The future of financial services will be shaped by the ability of financial institutions to extract and deliver more customer value from data. The convergence of mobile, cloud, and IoT technologies continues to create new opportunities for institutions to deliver personalized and contextual financial services. Those opportunities will rely on data and analytics for real-time decision making.
Some familiar examples are receiving banking fraud alerts on mobile devices, submitting photos for insurance adjustments, or using robo-advisors for investment decisions. There is an opportunity beyond these core services to embed financial services into broader digital commerce ecosystems. Those ecosystems could add up to a $60 trillion integrated network economy by 2025, according to McKinsey.
Intuit, the American financial software company, is leveraging integrated data-driven intelligence from its diverse acquisitions of Mint, Credit Karma, and MailChimp. Their goal is to move beyond tax-related services to deliver a holistic financial services platform to small businesses and their employees, inclusive of banking services. In China, insurance provider Ping An’s “finance and ecosystems” strategy has evolved. They now oversee subsidiaries that leverage their finance and data analytics competencies to build ecosystems for a variety of non-financial industries like healthcare and real estate.
What Lies Ahead
These examples highlight a diverse and exciting future for financial services. Capturing these opportunities however is a multidimensional challenge requiring a broad set of data-related structures and competencies. These include institution-wide standards for data infrastructure, governance, and security, as well as business- specific needs related to data acquisition, data science, compliance, and more.
The reality is that most institutions must reduce the complexity of managing large pools of data, much of it still decentralized, while simultaneously supporting the need to extract a broader range of business insights from structured and unstructured data. This challenge is compounded by the growing use of alternative data from sources like customer data platform (CDP) providers, fintech partnerships, and even from sensors and IoT devices.
The financial services industry is looking to the promise of artificial intelligence (AI) and the elastic scalability of the cloud. Both offer help in harnessing big data to deliver hyper-relevant content, products, and services based on customer behaviors, lifestyle, and preferences.
Creating new customer value from AI
A recent global survey of bank executives by The Economist Intelligence Unit highlights AI’s anticipated impact on competitiveness. Four out of five executives believe unlocking value from AI will be the key differentiator between winning and losing banks.
As digitization transforms operating models, institutions are deploying AI capabilities to front, middle, and back-office operations, embracing an iterative approach to improve the quality of analytic models. More attention is also turning to gaining competitive advantage from under-used customer data collected via conventional operations. The ability to surface these advantages and act on them in real-time will become more available to clients and financial associates as AI capabilities are embedded into customer experience solutions.
AppDynamics, IMI Mobile, and Webex Contact Center are examples of Cisco solutions that leverage AI to help financial institutions deliver differentiated client experiences.
Cloud
IDC estimates global financial services spending on public and private cloud services will surpass $1.3 trillion by 2025, growing at a CAGR of 16.9%. Financial services cloud adoption is accelerating, due in part to the significant computing horsepower required by big data and AI analytics. This momentum is also being fueled by growing adoption of cloud-native fintech solutions that are built on these capabilities.
Recent cloud innovations, like Data Cloud solutions, specifically target big data in the cloud. In addition to reducing operational complexity and cost, they offer the potential to improve institutional data quality, which can significantly improve the quality of AI algorithms.
To take full advantage, financial institutions must have the flexibility to choose solutions residing on different clouds. This requires integrated, cloud-neutral connectivity, security, and management capabilities. Cisco Cloud Solutions are designed for multi-cloud environments and leverage data-driven performance analytics to provide better operational visibility and resilience.
Customer Value
Put simply, data is an untapped treasure trove. Financial institutions need only tap into this data to reveal new ways of delivering incredible customer value.
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I think that the availability of data especially on the cloud is a way for people to connect to one another and for companies to further understand what their user needs. This can aid in user experience design for future applications, especially for mobile users.
Absolutely… there’s a lot of untapped insights within structured and unstructured data. It’s a significant challenge for financial institutions to manage the growing influx of data, extract the insights, and make them actionable in a reasonable timeframe. Cloud capabilities can help address these data challenges and accelerate the opportunity to deliver benefits directly to consumers thru mobile application. Thanks for the comment!