Against a backdrop of challenging macroeconomic risks, including inflation, potential recession and high interest rates, banks are also dealing with volatility connected to the collapse of three regional banks. These are difficult times, especially for financial institutions.
At the same time, banks are struggling to achieve primacy: being the go-to for their customers’ financial needs amid the marketplace of more agile fintechs. To do this, banks need to make smart decisions, fast. This amalgamation of business-impacting factors might seem like an unsolvable puzzle. But in an uncertain market, banks can leverage data to cultivate engagement and drive primacy.
Banks can count on data, with some caveats. The data must be:
- While there is a massive amount of data available, banks often lack a complete picture of the consumers they serve, particularly as digital banking has made it easier for consumers to initiate multiple financial relationships with different providers to get the best deals. It’s vital that banks get a holistic view of all aspects of a consumer’s financial life, including held away accounts, insurance and tax data.
- Increased open banking functionality empowers consumers to take charge of their data and use it to be financially fit. Open banking serves that connectivity and makes it more reliable.
- Banks are flooded with data, the torrent of which makes it difficult to extract value from that data. Up to 73% of data goes unused for analytics. But the right analytics allows banks to reduce the noise from data and glean the necessary insights to make decisions and attract and retain customers.
- Most transaction data is ambiguous and difficult to identify. Banks need enriched data they can understand and use. Data enrichment leads to contextualized, categorized data that gives banks tangible insights to improve their customer’s journey and inform more meaningful interactions.
Data as a Differentiator
Once banks have high quality data, they can use it to differentiate themselves across three key areas:
1. Make smart, fast customer decisions.
Banks are expected to deliver relevant offers at the right time to customers before rapidly making critical risk decisions. The ability to do this hinges on having a holistic view into the totality of a customer’s bank accounts. Data science algorithms using artificial intelligence and machine learning can then surface insights from that data to engage, retain and cross-sell via personalized, proactive experiences. From there, banks can execute for growth with rapid integrations that help gain wallet share and productivity.
2. Promote financial wellness.
Banks are nothing without their customers. To win and keep customers, banks need to provide tools and products that can enable an intelligent financial life: helping consumers make better financial decisions to balance their financial needs today and building to meet their aspirations for tomorrow. One way to help them with this is to provide a holistic view of their finances with account aggregation and money management tools. According to a recent survey, 96% of consumers who used financial apps and tools powered by their aggregated data were more likely to stay with the financial institution providing these tools. These tools give banks a way to helping their customers and inspire loyalty.
3. Forecast and manage risk.
Uncertainty over recent events in the banking industry has made the need for immediate insights into net deposit flows an imperative. Banks can use aggregated data to identify, forecast and manage their risk exposure. Digital transformation, which has been all the rage for years now, can enable centralized holistic views of a bank’s entire portfolio. Dashboards and alerts make it more practical for bankers to identify risks in the bank as they develop. A platform approach is vital. Banks need an entire ecosystem of data, analytics and experiences to mobilize data-driven actions for engagement, retention, growth and ROI.
Now more than ever, banks rely on data to cultivate engagement and drive primacy. Starting with holistic, high-quality data and applying analytics to derive insights, banks can drive the personalized consumer experiences that are necessary to attract and retain customers. And they can use that same data to better forecast and manage risk within their portfolio.