Regardless of industry, success in business is all about solving customer problems. Financial institutions and FinTech organizations help their customers solve a range of financial problems in areas like budgeting, money movement, wealth management, auto loans and real estate financing. In order to provide more relevant products and experiences they must not only leverage data but have processes in place to update and manage it on an ongoing basis.
Predictive problem solving for financial services
By gathering customer data, governing its access and structuring it for effective use by leadership and business units, a financial institution can predict the types of products and services that will provide the most value to each of its customers. Providing this single source of truth for customer data also allows digital teams to research repetitive habits, segment users and strategize device support for the organization.
Utilizing this shared data for investment planning is crucial to maintaining an organization focused on solving customer problems. With all teams working from the same full view of the customer, it then becomes easier to build a more immersive digital journey by removing friction, filling gaps in current services and anticipating future needs.
Data is the key to mapping initiatives for investment
Effective resource allocation sets industry leaders apart from the rest. Properly structured and managed data makes it easier to know where additional investment is necessary and where it won’t produce a sufficient ROI. Successful business leaders understand that just because the company can do something, doesn’t mean it should.
Having data in hand empowers digital teams to provide leadership teams with the facts required to make informed decisions. This ensures that investments are solving customer problems and improving overall experience in a measurable way. With the right data, the following tools can be used in planning for digital investment and growth:
● Cost/benefit analysis: reveals the full cost of implementation and ownership compared to the potential value to the customer and/or the organization
● Customers affected: reveals the number of active users currently affected by the problem and points to the value of providing a solution
● Operational savings: a measure of the potential savings, based on the current impact the problem poses to front line sales and service and/or back-office operations
● Market viability: a measure of the likelihood that the technology will be capable of solving the problem once implemented
● Impact to risk model: an analysis of the impact a new investment could have on the organization’s current risk model and a plan to mitigate it
● Market sensing: an analysis of market and technology trends and customer feedback pointing to the market value of the proposed solution
Stay out of the weeds
It is important when doing analysis and planning not to get so caught up with small details that you end up stalled entirely. When determining the potential scope of a solution, keep the team focused on the customer problem they are trying to solve by limiting the number of use cases you will initially support.
Getting caught up in edge cases that affect less than ten percent of users or exercises that abstract the team from the specific task at hand provide little value and should quickly be dropped from the discussion. Solving the problem for as many customers as possible should always be the primary focus, but cost and timeline need to be considered as well. If it requires three times the investment and twice as much time to solve the problem for an additional 5-10% of users, those use cases should not be considered for initial release.
According to research done by Deloitte, expectations from financial institution customers have grown. Even more so now that banking is heavily reliant on user-friendly mobile technology. Data must be properly utilized so that financial institutions are able to be a step ahead of the increasingly aware consumer that expects not only efficiency and speed, but also anticipatory service and action. With the right data governance, digital strategy discussions become easier to navigate using deeper customer intelligence instead of assumptions or vendor analysis.