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What we do know is that the more structure to the problem, the less noise or mistake you will see with any decision. Dan Kahneman discussed the problem when he wished to use algorithms with an organization he was advising on soldier selection in the Israeli army. There is significant pushback from his customer, so he came up with a bargain solution of using the set of factors associated with the decisions as a scorecard.

The scoreboard of key success factors would be done with the ultimate decision in the hands of your client given the factor information. The scorecard or checklist always resulted in a decision improvement that was much better than no checklist and almost as good as the algorithm. There could be a highly effective middle ground approach for just about any decision-making that could work well for those who do not need to turnover decision-making to an algorithm – a decision information dashboard.

Dashboards are being utilized more frequently in businesses across a wide number of areas. They are generally focused on providing up-to-date information on constantly changing data. This tool is perfect for investment management and can become more informative than a checklist. Bloomberg terminals have been tricked out as dashboards for years, but with new visual shows of information and versatile business analytics tools, dashboards took on greater timeliness and usefulness.

The dashboards can incorporate the process of the algorithm in an easy to learn format. A dashboard can be centered on a specific decision-making through using graphics and credit scoring of key factors employed in a specific decision. For instance, a straightforward scorecard on fixed income could include condition of the entire economy, the form of the yield curve, momentum, carry, expected inflation, and Fed policy.

These scorecard factors could be established to flash red or green based on the rating. The set of indicators can be aggregated to a fixed income buy/sell rating. The decision can still be positioned in the hands of the trader, but the likelihood of a noisy decision is reduced since the decision-maker would need to react against the factors that he is convinced are essential for your choice. Mistakes will be made, and the dashboard may signal false positives, but the potential for misdirected activities will be reduced. The dashboard could be arranged sign what multiple algorithms would do actually.

The decision-making problem could then concentrate on disagreement with these algorithm assessments. A reviews loop can be established for any group of decisions, so the decision-maker’s action can be matched with the dashboard score. Dashboards can force self-discipline on investment decision-makers. There’s a problem if the dashboard advice is not taken or demonstrates to be inaccurate, but it is an excellent way to impose algorithm-lite structure on decision-making.

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By channeling money from those who have it to spare, to people who can put it to good use, Wall Street and the City help drive the investment that underpins economic growth. However, many may ask why, if investment banks make so much, other banks do not enter the market and undercut their profits. Part of the answer is that very few firms have the required global reach.

To make money, an investment bank or investment company must be able to match all kinds of traders and borrowers from all parts of the world. One of the most profitable transactions usually come when a bank spots a chance to match buyers and retailers that nobody else has seen. But others claim that a lot of the investment-banking institutions’ reported revenue is not real.