In a modern financial services organization, big data technology is not a commodity, it is a necessity. It allows the company to capture, integrate and look through vast amounts of information in real-time. Some forecasts* claim big data in the global financial market will grow at an average annual rate of 35% in the next years.
The top four US banks each spend between $7 billion and $10 billion a year on technology, according to a tech firm quoted by the Wall Street Journal. But technology is not a goal per se when investing in big data. Companies do it to improve business results and foster sales. And in fact, an Aberdeen study found companies that deploy big data analytics report better sales results across the board.
Financial services companies work with vast amounts of highly sensitive, confidential information. They must store this data safely and use it appropriately and legally.
Also, in many sub-segments of the industry, business greatly depends on the accuracy of sales forecasts. In some cases, a minuscule 0.1 error or variation can cost the company lots of money.
Financial companies cannot afford leakage, errors, or flawed decisions based on inaccurate data.
The Three Vs of Big Data
In a detailed report about the deployment of big data in financial services, PWC identified three attributes that new data management capabilities in the sector must accommodate:
- Velocity – process data faster than their competitors
- Variety – support structured, unstructured (social media data explaining customer behavior) and semi-structured data (trade messages, template reports)
- Volume – tackle enormous amounts of tick data.
With these qualities in mind, there are four main areas where big data can make a difference in a financial services sales organization:
1. Customer Intelligence
The Web and social networks are generating more customer behavioral and demographic data now than ever before. If you put it all together, you’ll create a deeper understanding of your customers’ needs, desires, and patterns. What’s their age? What’s their occupation? Where do they live? How often do they travel? The list could go on forever.
With the right tools, you can analyze all this data and leverage it to develop and position your products and services, improve sales forecasts, and deliver a refined customer experience.
2. Customer satisfaction and retention
Countless customer surveys testify that when buying services, it is the experience that matters most to the client, not the price. Sure, a good price helps, but your salespeople’s knowledge, attitude, and engagement will surely make a longer lasting impression on your client.
Customer satisfaction is tough to build yet easy to lose, so you can never put enough effort into it. Once a client starts to feel dissatisfied, the scary “A” word becomes a growing possibility. That’s right…client attrition.
The sales organization can analyze salespeople’s activities across systems and sales channels by using big data. This increased visibility will allow them to trace incidents or indications of low customer satisfaction, giving the company the possibility to fix the situation in due time.
3. Know Your Customer (KYC)
If selling and servicing clients were the only two things sales reps had to focus on, I bet many of them would be much happier. As the legal frame widens, meeting regulatory and reporting obligations steals more time away from actual selling.
Although necessary, Know Your Customer (KYC) rules complicate this picture. Companies have to verify customers’ identities to prevent identity theft, fraud, money laundering, and terrorist financing. According to research by Thompson Reuters, money laundering, compliance violations and other breaches cost the world up to US$ 3.8 trillion in 2014 (approximately five percent of global GDP).
However, for financial organizations, complying with these new rules has its disadvantages. KYC can slow the process of opening an account and onboarding a new client by as much as six months.
Many institutions have completely overhauled internal processes, even beyond customer data collection. KYC has intensified data analysis, increased reporting of sales data to other internal departments, and mandated training for sales on the new rules and the new approach.
4. Other Regulatory Reporting Obligations
Enhanced regulation seems to be the primary response to the cyclical financial crises. Some say the financial industry is over-regulated; others claim it is under-regulated. What is certain is that the industry is committed more than ever to understanding, monitoring, and managing risk, wherever it originates.
Big data solutions give financial organizations the capacity to back up regulatory data with contracts, certificates, and other supporting documents they sometimes need to present.
Big data, big promises
So big data brings big promises compared to traditional data management (like data warehousing or business intelligence): faster, better capabilities to process, store, and analyze data, often at lower costs.
How about you? Are you concerned you might be making decisions based on erroneous or incomplete information? Well, don’t lose your hope if you look into your backyard and find out (some of) your big data is bad data. There are solutions to cleanse it and put it to good use. As with any technology, what makes the difference is how you utilize it.
Make sure you have a thorough approach across departments. Sure, IT is the owner of most big data implementations, but the ultimate goal is to drive sales. From this perspective, big data is more a business than a technology matter. And remember to be patient.
Rome was not built in a day, and big data projects may take years to get right. With the right assistance, you can reduce that time.
I’d love to hear about your experience with big data projects. Write to me and let me know about it.
*Novonous, Big Data in Global Financial Services Market: Key Trends, Market Opportunities and Industry Forecast 2015-2020