Today’s sophisticated technology solutions make data and analytics more accessible than ever. Financial institutions in particular have data from a variety of sources across new and legacy platforms, and face a myriad of challenges in integrating this information across multiple channels. However, there are tremendous opportunities to take advantage of.
The challenge many executives now face is how to effectively transform it into actionable insight. Identifying the best ways to analyze and visualize data for both internal and external purposes can help you reduce costs, develop new products, and improve your overall customer experience.
New data visualization toolkits, mapping APIs and business intelligence (BI) platforms have made this process easier. However, creating compelling enterprise solutions and highly engaging customer experiences are not always easily achievable with just a tool or packaged reporting application.
The opportunities within financial services to design and develop powerful analytic offerings have never been greater. In this post, I’ll discuss effective ways to leverage analytics in financial services to improve internal processes, better anticipate customer needs and create new external offerings.
Employ analytics for risk management and compliance
Many large financial firms such as asset managers and investment banks can realize significant gains by leveraging and correlating their data to develop more sophisticated risk management capabilities. In the current regulatory environment, having a pulse on the state of the business is critical. One effective way to increase risk management and overall control is to define and closely monitor key metrics (KPI’s, KRI’s, etc.) across your risk categories and company.
With constant change around new regulations, developing an integrated centralized risk management platform with aggregated, summarized and visualized data becomes a way for firms to better manage existing processes and stay ahead of new requirements.
Another element of enterprise risk to monitor beyond regulatory risk is operational risk. To maximize existing resources, data can be captured and used to interpret existing accuracy, efficiency, compliance to procedures, and work patterns. Within a bank’s middle office for example, the ability to monitor operational data at managerial and executive levels is crucial to track the organization’s daily transactions and recognize any patterns and overall risk exposures.
Identify new product and service opportunities
Another trend with great upside potential is employing analytics across the enterprise to develop new client-facing products and solutions. Several leading wealth management organizations have developed quantitative models that look across their investment funds and products or that provide new tools for advisors or end clients. Similarly, mutual fund companies are able to build and monetize model portfolios and related tools based on risk, performance or other relevant analytics.
By giving access to multiple users within their organizations, these firms are actually reducing their longer-term technology spending by optimizing software distribution and use of resources. Since portfolios can be constructed based on risk and performance profiles, analytics solutions and model portfolios can provide insight for managed accounts for high net worth individuals and drive more profitable and deeper client engagement. For large global wealth management firms with broad financial advisor networks, these powerful tools help make these professionals more productive and efficient, allowing them to focus on their relationships and growing their book of business.
Large commercial and investment banks are developing analytics-based products and services that leverage internal meta data from their core businesses to add value for customers. Aggregation of anonymous data can be used to develop new benchmarking tools, indices and other trading or asset allocation models based on historical data.
Within the capital markets, firms are developing value-added services, for instance creating new liquidity, trading products, algorithms and quantitative reports to sell on top of existing core capabilities in order to reach new markets, like corporates. This approach has been instrumental in identifying new customer segments to increase market penetration and maximize technology investments.
For client-focused organizations where driving relationship value is critical, looking at gaps in the customer journey to identify new opportunities can improve the overall client experience. By leveraging predictive analytics, for example, big data can be transformed into products that meet new customer servicing needs.
Use analytics to improve client service
Understanding and identifying elements that impact customer service and call response times can help to indicate areas for process improvements that can help optimize workflows. Mapping the client experience or journey is a best practice for providing a framework for doing this. By minimizing client waiting time and improving availability, your organization can maximize its effectiveness and improve overall customer experience. Developing predictive models based on historical data correlated with customer data tied by persona can enable your organization to better anticipate client needs and provide a better customer experience.
An additional byproduct of workflow and experience mapping is the ability to improve management’s decision-making abilities by providing an overall view into customer acquisition and retention activity and client KPI’s.
Choose an approach that maximizes user and/or customer experience
If leveraging analytics in financial services for competitive advantage, careful consideration to the overall user experience and workflow around the application must be given. Questions that need to be asked include:
- How will the data be used by the client or internal user?
- Does the functionality also need to be provided via an API for integration with existing applications?
- What technology can best enable the customer experience? What modern application frameworks and portal technology should be considered?
When should I consider a custom solution?
After conducting a thorough assessment of your existing analytical tools, evaluate whether they are able to meet your organization’s current needs. A strategic approach is necessary to determine whether a more customized solution is needed to provide better workflow, specialized capabilities and deliver an exceptional user and/or customer experience.
Multiple tools are currently available to help visualize data. Examples include Tableau, Domo, TIBCO Spotfire, R and many others. However, the out-of-the-box capabilities provided by these tools are often not suited to the unique needs of an organization and cannot provide a full multi-channel customer experience. For example, they may not scale sufficiently to deploy in an external product and often do not provide appropriate workflow capabilities and navigation frameworks. By leveraging your existing tool sets and developing bespoke offerings around your customers to enhance their user experience, you can get more leverage.
Here are some typical elements that play an important role in an analytics-based solution offering:
- Dashboard: Create role-based customized views that track key metrics by department, risk category, region, client segment or sector. Providing users with the ability to configure or access multiple views can quickly highlight important insights around critical business activities.
- Visualizations: Employ useful graphics and data visualizations to help users to understand large data sets and to quickly identify and act upon trends. Heat maps and geographic dispersions can make monitoring regional or sector trends easier and faster.
- Workflow: Based on your customer’s needs, design an optimized, streamlined workflow that leverages any visualizations and functionality in a contextual way.
- Alerts: Create triggers that notify users about key changes they need to act upon or based on anticipated events or needs based on predictive analytics.
- Filters: Actively interrogate data by creating customized screening tools and advanced filtering that identify key measures and provide alternative views.
- Integrated Analytics: Bring together different elements of your systems within a single interface to identify important interdependencies in real-time.
- Mobile Integration: Provide access to reports and alerts “on the go” so your global workforce can operate more effectively for key workflows.
Consider whether you need help
To decide how to proceed and whether to use out-of-the-box tools and/or create a more custom analytics solution, you should assess whether your organization has the necessary experience and skills. An experienced team should be familiar with a variety of packaged solutions (and their limitations) and when custom solutions are appropriate. They should have relevant customer experience, application design and development skills and can provide insight to help you understand how or whether these can be adapted to suit your business needs.
Here are some questions that will help you determine whether you’re working with the right design and development team:
- Does your company use technology as a competitive differentiator?
- Is providing an exceptional customer experience a company priority?
- Does the information need to be delivered via a multi-channel experience, e.g. desktop, mobile, wearable?
For more complex cross-channel offerings across platforms, call centers, websites, mobile and app solutions, creating a holistic user experience for both customers and employees can be challenging. This is where it may be worth making the investment in creating customized enterprise-wide offerings. Consider bringing in a team with the right skills and experience who can map out your needs to develop an experience strategy, help your organization evaluate appropriate off the shelf and custom solution approaches, and assist you in executing on your vision.