How advanced analytics can impact financial services

The same thing is (fortunately) happening in the banking industry and other financial services are catching up too. Nowadays you might be living in a small, non-EU country and still have advanced mobile banking, access to online banks such as Revolut or N26 where you can set up account in 60 seconds, the ability to photograph your car accident and make a claim with your insurer, or to invest some money in stocks listed on the NASDAQ from the comfort of your couch as a small-scale retail investor.
In 2020, whether you are a retail bank, investment bank, broker, exchange, wealth manager, insurer, fintech company or even a central bank or regulator, data has a huge impact on your business in several segments.

Four key areas where data can add value in the financial services sector

Customer intelligence

The segment most visible to end users can be referred to as customer intelligence. Gathering data from various data sources such as mobile banking apps, social media, GPS movements (if the customer agrees to this), and blending it into machine learning algorithms for smart segmentation can open ideas beyond pure demographics on how to best position your products, and how to position them at the right moment to the right segments of your customer portfolio.

Well-designed products in this area could really change the perspective of how young generations see banks and insurance companies. For example, I would love it if someone were to take and analyse data from my Garmin watch, and then could provide me with health insurance offers according to how active I am and would allow me to accept/sign up for these via my mobile banking app.

Reimagine business processes

The second area of potential improvement is basically to reimagine business processes to boost efficiency in some business areas. This segment relies on data that companies already have, but are not using it in the right way or are not presenting it to the right people. For a sales rep to boost their performance, they need to have a few simple drill-down sheets on their BI tool on their mobile phone.

Forcing them to come to the office, export something and then create a pivot table out of it, does not boost performance. In all companies, all departments could make better use of the data they have with the right business intelligence tools, whether we speak of measuring call centre performance, boosting sales teams, or having a clear daily view of product profitability instead of a quarterly view.

New business opportunities

The third area which heavily relies on data analysis is often neglected in companies because it sometimes requires the blending of third-party data, but it can also lead to new business opportunities. For example, correlating the average deposit amount in your bank and average purchasing power by geographical regions can give a clear insight into which region is under-utilised or maybe requires more education on savings. Also, there may be a whole segment of potential customers sniffing around your website who just come and go, and by learning from their behaviours on your website, you can easily optimise the path so that, for example, buying travel insurance takes 2 steps instead of 6 steps, which would lead directly to new customers in your portfolio.

Risk management

The last segment is probably in first place in many corporate presentations, and this would be the segment of risk management. This is the area where companies are well developed in terms of delivering various simulations and checking credit quality or just, in general, maintaining compliance. However, as the amounts of data grow, so does the challenge of analysing that data and spotting fraudulent transactions, for example.