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Perspective:
Perspective
09 Aug 2020
15 minute read

Using data to grow with confidence

There have been long standing, well intended plans to develop a more proactive approach to the detection, quantification and management of risk - and for Risk and Compliance functions to drive more value into their respective organisations.

Rajat Saigal

More about the author

Rajat Saigal

Deloitte - Australia
Rajat is a Partner in Risk Analytics under Risk Advisory in Sydney, Australia. He currently leads the establishment of the Risk Analytics based Managed Services for Conduct. While establishing the practice, he remains responsible for taking complex industry scenarios/challenges and transforming them into simple yet relevant data and technology solutions. His experience of working in professional services, as well as the industry, helps him drive the adoption of data an enabler for business outcomes. Prior to moving to Sydney, Rajat was a part of the Risk Analytics team in Deloitte South Africa. Outside of Deloitte, Rajat enjoys hiking on trails around the shores of Sydney.
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In many cases, the execution of this strategy has been hampered by heavily manual processes, an increasingly complex regulatory landscape, and pressures to address emerging and disruptive risks. In some sectors there has also been an unhelpful distraction from fixing issues of the past.

While many business divisions have adopted automation, digitisation and data analytics to support their growth, this has not always been possible for Risk and Compliance functions.  Yet, the holistic transformation of the risk function using data and technology capabilities can yield many benefits.

To begin with, let’s consider some of the needs that are driving this transformation:

  • Identifying weaknesses and deficiencies across the product lifecycle more efficiently can reduce the potential for customer remediation
  • Providing analytical insights across customers and portfolios using data and technology to

1. Identify the potential risks in the ‘unknown’

2. Prevent revenue leakage due to system or process issues; and

3. Build a holistic picture of interactions and behaviours, not just identifying the needle in the haystack

  • Building trust and confidence in organisations by delivering on contractual obligations and customer promises, delivering ‘true to label’ product pricing, fees, and features
  • Driving enhanced customer experiences by anticipating and responding to customer complaints and issues; and
  • Monitoring new and changed regulatory requirements
What are the next steps?

Let’s assume that you have a well-defined risk framework, which clearly and simply sets out the various classes of risk and identifies non-negotiable areas of compliance such as regulatory and prudential requirements.

A simple and pragmatic first step is to overlay your risk framework to your customer journey lifecycle and identify points of issue concentration based on past thematic reviews, known risk areas, customer complaints or incidents.

This typically results in a heatmap of areas of concern (Sales Practice, Sales Quality, Product Design, Product Servicing) across the customer journey and their interdependencies, which can be used to prioritise a data-led deep dive into each of the areas of concern to obtain a clear picture of:`

  • What occurred, using descriptive analysis
  • Customers, products or employees impacted by the issue
  • Thematic root cause issues through extrapolation
  • Potential contagion of impacted behaviours to other products or customer groups; and
  • Fit-for-purpose monitoring requirements to detect early-warning of similar issues recurring.

By starting small, and considering the foundations such as data, technology and the range of stakeholder expectations, this can evolve quickly to shift the view on risk from incident-centric to a more holistic picture, and from reactive to proactive capability:

We are helping clients to develop and implement this transformation journey using a data-driven, forward-looking risk detection and monitoring approach, leveraging the following:

  • Data Accelerators – a well-defined catalogue of relevant data management and transformation models which can bring together new and varied data sources, including unstructured and voice data, into a single conduct-oriented architecture
  • Platforms – dedicated environments and technologies on which we build, process and visualise data in a reliable and consistent way
  • Artificial Intelligence – weaving together various aspects of AI like NLP, Machine Learning and voice analysis  to expedite the learnings.

We integrate this with deep risk, regulatory and compliance capability, and our experience across industry, to help our clients manage what is important, know where to look and help detect and mitigate risks they didn’t know they had. Some recent examples include:

  • Using voice analytics to identify patterns of mis-selling or pressured selling techniques, which compromise sales quality and customer outcomes;
  • Combining NLP and more traditional data analytics identification of patterns of miscommunication or mis-alignment between product terms and product performance; and
  • Applying machine learning to customer complaint data to identify patterns of systemic financial, compliance and operational risk.

Are you thinking about whether you are ready to start your transformation journey? We recommend you start by asking yourself these questions:

  • How are good customer outcomes being measured, delivered and improved across the customer journey?
  • What learnings from the past can be leveraged as a foundation for future monitoring activity? and
  • How might a more sophisticated use of data and technology drive a more effective and efficient approach to risk management?

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