Without data, a financial analyst is just another person with an opinion. Nowadays, data has penetrated every corner of a business. Fortunately, financial analysis software speeds up the creation of reports and graphically presents the data in executive dashboards, making it easier to read and interpret than a series of spreadsheets with pivot tables. By combining internal financial information and operational data with external information such as social media, demographics and big data, financial analytics has shifted to ad hoc analyses that answer specific business questions. It is no longer just analyzing financial statements, but providing the right people with the right data to make timely decisions.
Armed with advanced technologies, financial analytics is widely applied to literally every industry. In the banking industry, for example, analytics can help to detect fraudulent activities based on a customer’s history, meet compliance and regulatory requirements of deal monitoring and trade documentation, segment customers to personalize marketing based on their individual buying habits, and to manage risks associated with liquidity and algorithmic trading through testing and real-time alerting if a risk threshold is surpassed.
Mission Critical Data Metrics Every Organization Should Have:
Sales by product
Sales by days
Sales by employees
Monthly or weekly cost breakdown
Profit and loss
Reporting in Financial Analytics
Alerts for any abnormal costs or transactions
Predictions for unit sales for next month
Optimal spend for marketing and fund allocation
When it comes to other performance indicators for an CFO, financial metrics often fall into three aspects: leverage, liquidity and profitability. Debt-to-equity (D/E) ratio and interest coverage ratio are two typical examples for assessing leverage; liquidity can often be measured by quick ratio and current ratio; as for profitability, return on equity (ROE), gross profit margin, and cost of good sold (COGS) are some of the representative metrics. [i]
As businesses rely more on data and technologies, the real engines of wealth creation have shifted from tangibles to intangibles created by talented people. As such, to measure returns on invested capital (ROIC), the metric companies care most, decision makers are taking notice of the specific contribution of each intangible. People have found that net income and market cap can be regarded as functions of the return on either capital or talent, and profit per employees is a more powerful proxy of ROIC in a digital environment where intangible assets created by talented employees are the main profit drivers. “With these metrics, the company can set its goals for the return on intangibles (that is, profit per employee) and growth (the number of employees), as well as its return on capital, which is largely a sanity check. Together, these three metrics squarely highlight—and drive—market caps.”
Integrated financial analytics is currently being applied most commonly. As its name implies, it integrates everything: fixed assets, budgetary control, general ledger, payables, receivables, goal and gap analytics; proactive intelligence, automation reporting, data preparation, enrichment and auditing, out-of-box integration, and exalytics ready.
There are many industry examples demonstrating the power of financial analytics.
Lanxess[ii], a German specialty chemicals company, migrated its business warehouse to the in-memory database SAP HANA. This technology included a management dashboard for an improved overview of key financial performance indicators and a powerful margin simulation tool, supporting both business unit and central views. “The former allows to create individualized reports with short response times for insights as detailed as the individual record level. The latter allows simulating the development of Lanxess’ profit margins depending on changes of internal and external parameters such as raw material prices or inter-company transfer prices”. Since specialty chemicals industry is highly subject to such external factors, this is extremely valuable for a company that operates multiple production sites worldwide such as Lanxess.
JPMorgan[iii] has used Palantir Technologies, a Silicon Valley company whose technology was honed while working for the US intelligence services, for fraud detection. It first used the technology, which is originally used for countering terrorism, to spot fraudsters trying to hack into client accounts or ATMs, but has started turning it on its own 250,000-strong staff. The bank also integrated and analyzed the vast amount of highly diverse information about local economies where it has troubled real estate loans, which is used to determine sold property prices before loans go into default, for reducing the social disruption caused by the troubled loans.
All in all, analytics is meant to redefine the art of the possible.
[i] L. Bryan, Lowell (2007). The new metrics of corporate performance: Profit per employee. McKinsey&Company. Retrieved from here
[ii] Bärenfänger, Rieke; Gizanis, Dimitrios; Otto, Boris (2015). Business and Data Management Capabilities for the Digital Economy. Corporate Data Quality. Retrieved from here
[iii] Waters, Richard (2012). Counter-terrorism tools used to spot fraud. Financial Times. Retrieved from here