Big data & analytics: recommendations for financial services firms

Increased competition in the financial services sector is one of the key drivers for growth and innovation. With $40 billion being secured by fintech start-ups since 2015 [Frost & Sullivan], they present banks with the key challenge of competing against customer-centric, agile companies who are building businesses from the ground up, powered by big data investments from the outset. Banks are thereby forced to compete by also attempting customer driven strategies, by offering a more personalised customer experience, and using data as a means to do so.

High consumer expectations surrounding customer experience, driven by other industries - where big data is already being used - is also a key growth driver for the technology uptake. Banks are being measured against more digitally savvy industries and brands regarding their query response times, clarity of communication around product offerings and social media dialogue with customers, who are already established in this area. This, coupled with the threat of the new market entrants in their own industry, including digital only banks, encourages a sharper focus of new big data technologies, and an emergence of unique products and services geared around the customer.

Below, I have listed my key recommendations for financial services firms deploying new innovative technologies.

Learn from other industries

Banks should learn from industries that have already undertaken, tried and tested these technologies, gaining huge value as a result. The uptake of big data and analytics is not advanced in Financial Services, and should be leveraged for everyone’s benefit, however there needs to be a level of acceptance and urgency around making changes, investing in them and staying ahead of the curve.

Invest in infrastructure

The legacy, custom architecture that banks have used for decades needs updating to accommodate and integrate new big data platforms. One possibility is to modernise the current legacy applications so the new products can be integrated, as well as migrating data from legacy databases to a high-speed data warehouse. This will undoubtedly avoid roadblocks around big data processing.

Encourage buy-in from the whole organisation

Big data deployment projects are not focussed on one area of the business, and they certainly span both the business and IT worlds. Governance and coordination between banking divisions is important for the success of projects. To ensure a cohesive approach, banks should involve the whole business, including C-suite sponsorship and backing. Additionally, by bringing department heads together for full briefing sessions, it will be easier to motivate staff and teams across departments.

Mobilise new teams and partnerships

With new technology requires new talent, and currently big data projects are understaffed in banking. The challenge is that there are few big data technology experts, who also understand the business side. Perhaps to address this, banks could add individuals of varied skillsets to the project team, allowing for business process leaders to engage with those that truly understand the technology. Furthermore, big data applications bring security and privacy issues, and therefore the recruitment of a specialised team to deal with the legally and commercially sensitive information, according to regulatory guidelines, would be wise.

Work on customer experience and incentives

It is clear that without customer data, progress cannot be made in this area. Strong customer experience strategies can also be developed as a result of data. The key for banks will be to work on partnerships with the right technology vendors, as well as the appropriate partners for loyalty and points schemes, in engaging consumers and collecting valuable data. This is not only a short-term strategy for marketing, yet a long-term solution for maintaining customers, and growing wallet share.

#bigdata #customerexperience #CX #chatbots #AI #retail #omnichannel #partnerships #robotics #financialservices #fintech #banking #analytics #automationsystems #automation #transactions

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