Business
Mitigate risk and accelerate growth with ‘fit for business’ data
Global Banking & Finance Review®
Company
By Peter Ku, VP & Chief Industry Strategist – Financial Services, Informatica
The last two years have been unprecedented for financial services organisations, with the industry undergoing one of the biggest, most transformative periods since the introduction of the internet. During this time, with Covid being a significant force for change, the industry has seen a significant acceleration in the modernisation of its technology to support the need for customers to interact digitally with their banks, insurers, and other financial services providers. IDC’s prediction of spending on Cloud by financial services highlights the pace of change. Institutions would grow 16% year on year between 2021 and 2024, representing 77 billion in net new investments.
For banking institutions, developments in smartphone technology, global lockdowns, and increased comfort levels from customers around conducting business digitally have replaced physical bank branches and ATMs in developed countries and allowed banks to provide services to millions of unbanked customers in less developed regions.
In insurance, we’re seeing AI-enabled solutions help to reduce manual human-led processes from underwriting to claims processing, resulting in lower business costs and improved customer experience.
These demonstrate the irreversible shift in how the financial services industry operates, with data at the heart of it all. From banking to insurance, companies are realising the business benefits of implementing newer technologies for leveraging data and the positive impact this change brings to their customers. According to a recent Fortune 1000 C-suite executives survey, data and AI initiatives are ubiquitous, with 99.0% of participating firms reporting ongoing investment in these areas.
Although how financial services companies interact with customers has changed, the importance of the customer experience has not. This remains a top business priority, and organisations continually look to improve the customer experience to increase wallet share and extend the customer’s lifetime. However, many banks and insurers are facing the same predicament. Fragmentation and complexity of data and the inability to scale data management and governance to deliver ‘fit for business’ data across the organisation. Those that master this challenge will leverage data to intelligently drive the next-best actions, recommendations, and predictive insights for their business.
We’ve established that to meet the objectives of improved customer experience and sustainable business growth, organisations need data that is fit for business use, but what is that exactly? Fit for business data allows organisations to turn data into measurable business value by making trusted data actionable at scale, so it can be readily used by people, applications, machine learning, and more.
Fit for business data has a number of attributes; first, it must be accessible from any system, location, and format – whether that is a customer service representative attending to a customer on the telephone or an automated offer served up via a banking app; each has access to the most relevant, trusted data. To ensure accuracy and avoid underperforming marketing campaigns and inflated customer acquisition costs, the data that feeds these activities, such as business reference data, customer contact information, and relationship profiles, should all be clean, verified, and approved. As more lines of business functions utilise data, it’s essential that data is understood, helping those in sales, customer service, marketing, or other non-technical roles to comprehend the business definition and use of existing data.
Improving customer experience and growing the business is important, however, as the most regulated industry in the world, there is a raft of regulations to adhere to, so strengthening risk management remains one of the financial institutions’ highest priorities. With fit for business data organisations can fortify risk management and fraud prevention practices with trustworthy and transparent data while operationalising data governance at scale. To do this, data must be transparent so that teams can understand where data comes from and where it is stored, processed, and consumed. Not understanding and being able to report on this data lineage can result in higher compliance costs and increased risk for the business. Protecting that data is of the utmost importance with a wealth of personal customer information. This involves identifying, classifying, tracking, and protecting personally identifiable information (PII) to avoid data breaches and comply with data privacy regulations.
Managing, governing and protecting data across multiple business lines and very often geographies is complex. It takes the right skill sets, governance policies, processes and technology to do it right. Missing any one of these elements puts you at risk of not having data that is fit for business use. Technology used to manage, govern and protect data alone does not address the lack of experienced workers, or define what data you need and why, or how, success is defined. To address fragmentation and reduce the complexity, financial institutions should consider an end-to-end data management platform for data integration, application integration, data governance, metadata management, data quality and master data management. Bringing these functions together into an AI-enabled platform will help financial services organisations unleash the power and value of data across local systems and hybrid and multi-cloud environments – ensuring everything is trusted, protected, governed, accessible, timely, relevant, and accurate.
Those financial services organisations that adopt a fit for business approach to data, leveraging cloud-native tools to make trusted data available across the business will deliver more personalised experiences, support cross-sell opportunities and improve their risk management. It is these organisations that will rapidly deliver data-driven transformational outcomes and expand their opportunities for success.
Fit for business data refers to data that is accessible, accurate, and actionable, enabling organizations to derive measurable business value and improve decision-making processes.
Risk management is the process of identifying, assessing, and controlling threats to an organization's capital and earnings, including financial, operational, and compliance risks.
Customer experience in banking encompasses all interactions a customer has with their financial institution, aiming to enhance satisfaction and loyalty through personalized services and efficient processes.
Data governance is a framework for managing data availability, usability, integrity, and security in an organization, ensuring that data is accurate and used responsibly.
Digital transformation in financial services involves integrating digital technology into all areas of a business, fundamentally changing how it operates and delivers value to customers.
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