in the system.
With CAR, analysts can view real-time graphical representations of a customer’s behaviour over configurable and dynamic periods of time.
The analyst can see anomalies in multiple summaries of the customer’s behaviour, against their previous activity and against their expected behaviour. This allows deep investigations into potentially suspicious activity without having to switch between different views or applications.
By analysing customer behaviour as it happens, any necessary action can be taken when it really matters – and not several months, weeks or even years down the line.
Client reviews can be scheduled to automatically take place according to the required frequency, whether that be daily, weekly, or monthly.
Reviews can also be triggered as a result of changes in the customer behaviour, not just the risk score.
For example, if the customer’s information changes because they move to a new house or perhaps become a director of a company in a high-risk country, then this could trigger an alert for a review.
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Dramatically reduce false positives, while still detecting truly suspicious activity, with our machine learning-enabled transaction monitoring system designed to be used by non-technical business users in organisations of all sizes.
Run real-time searches on payment or transactional data against multiple watch and sanctions lists to make rapid decisions about the level of risk associated with payments beneficiaries and originators.
Screen clients or entities against designated sanction lists while leveraging a machine-learning programme and advanced fuzzy matching algorithms to reduce false positives.
Gain additional deeper insights about your customer’s activity with an automated ongoing review of all customer data - including transactions, payments and screening results - against their expected behaviour.
Perform enhanced risk assessments to generate a risk level for each client. Use these levels as part of a risk-based assessment to optimise your screening and monitoring processes.
Screen entities against designated sanctions and watch lists using advanced fuzzy matching algorithms to reduce false positives.
Ingest, enrich and analyse unprecedented quantities of data from multiple sources in real-time at a fraction of the cost (and in a fraction of the time) of legacy systems. Adding insight, whatever the sector.LEARN MORE
Book a demo and get critical insight into our unique approach,
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