From initial data discovery to business insights, breaking out of data bottlenecks requires a clear strategic vision from data leaders.

There is a crisis with data provision in the financial services today. Image by Aleutie from Shutterstock

Rigid institutional mindsets, processes and structures within heritage financial services institutions are predicted to bring down 80% of them by 2030 if they don’t embrace digital transformation, according to Gartner. Banks, in particular, have historically struggled to get value from customer data as they tend to see themselves as trustees of customer privacy, keeping possible data insights under lock and key, both for the customer as well as the business.

More than ever before, there is a sense of urgency in 2021 to democratise data post pandemic due to changes in consumer spending and the higher level of rich data being produced as a result.

Every single financial transaction that occurs today produces more data than ever before. Frameworks like the MiFID II in the EU are already in place to improve record-keeping of transactions — even communications — creating even more data points.

The value of all this data lies in being able to unlock insight in a timely manner, but before we can get to data processing and analysis, we must resolve the crisis we have with data provision.

Thanks to innovation and disruption in this area led by challenger banks, many FinTechs, traditional banks and other financial services institutions have already opened up their APIs to remove some barriers to access financial data. This kind of open banking works best when there is rapid adoption — the more businesses adopt them, the better the results. Open banking has already come a long way in a relatively short span of time, growing from 18 million users in 2018 to 40 million now.

When I enabled Lender View in my Clearscore app in December 2020, I must admit, I was hesitant to link a credit scoring application to my personal Barclays bank account. I had concerns about how my data could be used against me, but at the same time, I really wanted to see what transactions could be viewed as risky by lenders. So I took the plunge and awarded my consent to share my data (only for three months), thanks to open banking.

If this is this level of granularity and access to rich, up-to-date information that I desire as a customer, one can only imagine the business insights data leaders can gather on a macro level as more and more banks partner with each other as well as with third-party service providers.

Open banking will have to overcome a barrage of regulatory, compliance and trust issues because it enables sharing of real customer information across silos. However, there are other ways financial institutions can conduct sophisticated data analysis without compromising on customer privacy.

For some time, financial institutions experimented with anonymised data, which is simply a method to encrypt or erase identifiers that could connect an individual to stored data, which could then be shared with third parties or across borders. However, it was demonstrated that attackers could easily use de-anonymisation methods to retrace the data anonymisation process, rendering data anonymisation a no go for them.

Now the industry is gradually becoming aware of the possibilities with synthetic data, which is algorithmically manufactured data with no connection whatsoever to real data. In other words, it is fake data with no overlapping real information — synthetic data retains almost the same statistical aspects of the original data without matching any real record. It allows organisations to break down data silos to share data safely to generate business insight.

Heritage financial institutions are now able to make a synthetic copy of their data to share with third parties without compromising on the privacy of their customers while passing on the value of their data — across regulatory boundaries. If they are reluctant to move their data to the cloud — because of customer agreements, regulatory restrictions, or geographical limitations — they can now embrace digital transformation with synthetic data.

From initial data discovery to business insights, breaking out of data bottlenecks requires a clear strategic vision from data leaders working in banks, financial services institutions and fintechs. With tools like open banking and synthetic data opening up opportunities to drive innovation by connecting developers with data that was previously locked in bank vaults, the time has come to overcome reluctance to share data and eliminate siloed mentality that plagues the financial services industry.

Let’s enable a more connected digital world, with customer privacy and consent at the heart of it.