Make every decision better than the last



No industry places a greater focus on data-based decisions than financial services. But as advanced as the industry is in this regard, more is needed. Increasing volumes of data, higher expectations from customers and bigger demands from regulators mean that every provider needs to take a hard look at their decision processes and ask: can we do better?

Financial institutions (FIs) may be more reliant on data and analytics than other sectors, with 71 percent of FIs believing analytics creates a competitive advantage, but most still lag behind when it comes to optimising decisions. Only 41 percent of banks are using advanced Big Data tools to develop actionable insights. Implementing a systematic approach to decision management is the only way FIs can make optimal decisions based on growing volumes of data and meet the demands of new regulations.

The implications of PSD2, for example, could overwhelm banks with data, if they do not have a proper process in place. PSD2 will put a significant amount of emphasis on how banks manage and structure their data and decisions processes, because they will need to be accountable to new third-party organisations. IFRS9 will place further transparency requirements on FIs, as it compels them to have decision-making models that can be monitored and checked with ease.

It is only possible for banks to meet the conditions imposed by new regulations if they can justify their risk decisions. This means having a clear and demonstrable decision management process.

Establishing a framework for accurate decision making

A six-step framework for best practice decision making can create a full cycle with a feedback loop so that every decision is not only better informed than the previous one, but more transparent and accountable too: (i) codify the decision process and domain expertise so both can be easily examined, repeated and shared; (ii) record the decision and the factors and data that led to it; (iii) model the insights with predictive analytics that can operate within your decision streams; (iv) optimise results through analytics that determine the best decisions to take given business goals and constraints; (v) adapt models so they can be applied to multiple decision scenarios; and (vi) improve decisions by measuring results, evaluating successes and optimising further.

Adapting a clear decisions process is not just about keeping up with the latest financial regulations. When decision making is simplified and democratised, it creates accountability, buy-in and innovation.

In his TED Talk, Steven Johnson notes that innovation occurs when people of diverse viewpoints and background come together “to have new, interesting, unpredictable collisions”. At a time when disruptive FinTech firms are stealing the limelight in terms of innovation, a decision-first approach might help more traditional Fis and operations to find a way forward.

How Toyota implemented a decision first approach to data

One example of this, from the world of collections and recovery, is Toyota. At Toyota, collections agents were previously hampered by an outdated decisions environment that had a lack of reliable, fresh data and an inability to connect related decisions.

This decisions process was having a serious impact on the financial status of customers, undermining some who might otherwise have been able to save their accounts. To combat this, Toyota established the Collections Treatment Optimisation (CTO) programme. The Toyota CTO programme integrates decision management, reporting and advanced analytics to implement a decisions-focused collections system driven by data. The new system is more personalised and easily repeatable. During its first year, the CTO programme helped more than 1600 customers avoid repossession and keep their cars, while preventing 10,000 customers from reaching a stage of delinquency that would affect their credit.

It has been a win-win for the company too, as Jim Bander, national manager for decision science at Toyota Financial Services, explains, “Working with delinquent customers to keep them in their cars while working out payment options has helped Toyota avoid millions of dollars in losses. Furthermore, it reduced our operating expense ratio by allowing Toyota to grow our portfolio by roughly 9 percent, without adding collections headcount. This has also enabled us to tie future lending decisions to our collections abilities – putting more customers behind the wheel of a Toyota”.

As Toyota’s work shows, deploying optimisation to handle growing volumes of Big Data can improve the quality of decisions. Not only this, but by putting a clear process in place, decisions are more transparent and accountable, keeping businesses in line with new regulations.

Above all, better decisions lead to better outcomes. This benefits customers, and makes a business more competitive. It is time to ensure every decision is better than the last.


Dr Stuart C. Wells is executive vice president and chief product and technology officer at FICO TONBELLER. He can be contacted by email:

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Dr Stuart C. Wells


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