The
system combines data on clients' banking activities, with public
data on company ownership and directorships, to flag desirable
potential clients to HSBC staff and offer ways to connect to
them through existing relationships.
Using data and artificial intelligence to try and boost revenues
is part of HSBC's broader push to squeeze more out of its large
physical network and client data, a key priority for interim
Chief Executive Noel Quinn.
"It's one of the first commercial uses of investment in
financial crime prevention, and the business we're getting in
this way is inherently lower risk and quicker to win," said
Stuart Nivison, HSBC's global head of client network banking.
HSBC declined to comment on how much it expects to make from the
new system but said the broader 'network income' initiative has
already yielded hundreds of millions of dollars in additional
revenue.
The drive is an important part of the bank's efforts to defend
its global presence at a time when some analysts and investors
are saying it should shrink or exit markets like the United
States where it makes returns below its cost of capital.
HSBC was forced to invest hundreds of millions of dollars in
financial crime compliance as part of a $1.9 billion settlement
in 2012 with U.S. authorities over the bank's failure to prevent
money laundering by drug cartels though its Mexican unit.
The system works by mapping individual customers' and companies
ties to each other and then looking for unusual patterns of
transactions or unearthing previously unknown connections
between those entities.
That system has already freed up more than 400 staff to go from
manually checking transactions and records to client-facing
roles where they can spend time helping customers, said Adrian
Rigby, chief operating officer of HSBC's trade business.
HSBC's Nivison said the lightbulb moment was realizing the tool
could be repurposed to look for 'green flags' of attractive
potential clients rather than 'red flags' of wrongdoing.
"We took our customer dataset and combined it with (Britain's)
Companies House data and turned the algorithm around to look for
attractiveness in a client, whether that be through sector,
growth of the company, and connection to existing clients,"
Nivison said.
The tool has mapped 22.5 million entities and people in Britain,
and can identify in three minutes a network of connections that
a staff member would have taken three hours to map out manually,
he said.
(Reporting By Lawrence White; Editing by Himani Sarkar)
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