Predictive analytics is poised to make banking more client-centric, profitable and streamlined, says IBM.
Lesley Plaistowe, partner and head of financial services at IBM South Africa, says predictive analytics is set to revolutionise banking on several fronts.
“Because advanced analytics gives you richer insights across a variety of platforms, you are able to not only customise banking products to meet the current needs of individuals, you can also accurately predict fraud, avoid the cost of false fraud positives, accurately forecast income and balance sheets across a range of variables, and so cut operational costs.
“In short – analytics makes banking better, and delivers a return of easily 20 times the investment in the technology,” she says.
Plaistowe says that South African banks are looking to advanced analytics as part of their long-term strategies, but most have been slow to adopt and maximise the potential of the technology.
“It’s a client-centric game now. Customers, particularly the younger generation, expect their banks to know who they are, what their lives are like and what products they need,” she says.
“However, banks still tend to segment their customers in broad sweeps – by age or income group, for example. This does not take into account the real profitability of each customer, the stage of life they are in, and what products they are likely to need in the short and long term.”
Plaistowe points out that internal historical data on customer banking patterns may indicate that when a customer buys a diamond ring, for example, they will likely incur costs of a wedding in the short term, and start looking to home loans or life insurance in the longer term.
“If you overlay this historical data on current spending patterns of customers, and perhaps incorporate social media data such as an engagement announcement, you are able to offer that customer the products he or she needs at exactly the right time. This significantly improves the chances of uptake.”
Better targeted marketing also allows banks to optimise their marketing spend, she adds. “You don’t want to spend a million on marking and get ten new accounts. You want to get real bang for your buck. If you are offering the right products to the right customers at the right time, your marketing will see a far greater return on investment.”
Another benefit of predictive analytics is countering fraud and cutting the cost of false fraud positives, says Plaistowe. Credit card companies have been successfully flagging fraud and eliminating false positives for years, but banks have been slower to successfully reduce the cost of combating fraud on transactional accounts.
“By using advanced and predictive analytics, they are able to incorporate information, such as a particular customer always goes on holiday to Cape Town in December, and so cut the cost of calling that customer to check a transaction that occurs in Cape Town during December.”
Using advanced analytics, banks could also get smarter around budgeting and forecasting, she says.
“They can start with their historical databases, identify patterns of behaviour, marry this to the economic climate and more accurately forecast growth and losses in future. This would allow them to become more proactive in managing their income statements, balance sheets, headcounts and branch costs,” she notes.
“In South Africa, banks are slowly becoming aware that there are potential benefits to advanced analytics, but they don’t yet realise the value of the information they already have access to. By marrying this data to unstructured data in social media, insights from mobile banking, and external market data, they could be delivering more targeted, more successful service to customers at a lower costs,” she says.
