Dollars In The Detail; Banks Pan For Gold In ‘data Lakes’

Dollars In The Detail; Banks Pan For Gold In ‘data Lakes’

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LONDON, June 21 (Reuters) – From sending special offers on restaurants to burger-loving current account holders to offering anonymised credit credit card records, banking institutions are racing to generate income from the huge troves of data they keep. Mining mountains of trading data to anticipate stock movements; partnering with retailers on marketing promotions and using artificial cleverness (AI) tools to try and speed up credit decisions are a few of the area’s banking institutions are concentrating on.

Craig MacDonald, mind of data monetisation at Accenture. The surge in data mining is happening against a changed regulatory backdrop. New European Union (EU) rules released this past year allow technology companies to gain access to banking institutions’ customer data if they have customers’ permission. The European union has toughened its privacy laws and regulations as well. Companies will have to get permission before they can gather and use private information gleaned online from people living in the bloc. But with the extra protections even, sensitive data continues to be vulnerable to being exploited because many people are not aware of how they may protect themselves.

Less when compared to a third of Europeans were aware of almost all their data rights in support of 13 percent said they read personal privacy statements fully, this season of 27 according to a poll,000 EU people. Banks do not disclose how much they earn from analyzing and marketing customer data or different ways in which they monetize the information they hold. But, in comparison to the billions earned from trading and lending, the amounts generated will tend to be small.

Benjamin Ensor, an analyst at Forrester. Tie-ups with retail firms is one way banks are monetizing their data. Customers of Britain’s Lloyds and Spain’s Santander can get special deals from a variety of retailers after the banks joined an electronic loyalty scheme run by US-based data advertising company Cardlytics. The plan uses spending data to provide customers discount rates at shops they already regular or that are in their neighborhood.

So, burger-aficionados get deals at local burger restaurants and fashion fans get ads about discounts at clothing stores. A percentage is got by The banks of the fee charged by Cardlytics for running the campaign. Cardlytics get insights on consumer behavior that assist the retailers account and tailor the offers and discounts. Cardlytics, Santander, and Lloyds declined to comment on what percentage of the fee banks get. Campbell Shaw, London-based head of bank partnerships at Cardlytics. Bank or investment company clients have to enroll in the rewards program.

A spokesman for Santander said their customer spending data was only distributed to Cardlytics if customers choose to receive retail offers. The bank said the information was shared with an anonymised basis indicating the customer’s name is replaced by a unique identifying number. Lloyds declined to touch upon the details of the offer. Its online privacy policy said the plan would use customers’ mobile location data only with their permission.

Even with the tougher rules around big data, privacy experts warn there is still scope for misuse, for example, if highly-indebted people are targeted with unsuitable offers for high interest credit or loans credit cards. Paul Bernal, an expert in data privacy at University of East Anglia. Ashok Vaswani, global head of consumer and payments at Barclays, told participants at AI meeting CogX in London this month that the lender would crunch data within an ethical way.

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Like many banks, Barclays markets anonymised spending data to a range of businesses including shopping mall operators who can see from the info that retail chains draw in the most customers and are therefore worth concentrating on as tenants. Barclays said it generally does not share individually identifiable information and it sends privacy notices to customers through a mixture of email, text message, post, and via mobile apps. In addition, it has a page on its website detailing its data privacy policy. Using data to improve risk analysis, make faster credit decisions, and anticipate customer needs is appealing for banks seeking to spend less particularly.

HSBC programs to use AI tools to rake through its 10 petabytes of data – roughly equal to the storage space capacity of 2 million DVDs – from investment banking clients in 66 countries. Europe’s largest bank or investment company has struck a deal with Element AI, a Canadian company, to help it touch this so-called `data lake’.

JPMorgan, in the meantime, is developing a raft of AI applications to raised predict stock goes and to map and mine 3 billion transactions it manages annually. The bank hired Manuela Veloso, the head of the machine learning division at Carnegie Mellon University, season to be its mind of AI research last. In comparison to newer, tech-focused companies, banks are often at a disadvantage when they turn to extract a value using their data – they lack in house experts and their companies are often filled with legacy IT systems. Hires for mature market leaders with digital experience at financial companies have doubled or on year for the last five years, relating to London-based headhunters Heidrick & Struggles. Marcus De Luca, UK financial services practice innovator at the recruiter.