The financial services industry is dealing with record amounts of data flowing faster than ever, so smarter analytics will increasingly become the competitive differentiator among financial service companies. The true strategic value of these big data streams is to predict consequential outcomes at critical decision points, optimizing operational decisions in core processes.
Faced with the challenges of how to contain costs, increase revenue, and mitigate risks, innovative advanced big data analytics solutions are being used to improve regulatory compliance, automate business processes, and enhance customer experience. Such capabilities are enabled by analyzing structured data and unstructured text within the data stores available to the banking and financial institutions. When analytics consulting expertise is combined with internal organizational commitment, the strategic value of data is greatly enhanced.
Elder Research analytics consulting services can provide support throughout the journey — from assessing analytic strategy to managing the institutional challenges of integrating analytics into operational financial systems and banking processes. Making analytic insight accessible to the right people at the right time is critical to maximizing value derived from data. Examples of our financial services analytics consulting services include:
FINANCIAL FRAUD & MONEY LAUNDERING DETECTION
Elder Research applies advanced analytics to study risky networks of financial actors, providing much greater insight into dynamic financial behavior across high volume transactional data. Applying the latest advancements in behavioral modeling, our prediction engines can identify fraud far sooner than the typical programmatic solutions, and can highlight complex, emerging trends to bank administrators before a loss occurs. Learn more.
Credit & Counterparty Risk Analytics
In today's competitive credit marketplace for financial loans, accurate credit risk scoring remains a challenge, especially as providers try to manage overall credit and counterparty risk exposure while meeting their market share and profitability goals. Using a mix of credit history, available policy alternatives, and external data, Elder Research can build robust predictive models to optimize terms and approve loans to achieve these goals for more prospects and customers, without compromising risk exposure. We can assess portfolio risk factors such as commodity prices, interest rates, exchange rates, or other factors that will impact contract maket values in order to manage default risk.
Elder Research has extensive experience in applying advanced analytics to program risk, oversight and compliance. Let machine learning help identify negative trends, anomalies, and bad behavior long before they trigger an audit.
Elder Research can provide predictive analytics and text analytics to help banks and financial services corporations acquire new customers, reduce customer attrition, and personalize customer experience through targeted products and services to improve customer loyalty and profitability. Learn more.
Elder Research partners with investment clients to optimize and verify original and third party investment strategies, develop proprietary investment modeling software, and provide trusted advice, rapid prototyping, and investment strategy consulting. Learn more.
Financial Services Case Studies
Our clients—whether newly formed analytics teams or established pros—find that we help them understand their data, strengthen their teams’ abilities, and bring to the forefront basic and advanced levels of insights aligned to their needs. Examples of our banking and financial analytics solutions include:
The project goal was to use text mining and machine learning to extract economic sentiment indicators from millions of disparate documents. Elder Research built a weakly supervised text sentiment classifier for economic indicators using the latest Natural Language Processing tools. The models make valuable new sources of data available for the client to inform decision-making such as rapid portfolio rebalancing based on continuous market signaling. Read the Case Study
Improving Credit Card Risk Scoring
Elder Research was brought in to provide an outside perspective to enhance the credit risk scoring results for a client with an in-house team of hundreds of analysts with advanced degrees. Over many years that team had honed models to world-class levels of performance. Astonishingly, Elder Research’s expertise with a dozen modern data science algorithms was able to significantly improve the prediction of bad credit risks over the client’s models.
Results: Improving the early identification of credit card accounts likely to default led to tens of millions of dollars of annual gains for the client. Read the Case Study
Identifying Risks in Brokerage Firm Applications
Elder Research designed and implemented sequence matching patterns for a regulatory agency to identify risks in brokerage firm compliance, anti-money laundering, and equity trading and market making applications.
Results: These technologies were incorporated into a product that operates on large data marts to uncover patterns of suspicious behavior and provide actionable alerts to financial institutions.
Predicting Financial Account Churn
Elder Research partnered with a diversified bank to predict account closures (churn), prioritize marketing interventions, and understand precursors to customer churn. The goal was to improve the predictive performance
of an existing account churn model that was based on heuristics in order to reduce account churn rates by at least 10% using only internal data.
Results: We built a predictive model that was 20% more effective at predicting customer churn than the existing techniques. Read the Case Study