The ability to plan the best path for the future by understanding how the wind is blowing is critical to bank success. Banks must predict market shifts in order to divest from troubled areas and invest in the economy’s increasing sectors. The majority of these forecasts and analyses were performed by hand. Market metrics, news reports, and trade magazines will all be closely monitored by bankers. They would also establish friendships with influential people in the industry in order to gain access to the most up-to-date information. These tactics, however, are no longer sufficient.
When comparing the olden days to today, one point that is often overlooked is the speed at which trade now takes place. All was slow back then – communication, trading, news – and reporting was slow as well. Markets used to move much more slowly than they do now. Another notable change is that the amount of information now available is simply beyond human comprehension. No one can take data from thousands of sources and analyze it in real-time to decide the best course of action.
Risk technology has become a requirement for banks that want to expand because new challenges need modern solutions. Risk technology can help banks consider more than just upcoming threats; it can also help them identify the market’s most promising opportunities. The banks that have the resources in place to identify opportunities first will be the ones to benefit the most.
Predictive Capabilities
Modern risk management tools such as risk management system can provide predictive analytics thanks to two main pieces of the puzzle. The first component is historical information. Risk assessment software can quickly review years of data to uncover patterns and observations that humans may have overlooked. Predictive solutions may use this information to figure out how the variables are related to one another. Real-time data is the second component of the puzzle. Once advanced solutions have figured out how the various variables interact, they can plug real-time data into the equation to generate real-time metrics and risk assessments.
Predictive analytics is delivered by risk management systems using these two components: historical data patterns and real-time metrics. The machine analyses the latest data and determines the current trend. It then examines the trend’s trajectory using historical data, allowing it to extrapolate likely future metrics. This means the CRO (Chief Risk Officer) would have access to not only the most up-to-date real-time data but also predictive analytics to aid executive decision-making.
Metrics both within and outside the business
Using Artificial Intelligence (A.I.) to complement internal and external risk data, advanced solutions use integrated internal and external KPIs (Key Performance Indicators) and KRIs (Key Risk Indicators) to identify troublesome patterns and anticipate emerging risks. These experiences assist executives in making better decisions, allowing the company to improve profitability and speed up innovation. This allows the solutions to include highly accurate risk map-based forecasts and warnings.
Mapping the Risks
A risk map is developed when risk technology is applied. This risk map shows how various business processes, controls, risk metrics, records, and other factors interact. This allows corporate leadership and boards of directors to concentrate on what matters most in order to improve their company’s operations and profitability.
External market news and developments will reveal areas of concern and the potential for risk executives to investigate further. Risk leaders may also use real-time data with interconnected risk, KRI (Key Risk Indicator), and control data to help a bank seize opportunities faster than its competitors.
Liquidity risk and its associated KRIs are an example. The hypothetical CRO is using an advanced risk software approach in one situation. She states that the bank is reaching its top-line threshold as a result of stock market uncertainty, which has caused many clients to rapidly convert their stock holdings to cash.
The CRO will easily remind the CFO (Chief Financial Officer), CEO (Chief Executive Officer), and board of directors of the bank’s liquidity surplus because the system provides real-time reporting. As a result, strategic investments are made, allowing the bank to gain market share.
Meanwhile, rival banks using manual or legacy solutions are producing quarterly reports based on data that is weeks or months old, making strategic decisions slower than the hypothetical CRO. In such a situation, the risk leaders’ strategic advantage allows them to engage in value development on a larger scale.
With today’s emerging technology, we can anticipate CROs (Chief Risk Officers) playing a larger role in corporate decision-making and the risk team having a greater influence on strategic planning decisions.
