Big data analytics will bring about significant change in value generation for the financial services industry. Winning companies will be the ones that utilise big data to help make the crucial shift from product to a customer-centric focus.
Collecting information, aggregating it, and managing it over multiple channels is a huge challenge for the financial services industry. If your business isn’t set up to correctly store, analyse and use this data, it can become a burden, either on people’s time or on costs for digital storage solutions with no ROI.
Too much data and not enough insight or analytics to understand it can cause digital overload. With the advent of advanced analytical options for big data, this is set to change.
While the various benefits of big data have been widely discussed in other industries, the financial services industry has yet to catch up. The industry must act now and involve big data in its strategies to evolve the relationships with their customers, and transform data into an asset.
Personalisation of services
In an age of commoditisation of products and services in financial services, developing relationships with customers is the key to success for the majority of businesses within the sector. By employing big data solutions, financial service providers can design ways to offer their customers more personalised experiences.
With the vast amounts of data now being generated by customers across multiple channels as they browse for financial services such as loans and retirement savings products, big data analytics offers the opportunity for these interactions to become increasingly personalised for the customer, based on a combination of their past preferences, real-time needs, and attitudes towards spending money and investing.
The importance of this personalisation is amplified when considering the rising expectations of digitally-empowered customers. Personalised and convenient services are now no longer a want, but a must for customers, and the need to meet this market demand will drive transformation in the industry over the next decade.
Big data-enabled AI
In much the same way that personalisation of services through big data analytics will transform the financial industry, so too will Artificial Intelligence (AI). The two concepts go hand in glove, with big data being one of the most effective enablers of AI.
Big data enables the use of AI in the financial services industry because it provides the necessary capacity for learning algorithms to not only consume data, but also use that data to make strategic decisions.
For example, big data can enable AI to provide recommendations to the business development arm around the location of a branch office based on real-time behaviours of customers, or around loan approvals — significantly reducing the workload on professionals previously tasked with doing all the background research for these decisions.
AI within the financial services industry is already manifesting itself — Deutsche Bank’s robo advisor, which uses algorithms to compile individualised portfolios for investors, is just one example.
While this technology is highly unlikely to completely remove the need for financial service professionals such as brokers, it will allow them to focus on building genuine relationships with their customers, and spend less time manually mining data and evidence to support their decisions.
Combating cyber vulnerabilities with big data
A technology like AI might only be in its initial stages, but the technology behind cyber-crime, and the fight against it, is widespread. As more of the financial services industry’s relationships, services, and products move online, digital security threats have become increasingly pronounced as this valuable, private information becomes susceptible to attack.
Big data and cybersecurity technologies can complement each other, as the two work together to ensure that data is protected. There are three key ways that big data can be a part of effective cybersecurity strategies in the sector:
- Extensive coverage of security data sources, such as deriving inferences, can dramatically accelerate any security investigation process.
- Wide-angle data lenses enable data linkage and visualisation, which can be used to follow a chain of evidence related to an attack, or map a path for its prevention.
- Quantum improvements in data usability have allowed for the creation of dashboards and reports, which streamline security operations.
In an age of digital threats, digital solutions are needed to maintain security and trust, so that by remaining in a world of paper, spreadsheets and data entry, organisations don’t have to compromise on the efficiency and business benefits that new technologies provide.
From product to customer: a shift in thinking
Protecting against cybercrime using data as part of technology solutions will become the norm as cyber-attacks get more sophisticated. However, only truly innovative businesses within the financial services industry will use big data to shift traditional thinking from product to customer.
Improving customer engagement through big data analytics will empower businesses to help their customers manage their financial lives easily and securely, creating loyal customer relationships.
Hardware and software are increasingly transforming the nature of work undertaken by professionals, and big data has a huge role to play in this shift. Once businesses processes are in place to efficiently analyse the massive amounts of data generated, automation will start to apply the levels of personalisation necessary to engage and retain customers in the long term.
Big data will be a major player in the wider digital transformation occurring in the financial services industry. The industry needs to ensure it is ready to meet the challenges to avoid digital overload, and instead unleash the true power and value of effective big data analytics for customers.
This, coupled with regulator objectives of portability and interoperability, will create far more flexibility for the customer, resulting in less friction in changing financial institutions and, as an outcome, create a more competitive marketplace.
Therefore those institutions that can best leverage data and its insights around customer needs will be best placed to gain in the new digitally empowered marketplace.