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How can data solve challenges for banks?

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Unlocking the value of a bank’s data can create benefits right across its business - from operations and maintaining regulatory compliance to boosting customer satisfaction and being more competitive. Here is a rundown of the key areas and use cases where data can help banks perform better:

1. Operations

One area where data can support more efficient operations is with payment reconciliation. This involves the payments processor, typically a clearing bank such as ClearBank, and the core banking system where the payment will be recorded on the ledger, with banks then having to reconcile the two to ensure the payments processor’s view of what happened matches the core banking system’s view of what happened. Traditionally this would mean at the end of the day, a bank’s accounting department would receive a file from the payments processor and a file from the core banking system, and there would be a custom batch process which compares the two files to ensure they match in terms of monetary volume and value. With an event-driven cloud-based core banking approach, the payments processor can emit an event that outlines the transaction that has taken place, which can then be instantly matched with the entry on the core banking system, meaning reconciliation can happen in real time instead of at the end of the day

2. Compliance

Ever-tougher regulatory requirements for banks are increasing the need for risk and compliance teams to find more cost-effective ways to maintain regulatory compliance. Take customer addresses, for example. In a worstcase scenario, some banks may hold several different addresses for a single customer. If that customer has taken out a consumer loan, regulators require that the bank must send out a letter summarizing the annual interest the customer is being charged. If the customer doesn’t receive that interest-rate summary, then the bank is disentitled to any interest charged and must repay the balance to the customer. So if a customer has moved house and they update the address on their current account, the customer might forget to do it for the loan account. Because a bank’s internal systems don’t talk to each other, the bank is now noncompliant for the customer’s loan.

In the past, some banks have tried to fix this by grouping all the customer records together and then manually trying to figure out which address is correct - sometimes involving hundreds of employees sitting around manually sifting through addresses and inputting data.

In an event-driven banking system world, this scenario can be avoided by having just one master address that is published as an event and then subscribed to by other microservices so there is no need to update customer address records for every single product - there is just one single source of truth that all parts of the bank can link to. If a customer then changes their address, all the bank needs to do is update the master address and all the other microservices that subscribe to that master (e.g. statements) will automatically be updated.

3. Fraud detection

Another area where data can help banks improve the customer experience is with fraud detection. While most banks have the ability to do real-time fraud detection already (they can flag straightaway if a transaction looks suspicious), they often struggle with siloed data and therefore having to base fraud decisions on potentially incomplete data. Take an example where a customer has travelled to New York for a weekend of shopping. A traditional bank may see the customer’s elevated card activity on Fifth Avenue and put a fraud block on it because it is a departure from their usual spending behavior. Meantime, the customer’s banking app probably knows the customer is in New York, but because that data is stored in a different location and won’t be extracted until the daily batch process is completed, the two data points can’t be combined. Using an event-driven core banking system where data is streamed to one single integration point means those transactions will be married with the app’s geo-location in real time, reducing the need for false fraud blocks - the last thing a customer will want if they are travelling overseas.

This is one advantage of next generation core banking systems: customer data is stored securely in the cloud, enabling banks to access more joined up information on customers and act on it accordingly. Legacy technology systems also typically can’t fully utilize the new payments messaging standard ISO20022 and therefore end up with an incomplete view of what their customers are doing.

4. Competition

Smarter use of data can give banks a competitive advantage by helping them create better products that actually benefit customers, such as personalized rewards (spend £50 a month at your three favorite merchants and get £5 cashback, for instance). Banks could also offer products based on lifestyle events (if a customer’s income drops because of unemployment, they could offer the customer a mortgage holiday) or offer rewards based on merchant spend trends (similar to Tesco’s Clubcard vouchers).

Sharing data across different business functions can also give banks a 360-degree view of their customers, enabling banks to build up a more detailed profile of who their customers are and what products and services they use or might be interested in. That can help banks provide more relevant offers to customers that in turn can increase loyalty and wallet share.

The ability to make changes faster with an event-driven core banking system also means that banks can respond rapidly to initiatives launched by their competitors. If a rival bank puts out an enticing cashback or savings rate, the offer can be matched or bettered quickly, reducing the risk of losing out on business. In a legacy world, those changes could take weeks or even longer to process, by which point the business may have taken a sizeable hit (either directly or through lost opportunity).

5. Meeting Customer Expectations

Customer expectations for more personalized banking experiences is an area that is entirely dependent on data. Often that can require banks to be able to make location-based realtime offers—something that is not possible when they rely on end-of-day batch processes to extract and analyze customer data. Take Indian digital bank Jupiter. It alerts customers to cashback offers based on participating merchants located nearby and then credits any cashback due in real time - that way customers get progressive rewards rather than just receiving a lump sum at the end of the month. By being able to access customer data in real time, banks can act on that information immediately. Maybe the customer has received a significant pay rise that unlocks certain products or it might be that they have just taken out a loan with another provider, in which case their loan eligibility might need to be revised or removed.

The availability of that data also makes broader real-time communications possible to proactively engage with customers at the point of need - whether it is merchant offers based on location data or product offers based on imminent purchasing decisions. A letter in the post two weeks later is not going to cut it in a digital banking world.

“Such technology allows banks to respond more rapidly to changing market conditions or issues with their existing products.”

This article is an extract from our whitepaper "The Power of Data". To read on, please download the full whitepaper via the button below.

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