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One idea at a time.

Practical reads on earning more and losing less with data and AI. One idea, one number, one thing to try.

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7 results for “risk”. Show everything

Data & AI

AI agents in finance: what they can do today, and what still needs you

AI agents can now gather data, run checks and draft the next step across several systems. In finance that is useful and risky in equal measure. A practical look at where they help, where they don't, and how to start.

2 min read
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Continuous controls monitoring: a buyer’s guide

Continuous controls monitoring promises to test every transaction, every day. Before you buy, know which controls to start with, what an alert should look like and who will act on it.

2 min read
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Know every vendor by what it does: TPRM beyond questionnaires

Third-party risk programmes run on questionnaires that vendors fill in once a year. The risk shows up somewhere else: in payments, bank changes, filings and the news. Here is how to watch it.

1 min read
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Paying MSMEs in 45 days: what Section 43B(h) means for your P&L

Under India’s Income-tax Act, late payments to micro and small suppliers can cost you the tax deduction for that year. Here is how the rule works in outline, and how to know which invoices are at risk before year end.

2 min read
Earn $

Idle cash is a cost: a treasurer’s checklist

Cash sitting in the wrong account, in the wrong entity or for too long earns little and costs plenty. This checklist shows where it hides and how to put it to work without adding risk.

2 min read
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Private Gen AI for legal teams: ten questions to ask before you buy

Generative AI can read a contract in seconds. Before it reads yours, know where the data goes, how answers are checked and who stays accountable. Ten questions to put to any vendor.

2 min read
CoSaaS

Pay for what you deploy: the end of shelfware

Enterprise software is often bought in bundles and used in parts. The rest becomes shelfware: paid for every year, used by nobody. Paying for what you deploy changes who carries that risk.

1 min read

See it in practice

Use cases from our own project work, anonymised, and scenarios that show the method: one problem, the checks we run, what they find.