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

LONDON, June 21 (Reuters) – From sending special deals on restaurants to burger-loving current members to offering anonymised credit credit card records, banks are race to monetize the huge troves of data they hold. Mining mountains of trading data to forecast stock movements; partnering with suppliers on marketing promotions and using artificial intelligence (AI) tools to speed up credit decisions are some of the area’s banking institutions are focusing on.

Craig MacDonald, mind of data monetisation at Accenture. The surge in data mining is going on against a transformed regulatory backdrop. New European Union (EU) rules released this past year allow technology companies to access banks’ customer data if they have customers’ authorization. The EU in addition has toughened its privacy laws. Companies now have to get permission before they can collect and use personal information gleaned online from people residing in the bloc. But with the extra protections even, sensitive data continues to be at risk of being exploited because many people have no idea of how they may shield themselves.

Less than a third of Europeans were aware of all their data rights and only 13 percent said they read personal privacy statements fully, according to a poll this season of 27,000-EU citizens. Banks do not disclose how much they earn from analyzing and marketing customer data or other ways where they monetize the information they keep. But, compared to the billions earned from trading and financing, the amounts produced will tend to be small.

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

So, burger-aficionados get deals at local burger fashion and restaurants fans get ads about discounts at clothing stores. The banks get a percentage of the fee charged by Cardlytics for running the campaign. Cardlytics get insights on consumer behavior that assist the merchants account and tailor the discounts and offers. Cardlytics, Lloyds, and Santander 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 shared with Cardlytics if customers choose to get retail offers. The lender said the information was shared on an anonymised basis meaning the customer’s name is changed by a distinctive identifying quantity. Lloyds declined to comment on the details of the deal. 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 certainly range for misuse still, for example, if highly-indebted people are targeted with unsuitable offers for high interest credit or loans cards. Paul Bernal, a specialist in data privacy at University of East Anglia. Ashok Vaswani, global mind of obligations and consumer at Barclays, told participants at AI meeting CogX in London this month that the bank would crunch data within an ethical way.

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Like many banking institutions, Barclays markets anonymised spending data to a range of businesses including mall operators who can see from the info that retail chains draw in the most customers and are therefore worthy of targeting as tenants. Barclays said it doesn’t share personally identifiable information and it sends privacy notices to customers through a combination of email, text message, post, and via mobile apps. It also has a full page on its website explaining its data online privacy policy. Using data to boost risk analysis, make faster credit decisions, and anticipate customer needs is particularly attractive for banking institutions seeking to cut costs.

HSBC plans to use AI tools to rake through its 10 petabytes of data – approximately equivalent 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 tap this so-called `data lake’.

JPMorgan, in the meantime, is developing a raft of AI applications to raised predict stock movements and to map and mine 3 billion transactions it grips annually. The bank hired Manuela Veloso, the comparative head of the device learning division at Carnegie Mellon School, to be its mind of AI research last year. Compared to newer, tech-focused companies, banks tend to be at a disadvantage when they look to extract value from their data – they lack in house experts and their companies are often filled with legacy IT systems. Hires for mature leaders with digital experience at financial firms have doubled year on year going back five years, regarding to London-based headhunters Heidrick & Struggles. Marcus De Luca, UK financial services practice leader at the recruiter.