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DATA ANALYTICS - QUANTEXA


DATA ANALYTICS IS THE KEY TO KYC BY DELPHINE MASQUELIER, KYC SOLUTION MANAGER AT
QUANTEXA

 * 1 week ago Posted in Data Analytics

With businesses racing to digitalise, they amass enormous volumes of data to
help their strategic and operational decisions. However, most of these huge
swathes of data exist in silos, meaning organisations struggle to extract
meaningful value.


Currently, 95% of businesses are experiencing the effects of the ‘data decision
gap’, which is the difference between the data they have and the data they can
use to bolster business-critical decisions and drive optimal results. Alongside
constantly changing regulatory pressures, this ‘data gap’ exposes them to
compliance risks . This becomes increasingly important when it comes to ‘knowing
your customer’ (KYC).

Financial institutions can transform KYC processes through the better use of
data and its analysis, enabling better spotting of both risks and opportunities.
However these organisations must first re-address their internal KYC processes.

KYC as we know it

When looking at the way risk is assessed, the traditional and most widely used
KYC model still heavily leans on ‘profile data’, which is when it depends on
specific profile characteristics of a legal entity or individual based on
categories, such as geographic locations. This method is plagued with many
inaccuracies and inefficiencies when considering all growing complexities within
the global enterprise ecosystem.

On top of this, the way many organisations still apply KYC processes is vastly
done through human manual monitoring. Despite the hard work risk analysts put in
to ensure total compliance, it is still inevitable that human capacity cannot
process the gargantuan amount of data flowing into the enterprise. Manual
onboarding, refresh and remediation processes also require big teams, driving up
the cost of compliance whilst also resulting in poor customer experience.

Aware of the race to keep up with regulation changes as well as the pressure to
digitise rapidly, most organisations are launching themselves into the dark.
Many are throwing both money and human hours at these issues without addressing
the root problem. The solution lies in smarter data analytics and context - and
the role technology plays is critical in a highly constrained cost and regulated
environment.

Understanding customer behaviour in context

To enable a more intelligent way of staying compliant and driving effective and
efficient KYC processes , whilst staying in tight control of finances,
businesses must turn to contextual methods of collecting and making sense of
data- such as contextual decision intelligence (CDI). This is based on how real
risk in any organisation often hides within indirect connections and
transactional behaviour with other entities and organisations in the network.

Businesses must build a single network picture to create a single customer view
based on dynamic layers of context from every available bit of internal and
external data. Entity resolution can help with this overall enhancement of data
analytics - the process of working out whether multiple records are referencing
the same real-world person or organisation - and implementing automation on top
of this takes it a step further.

How businesses build customer risk profiles can also provide a key to the
solution. There needs to be a major move from categorising according to 'old
school risks' to a new model of looking at the behaviour of every customer to be
able to detect changes and anomalies as risk arises. This requires a fundamental
shift from profile-based and static ID element data use, towards more
behavioural approaches.

Once behavioural risk profiles have been properly established, enterprises must
be able to continuously monitor and constantly update the data in KYC record
systems to reflect changes in information and risk profiles. By applying dynamic
network generation to emerging or changing risks associated with customers,
analysts can refresh and reassess customer risk scores in real-time, before it
is too late to act.

This moves away from the ‘traditional’ KYC processes, which could risk
enterprises missing major shifts in their customers’ activities, and forms the
foundations of ‘perpetual KYC’ (pKYC). pKYC methods boost capabilities to make
processes far more informed from an internal data perspective. This helps build
a single customer view within an organisation, which can then be enriched with
external information that is relevant to the customer to drive better awareness
of the entire value chain.

Risks and opportunities

It is unquestionable that once enterprises have the ability to better know their
customers, they can better identify risks and opportunities related to them.

Enhanced KYC processes help transactional monitoring, so that the organisation
will be able to seamlessly reveal the origin and whereabouts of funds. This can
help uncover hidden risk among customer activities, such as money laundering,
fraud detection, tax evasion and even terrorism financing. A robust KYC process
clearly helps companies avoid becoming embroiled in economic crime, providing
security to remain compliant with ever-changing regulations.

KYC, however, is not only used for enterprises looking to remain safe from
regulatory scrutiny. These processes can also increase operational efficiency
and enhance customer experiences. In the enablement of helping businesses better
understand their customers, they will consequently be able to provide them with
exactly what they are looking for. In enhancing an overall customer experience,
and thus company loyalty, businesses reap the rewards in the form of overall
business development and return-on-investment.

Looking forward

KYC remains at the heart of financial crime compliance, forming the most solid
base for other use cases across financial institutions, including regulatory
pressure, fraud detection, as well as growth opportunities. The right data
analytics technology significantly reduces the need for ongoing due diligence
reviews, making businesses more trustworthy to both regulators and customers.

Context and technology within wider data analytics is the ‘secret sauce’ to
every KYC process, as it helps organisations shift towards better
behavioural-based monitoring. It can also enable the development of a critical
‘single view’ of customers amidst the vast silos of data many organisations are
still drowning in. With this, businesses will be able to make smarter
data-driven decisions and finally close the data decision gap.




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DATA ANALYTICS - ZIZO

What does the Edge mean for IoT? Peter Ruffley, CEO, Zizo, explains how edge IoT
and analytics can provide a powerful mechanism for translating complex data
sources into a streamlined, lower cost platform with faster return on investment
and higher value. First, he considers some of the key challenges businesses face
when considering an investment in IoT.


DATA ANALYTICS - PROJECT MANAGEMENT INSTITUTE

How data analytics will supercharge productivity in the next era of project
management By Ashwini Bakshi, Managing Director of Europe and Sub-Saharan Africa
at Project Management Institute.


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Michael Queenan, CEO and co-founder of Nephos Technologies.



DATA ANALYTICS - NEO4J

Getting Better Analytics Insights with Graph-Powered Data Science Neo4j’s Alicia
Frame on one way to unjam your stalled machine learning initiatives.


DATA ANALYTICS - INTUITA

Reverse ETL – Completing the Circle Data expert Darren Timmins, Chief Technology
Officer at leading data solutions and analytics provider, Intuita, is excited by
a promising way to automatically transfer derived and enriched data back to
operational systems to drive better outcomes for both enterprises and their
customers.


DATA ANALYTICS - FYMA

The video surveillance revolution: from passive to ultra-smart video data
analysis By Karen K. Burns, CEO, Fyma.


DATA ANALYTICS - FIVETRAN

Data democratisation is the golden ticket to improving business outcomes and
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