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Refocusing on trust and relevance Refocusing on trust and relevance<br />

Creating the client-centric capital markets<br />

business of the future<br />

Four key building-blocks<br />

Accenture has helped a number of leading capital markets firms to reshape and<br />

revitalise their client relationships. Our approach draws on our deep experience in<br />

building and optimising customer relationship value across a wide range of<br />

industries, while taking account of the unique characteristics, competitive dynamics<br />

and opportunities inherent to the capital markets industry.<br />

Based on this experience, we have defined an approach that is both pragmatic and<br />

effective. Getting customer centricity off the ground does not require a large upfront<br />

investment. Instead, a firm can make real and substantial progress by extracting<br />

its existing client data, and applying relevant, targeted analytics quickly and at low<br />

cost. The momentum behind the resulting ongoing improvement in client<br />

relationships and profitability can then be built up progressively over time.<br />

Our experience shows that four key steps can enable a capital markets firm to begin<br />

the journey towards putting clients back at the heart of its business.<br />

The four steps are:<br />

1 Conduct basic analytics to understand clients’ needs and buying behaviours<br />

2 Group clients into segments reflecting behaviour and need<br />

3 Realign your product offering and delivery channels to support client needs<br />

and profitability<br />

4 Initiate actions to enhance your parent brand progressively over time<br />

A firm that focuses successfully on all four of these areas will find it can build<br />

deeper, more durable and more profitable client relationships based on mutual trust<br />

and value.<br />

1. Conduct basic analytics to understand clients’<br />

buying needs<br />

Building better and deeper client understanding may sound like a good idea in<br />

theory. But how can it be achieved in practice? Many capital markets businesses<br />

assume the answer must be a major multi-year, multi-million pound CRM investment<br />

programme that transforms and integrates the management and analysis of client<br />

data across the business. However, our experience shows that a more pragmatic and<br />

phased approach — requiring far less up-front investment — actually has a far<br />

greater chance of success.<br />

In many cases, efforts to impose a customer-centric culture from top-down through<br />

a massive systems implementation project fail because of three challenges. The first<br />

is the siloed structure of much of the legacy IT infrastructure, with different business<br />

units unable to share information easily or effectively. The second is issues around<br />

data protection and client privacy, again preventing sharing of data. The third is that<br />

embedded ‘fiefdoms’ in the business may be unwilling to share client information<br />

and relationships that they feel belong to them individually, rather than to the firm<br />

as a whole. These same barriers have the effect of impeding cross-selling and an allround<br />

view of client profitability.<br />

Starting small: a pragmatic approach to analytics<br />

Given these issues, a ‘large’ systems implementation effort is usually not the best<br />

way forward, and will struggle to deliver. Client data may exist at many points across<br />

the business, in many formats. A more workable and effective solution may be to pull<br />

together these disparate elements of data into one place, and then conduct analytics<br />

to identify and understand the patterns in clients’ behaviours and needs.<br />

In industries where companies have hundreds of thousands or even millions of<br />

clients, this approach would be impracticable. But capital markets businesses benefit<br />

from having relatively small numbers of relatively large clients, rather than a<br />

multitude of small ones. And a comparatively limited amount of effort in pulling<br />

together the required data can produce dramatic results, enabling the firm to create<br />

hypotheses around how to improve the offering to each client, or at least clusters of<br />

similar clients.<br />

Launching a small initial pilot programme of client data analytics also brings several<br />

additional benefits. By kick-starting deeper client understanding, it can help to<br />

highlight not just patterns of client behaviour, but also the most pertinent elements<br />

of data that will help to clarify and illuminate those patterns. As more and better<br />

data is pulled in, the analytics can be iterated to progressively sharpen the insights.<br />

And the early findings can be leveraged to produce ‘quick wins’ that deliver good<br />

returns in a short timeframe, helping to sell the idea of analytics-based segmentation<br />

to the sales team and across the business as a whole.<br />

Compounding the benefits<br />

Once the iterative analytics programme is embedded and gaining momentum, the<br />

insights generated can be incorporated into the firm’s management information and<br />

incentives going forward, thus facilitating the cultural shift required. One approach<br />

for extending and embedding the programme is to build simple software that collects<br />

and analyses the client data firm various sources — thereby replicating many of the<br />

benefits of rebuilding the CRM infrastructure, but at a far lower cost and much<br />

higher speed.<br />

In the longer term, the benefits of better client understanding will be felt throughout<br />

the organisation. By providing senior management with insights into why customers<br />

buy particular product and service offerings, it enables the business to regain control<br />

of client understanding and insight from the fiefdoms. Furthermore, unifying the<br />

client data across products and sales teams enables individual client profitability to<br />

be tracked, managed and improved. And if regulators ask why a particular product<br />

was sold to a particular client, robust information is available to show why the<br />

product purchase was in line with the client’s needs and behaviour.

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