Data: the Cornerstone of Digital Transformation in Financial Services
By Torey Hunt | July 4, 2019
The single biggest driver for digital disruption in banking and financial services is data. Clean, high-quality data fuels the digital initiatives that are challenging the norms – for the better – when it comes to service delivery in financial services. But to accelerate business outcomes and maintain a competitive edge, enterprises must implement an end-to-end digital transformation strategy and define data governance goals so that their content is easily accessible.
Below is a Q&A with Phil Siarri, an industry thought-leader in the FinTech space along with Adlib Software’s CEO Peter Duff. Together, they explore the impact that data quality has on propelling a bank or financial services organization’s digital initiatives.
Peter:What is the most important digital transformation goal that organizations in financial services are focusing on?
Phil:We’re seeing more of a focus on the customer experience. Right now, digital transformation adds strength to transform financial services to be more customer-centric. Firms are no longer just competing with other financial firms for consumers' attention and their loyalty. They're competing with any entity that's offering a superior experience, and that includes consumer and technology brands in order to digitize a process to make peoples' lives easier.
A great example of that is the recent development of Apple Card, which is centered around Apple Pay, the company's mobile payment and digital wallet. And it promises a great customer experience and user friendliness, and 10 years ago, I don't think too many people would imagine a traditional big tech firm going that route.
Peter:From a digital transformation maturity perspective, how do you see the overall progress financial services organizations have made?
Phil:We’re seeing the sector put processes and tools in place to deliver a consistent and strong brand experience along their entire customer journey.
Industry players are streamlining operations, replacing legacy processes and automating the inclusion of compliance teams. Advanced analytics frameworks are also helping leadership teams to make strategic and informed business decisions.
Peter:What role does data play in some of the digital transformation initiatives you mentioned, but also in others like artificial intelligence (AI), machine learning and robotic process automation (RPA)?
Phil:Data is one of the cornerstones of digital transformation strategies and tactics. If you have an AI or RPA framework that is not fed with adequate data, it will perform poorly. I like to use a car analogy: you can't run a car on fruit juice; you need to fill up the tank with the proper fuel.
Peter:What types of challenges are preventing financial services organizations from leveraging their data as fuel, like you mentioned, to drive digital transformation initiatives?
Phil:Sometimes, organizations are obsessed with data volume alone or collecting lots of data, but the quality is also important. So, for example, if you were to collect and analyze huge sets of unstructured data, which historically is fairly hard to decipher, do you have the capabilities in-house or maybe the technological prowess to make it truly relevant? This is the type of question that companies need to ask themselves.
Peter:What are some of the enterprise solutions missing to your point about data quality?
Phil:Collaboration with data is key. You can't just collect data for the sake of it or keep it within a single business unit; you have to make sure it's in line with overall corporate strategy and it benefits an entire organization.
Peter:There's lots of stories about the data lakes from the past where each business unit simply dumped their content, but today, it’s essential to ensure that no data is contributed unless it’s complete, relevant and accurate.
Can you share some examples of how FinTech orgs are leveraging AI and RPA as part of their digitization initiatives, particularly around improving the customer experience, or related to improving operational efficiency?
Phil:The Bank of America has an AI chatbot they call Erica, and it uses it as a digital financial assistant for its client base. It offers user-friendly transaction search, it allows users to search in historical data for specific transactions with a particular merchant, so basically they don't have to look for these in each of their bank statements. It also computes the total amounts of credit and debt.
Previously we talked about operations streamlining and I think JP Morgan is a good example. They use AI-powered optical character recognition or OCR software for contract analysis, which frees 360,000 hours from its employees in only a few seconds.
About Phil Siarri
Phil Siarri is an innovation management professional, industry analyst, publisher, author, and tech influencer. He has been selected as one of Canada’s top 40 social influencers in finance, innovation and risk by Refinitiv, top 50 fintech influencers in Montreal by FinFusion as well as top 18 AI media influencers by Onalytica.
About Adlib’s CEO Peter Duff
Peter is a leading expert on unstructured content management, and has over 20 years of experience in the industry. He shares his passion on the latest strategies and best practices in automating content and document processes to help organizations drive bottom line results. Peter holds a B.Sc. in Electrical Engineering from Queen's University in Kingston, Ont., and a Master's degree in Information Science from the University of Toronto.
About Adlib Software
Adlib has been transforming the way enterprise organizations overcome unstructured data challenges for over 15 years. Integrating with various business applications, Adlib enables digital preparation of documents for improved migration, compliance, privacy and security, digital transformation, capture and classification. Our document enrichment solutions allow over 5,500 customers globally to elevate their content and derive the insight that is needed to support critical decision-making and secure competitive advantage.
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