Capital Markets innovation and the FinTech landscape

Client
servicing
Client onboarding
Client insight/
analytics
Research
Client relationship
management
Issuance, mergers
and acquisitions
Client insight/analytics
Capital markets firms have historically struggled to measure
their profitability accurately at the level of the individual client.
Root causes for this include:
• Multiple relationships between clients and firms, both by
region and by product or service.
• Challenges in generating a single view of the client, often
hampered by poor reference data.
• Complex allocations between cost centers.
• A lack of granular activity-based cost data.
• Complex cross-subsidization between divisions.
What is also clear from many of the organizations that we work
with is a growing recognition that:
• Most of the margin contribution comes from a relatively small
subset of clients.
• Some clients are not served to their full potential.
• There are currently unidentified clients that have high
future potential.
• There are some clients for whom there is no economic case
for retention, and who need to be offboarded.
• Costs can be heavily influenced by client behaviors; examples
include clients choosing to use the telephone or email rather
than post-trade portals, or making last-minute changes to
account allocations, which are rarely factored into pricing,
fees and commissions.
At the same time, today’s low-growth environment is amplifying
the need for smart customer analytics. Against this background,
we think a range of innovation opportunities present themselves
to help clarify client profitability. These include:
• Data to provide transparency on costs, such as KPIs at a client
or sub account level at each step of the transaction and client
lifecycle.
• Big Data analytics to provide contextual sentiment information
about each of the bank’s clients, for the purpose of factoring
into the “next best action” for client sales and relationship
handlers.
• Advanced Analytics on position and transaction data to
identify patterns and trends that inform the next best action.
These could provide early warning that a client is starting to
prefer another firm for a particular product or service, or that
its business needs are changing so additional or alternative
instruments might be suitable.
• Advanced Analytics could be used to identify the star clients
of the future. By understanding the attributes of the highest
performing client relationships today, and applying predictive
analytics to smaller and/or potential clients to identify their
potential, relationship managers can better prioritize where
they invest their time.
• Dynamic behavior-based pricing to encourage client behaviors
that reduce operational costs. This is a practice that has been
commonplace in areas of the “real economy” for years — for
example, in the fees charged by airlines for booking flights
over the telephone as opposed to online.
• The real competitive edge in investment banking needs to
come from powerful insights, rather than just being good at
providing commoditized services.
Capital Markets: innovation and the FinTech landscape | 35