Friday 29 September 2023

Customer Intelligent Platform ‘key for Saudi PDPL compliance'

DUBAI, June 7, 2022

By Naresh Kurup

The Middle East’s data protection regulatory landscape continues to evolve with Saudi Arabia’s newly published Personal Data Protection Law (PDPL) - a first of its kind mandate.

PDPL regulates how businesses collect, process, and store personal data about individuals residing in the country. The data protection rules were published earlier in the government’s Official Gazette on September 24, 2021, and is scheduled be effective starting March 17, 2023.

PDPL applies to entities (including public and private companies) and to their affiliates, that process the personal data of Saudi residents, to provide them goods or services. It also applies to entities operating outside Saudi Arabia, that process the personal data of Saudi residents.

The new regulation urges organisations, especially banks, to be responsible custodians of their customers' data and automate privacy and security operations. To operationalise compliance, banks need to have in place a real-time, enterprise-wide customer intelligence framework to keep pace with the current digital landscape. While there are several solutions that help comply with global privacy regulations, they are confined primarily to siloed channel-specific functions.

Let’s examine customer intelligence more closely.

Customer intelligence is the collection, identification, and analysis of customer data, behaviours, and activities that help banks deliver great customer experiences and make informed decisions. It involves identifying individuals across channels and applications at every touchpoint to deliver the most timely and relevant next best offer and personalize it at a granular level.

Customer intelligence links everything you know about a customer and applies data science and enterprise analytics so you can answer complex questions that help better understand what customers and prospects want. It enables tailoring those customer analytics to the unique perspectives of marketing, sales, service, and other departments so they can visualise relationships, hierarchies, networks, and households in the ways that best meet their strategic needs.

While banks store and use customer data in almost every system across the enterprise, that data tends to be incomplete, inaccurate, and siloed. Therefore, that data isn’t as useful as it could be for driving superior customer experience. To achieve the highest impact and greatest value from vast amounts of customer data, companies need to turn what they know and can infer about their customers into a true 360º customer view.

What constitutes a ‘customer intelligent’ platform?

A customer intelligent platform is the next step in advanced customer data management. It connects business users in sales, marketing, commerce, and service, linking billions of data points across disparate data sources to uncover insights.

It leverages AI and ML to understand, resolve, and evaluate structured and unstructured data across the banking enterprise, including:

  • Resolving and de-duplicating core master data about prospects, customers, accounts, locations, transactions, preferences, and associated reference data
  • Matching data entities and new record types
  • Enriching the data with inferred or derived indicators such as engagement, sentiment, value, and journey
  • Allowing a wide range of users to perform complex analysis via an easy-to-use interface
  • Generating multiple unique customer views in real time

A ‘customer intelligent’ platform delivers a single customer view that enhances both customer experience as well as business agility. Adding intelligent process automation helps reduce customer friction points by streamlining core data-driven tasks, allowing tracking and measuring every stage of the customer journey across a variety of use cases.

What insights do a real-time, cross-channel Customer Experience Management Platform deliver?

Using a real-time CEM platform to identify patterns in individual customer behaviours enables banks to put specific events in context, making it easier to identify unusual or suspicious activities that might indicate fraud or assess other types of risk, such as bad debt, in the broader context of what they know about the customer.

Banks can also use aggregated customer data to see and recognise new fraud techniques as they emerge. And by combining individual and aggregated data, banks can predict churn and determine which actions are most likely to retain which individuals. This allows banks to make the most cost-effective offers, limit offers to customers who are likely to be considering leaving, and design effective loyalty programs.

While many banks have invested heavily in analytics, they know that they must also invest in data governance and data management to avoid the risk of basing decisions on bad data leading to bad results.

To deliver more automated, personal, and predictive services that customers expect, banks require an AI / ML-driven Customer Experience Management platform to manage and analyse data from multiple disparate sources at volumes and speeds humans simply cannot match.

AI is also necessary to automate back-office processes and customer-facing interactions necessary to deliver accurate and personalized omnichannel digital experiences.

These customer expectations are driving banks to explore how best to implement a customer intelligence platform to achieve insights into individual customer behaviour.

Contextual data about where customers are in the buying process as well as in their broader lives, helps banks further tailor end-to-end customer experiences, from marketing offers to sales interactions, in person or online, with goods or services, after the sale and for renewals.

The more accurately banks can identify and eliminate friction points in their internal and external processes, the better they become at creating experiences that deliver what customers want when and before they know they want it.

A real-time, cross channel Customer Experience Management Platform synchronizes intelligence from across the banking enterprise and delivers the essence of the collective wisdom in the proverbial ‘moment of truth’, within the short transaction window, when the customer is the most receptive.

The platform understands that every banking customer is unique and provides the ability to offer individualized customer experience across all channels and communication. It has the ability to analyze and interpret every transaction intelligently and in real-time, which results in a banks conversations, services and products being highly relevant and contextual for the customer.

Besides increased revenue across channels through contextual cross-sell/upsell and enhanced Customer Satisfaction & Net Promoter Score an intelligent CEM platform helps reduce Customer Turn-Around-Time (TAT) and increase employee productivity.

From delivering instant contextual intelligence across all banking channels to powering every customer interaction with complete customer understanding to deriving customer insights from multiple backend systems digested in real-time to empowering employees to providing superior, timely service to customers in every interaction, a robust customer intelligent platform delivers advanced customer experience management. Imperative therefore for Saudi Arabian banks to have in place an advanced enterprise-wide, customer-centric well before the PDPL comes in to effect.

* Naresh Kurup is Chief Brand Officer at Clari5 (CustomerXPs). With offices in Singapore, Dubai and India, the company is a category leading customer experience management and financial crime management product innovator for global banks. The company’s 'human-brain-like', 'central nervous system' approach helps banks elevate customer experience as well as combat financial crime (transaction fraud & money laundering), in real-time across all channels by synthesising intelligence from across the banking enterprise and delivering precise contextual insights to stop fraudulent transactions, within the short transaction window.



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