You can’t control the sun, the wind or the snow. But using predictive and prescriptive analytics, along with optimization algorithms, you can do the next best thing.
Statnett, the Norwegian transmission systems operator (TSO) for energy, is going to use FICO energy optimization technology to power their models of the future of electricity needs in Norway and optimize the current infrastructure.
Optimization is an analytic approach to evaluate and discover successful decision strategies that meet one or more sometimes conflicting business objectives.
Instead of connecting one analytic powered decision solution to another, our customers are asking us to plan out a full, enterprise-wide, centralized decision solution.
You need to find faster, smarter and more value-inducing ways to get from the data to decisions (and actions) rapidly. Analytics are key to that process.
This is the second in a series of blog posts on deposit price elasticity, focusing on the modelling data requirements. There are several different modelling techniques and approaches to measure deposit price elasticity, which is dependent on the actual business problem and model usage. The exact data requirements might need to be amended to account for the modelling technique, but a large number of data items are consistent across all approaches. As with all modelling projects, it is good to initially take a step back and think about what type of information you would expect to be predictive, impact deposit price elasticity, and make you move your savings across different products and / or financial institutions. We would suggest that considering the below fields would be best practice for a deposit price elasticity model development: Product details: Historical interest rate of the product(s) to be modelled, this would include retention... [Read More]
Many top financial institutions have begun using predictive modelling and optimization to improve deposit pricing. This requires an understanding of customers’ deposit price elasticity — how sensitive are they to pricing changes, and what is the relationship between price and demand at the customer, segment and portfolio level? I’m going to explore this topic in a series of posts, which should be useful both to deposit portfolio managers and analytics teams. To start with, let’s look at the basics. Price elasticity is the study of responsiveness, and how the demand of a product changes with respect to price (and/or the price of competitors). Understanding deposit price elasticity, or having models that predict this, means you can quantify: Impact of a product’s price change on the deposit product How competitor price changes impact a deposit portfolio Impact of changing macro-economic conditions, such as a change in central bank lending rate How... [Read More]
In a recent post, my colleague Martin Germanis talked about the importance of optimization in collections. Toyota Financial Services has put this into practice with dramatic results. Toyota’s Collections Treatment Optimization program integrates decision management, reporting and advanced analytics to provide a data-driven, scientific and customer-centric approach to collections. During its first year, the program helped more than 6,000 customers avoid repossession and stay in their cars, and prevented 50,000 customers from reaching a stage of delinquency that would affect their credit. “Working with delinquent customers to keep them in their cars while working out payment options has helped Toyota avoid millions of dollars in losses,” said Jim Bander, national manager for decision science at Toyota Financial Services. “It’s a win for our customers, and a win for Toyota. Furthermore, it reduced our operating expense ratio by allowing Toyota to grow our portfolio by roughly nine percent, without adding collections... [Read More]
A lot of people may not know what decision trees are. Do they bear fruit? Are they hardy enough to survive inclement weather? Actually, decisions trees are an essential part of daily life. Everyone uses decision trees to plan their lives, whether or not they know it. Only we probably don’t think of them as decision trees. Should you change out of your pajamas? Will you ever find the thing you lost? Should you get a dog? Several daily life decision tree examples are posted on this site – these are intentionally funny, perhaps, but I think we can admit this stuff isn’t that far from the truth. Well, if decision trees power our daily decisions, how are businesses using decision trees to power their customer interactions? This was the key topic that my colleague Lamar Shahbazian and I recently co-presented in a short webinar, Unleashing the Power of Business Rules Development. While decision trees in business take... [Read More]
Innovation is in the plumbing of Yarra Valley Water, Melbourne’s leading provider of water and sewage services. The utility is committed to supplying recycled water to 100,000 homes, so people can continue to enjoy the natural beauty of the area without affecting drinking water availability. They’re also on the forefront of redirecting storm water to reduce pollution in the area’s scenic creeks and rivers. Their innovation is also making customers and businesses more efficient. Yarra Valley Water’s online portal for developers, easyAccess, helps expedite application approvals while reducing manual processes and freeing up employees to focus on more complex applications. easyAccess has been around since 1995; however, by 2011, the solution was unable to keep up with increasingly complex applications, and only 40% of each year’s 5,500 submissions were handled automatically — the rest required human intervention. Yarra Valley Water chose FICO® Blaze Advisor® Decision Rules Management System which enables its employees to... [Read More]