I return this year to a topic of last year’s Innotribe at Sibos – Big Data. Data is not going away. It continues to be talked about more and 
more, whether it is about the volume of data, the speed it is growing, or the different varieties and types of data and information that is being aggregated, compiled, or analyzed.
As we move from an era of automating transactions to the era of data, the information challenges banks face are increasingly around understanding and creating intelligence from information. Areas like regulatory compliance, customer insight, or real-time offer management are real data problems. The next wave of value creation is likely to come from creating more understanding, insight, and wisdom from this data to better protect the bank or find new customer segments to drive revenues.
Here are my 7 rules to follow when embarking on a new data project:
- Good data is key. For all the amounts of data we collect having less but clean data is the critical bedrock to any analysis. Flawed data leads to flawed discussions whereas clean data leads to confident decisions. Banks need to invest in data infrastructure to provide reliable information to the risk, compliance, and customer applications.
- The faster you analyze bank data, the better the predictive value. Since there is time value to banking data, the industry is moving from batch to real-time data. Value is created by making new offers in real time and risk exposure is better predicted and avoided if analysed in real time.
- Maintain one copy of your data. Your data may become less reliable and accurate the more you copy and move it. Further the cost of IT infrastructure increases when holding multiple copies for different applications.
- Use more diverse data, not just more. Value is increasingly being created using external social, risk data, or payment traffic data. It is not just the internal sources that are creating the value for decision makers but also new diverse sources.
- Data has value far beyond what you originally thought. As we add new sensors in networks, applications, and gadgets, data previously seen as useless has new value. Payments traffic data in aggregate can give a strong indication of the economic health of an industry segment or an economy. Analysing payment traffic data at a granular level can also lead to new services opportunities.
- Put data and humans together to get the most insight. It is an art not a science sometimes. Visual and geospatial information can reveal new patterns in data. Teams analyzing data from different “creative” domains can see connections and insights not seen by an IT team with analytical skills that can lead to better decisions. This requires a new generation of easy to use management information tools with stunning visualizations and gesture based searching that puts power of data in the hands of decision makers.
- Solve a real banking pain point. It is critical is identify the real business value that can be created by reducing the time to collect and analyze data, and then make decisions that create new value. Banks can reduce losses through real-time risk management and improve cross selling conversion rates by having a deeper and immediate view of transactions, thereby leading to a higher return on investment for projects. Take the time to identify the critical business issues to address and drive fact-based decision making in your bank.
If you have other rules that Big Data project teams should follow, please add to the comments section.
There are plenty of challenges that remain, not least of which is data governance and security of holding so much data in the bank. However, looking into the future, Big Data creates ample opportunity to improve productivity, accelerate innovation, and create business value.
We will be exploring these rules and sharing customer experiences at Sibos 2013 at the Welcome to the Age of Big Data session on Wednesday, 18th September at 9:30 a.m. If you are planning to be at Sibos and would like to attend, come see us. I look forward to meeting you there!