As financial institutions look forward into 2022 and beyond, it will be nearly impossible to predict the challenges ahead. While it is certain that coming years will be impacted by the pandemic, shifting consumer needs, and expedited digital transformation, the road forward remains hazy. The FDIC notes that, “overall, the industry must manage interest-rate risk, liquidity risk, and credit risk carefully to remain on a long-term, sustainable growth path.” Amidst these challenges, key stakeholders and decision makers must move forward with strategic planning
Actionable data insights can take these challenges into consideration while empowering faster, smarter, and sharper decision making. To be actionable, business forecasting and analytics must be aligned across the organization. Historically, this has been achieved through multiple analytics platforms, but this results in conflicting information as the organization doesn’t have a single source of truth. However, data analytics that are integrated from a single data engine are enabling financial institutions to maintain a competitive edge in the industry, develop a reliable roadmap for the future, and continue to experience growth, particularly in lending and compliance decisions.
Here are 3 ways that data analytics can assist strategic planning:
- Make Data-Backed Lending Decisions
Data is constantly being exchanged and generated within a financial institution. Data can quantify strategic decisions. Yet, without a strong data management strategy, this data piles up and cannot be leveraged to its fullest potential. With integrated data analytics your institution can:
- Provide insights and forecast consumer profitability
- Track and analyze campaign profitability and consumer journeys
- Forecast lending decisions for the unbanked or under-banked demographic
- Offer predictive analytics for mergers and acquisitions
- Track consumer behaviors to insightfully offer products and services
Portraying various lending scenarios leverages data to develop budgets, expand lending, reach new markets, and execute on planning decisions.
- Integrate Data Across the Organization
Although data is vital for financial institution operations, when data is scattered and siloed it can be a hindrance to business functions and efficiency. Conversely, when data is automated and unified it can become predictive rather than just informative. For example, an accountholder’s basic data can tell you their credentials such as name, contact information, and address. When basic informative data is combined with buying habits, credit score, payment history, and loan portfolio your institution gains a 360-degree view of that accountholder. These insights can predict future behaviors and can be integrated into strategic planning.
With the right data analytics platform, integrated data can then be combined with a library of economic conditions and market-specific scenarios to create unique and clear pictures for decision making and planning. Data analytics can also be combined with artificial intelligence to reach new market segments, automate routine tasks, and monitor compliance. - Plan for Upcoming CECL Changes
A new accounting methodology, Current Expected Credit Loss (CECL), has been underway for several years and will go into full effect later this year. The significant standard update will necessitate more stress testing, forecasting, and calculating, specifically to track credit loss exposure to outside investors.
Data analytics can provide these forecasting and modeling opportunities to stay in step with these standards. When weighing a CECL solution provider, thoughtfully consider investing in a data analytics solution that is designed to fuel strategic growth.
Leveraging Data for Strategic Planning
As financial institutions continue to face pandemic-related challenges, lending and compliance remain a focus for strategic planning. By centralizing analytics and forecasting through a single data engine, decision makers can better analyze portfolios, risk strategies, and capital management, and remove the guesswork to make clearer decisions for the road ahead. Consider adopting an enterprise approach to data analytics to quantify the impact of decision-making, drive profitable growth and help your financial institution evolve with market challenges. The future is now, and predictive modeling and enterprise analytics is more important than ever.