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AI makes zero-based budgeting a practical finance tool

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AI makes zero-based budgeting a practical finance tool

Experts in the pursuit of harnessing nuclear fusion will assure you that the technology is coming — just 30 years away, according to their projections.

The joke is that if you wait three decades and ask them where it is— they’ll say the same thing.

In finance and procurement, the concept of zero-based budgeting has long been a bit like the pursuit of fusion power: more of an aspiration rather than something any real-world corporation can actually implement today. 

Which is unfortunate. Like the idea of the world utilizing the free, non-polluting energy that a fusion plant would offer, on paper ZBB promises objective, data-based baselines for every budgeting phase that would allow decision-makers to only work with what’s real and current, not what happened last year, or even farther back.

The proposal with ZBB is that by mandating a comprehensive justification and validation of each expense, rather than relying on historical spending patterns, organizations can remove possible blockers within their procurement processes. This approach aims to ensure that what you’re doing is the numerically provable best case for the specific circumstances at hand.

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This approach certainly holds immense appeal, so much so that Jimmy Carter tried and failed to make federal government adhere to this discipline in the second half of the 1970s. However, ZBB never really gained traction or widespread adoption, and so its aspirations were largely relegated to the realm of “theory taught in business schools but lacking practical viability.”

The factors putting ZBB back on the table

History and controversy aside, the core idea of ZBB is clear — it presents CFOs with an approach that mandated comprehensive justification and explicit approval for all expenditures during each new budgetary cycle, typically at the outset of the financial year. This process ostensibly offered CFOs a way to make relevant decisions against a true picture of the company’s cash flow.

But ZBB never truly went away. In fact, it is experiencing a resurgence. Consulting firms like McKinsey have reminded us that if we could weigh the value of every dollar and start afresh with every budget cycle we could mitigate the risks associated with operating on outdated information and boost overall performance outcomes.

ZBB idealism is also happening at the micro-level, with social media influencers hopping on the ZBB bandwagon. Influencers like Beth Fuller have attributed their ability to pay off credit card debts to following online content creators who advocate for ZBB principles.

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The question then becomes how would we make ZBB, long an ideal but one that proved too difficult to implement, work at the enterprise level? It turns out, a viable way exists, or at least we can start the process to get there. 

And you won’t be surprised to learn that the game-changer here is AI.

A way to open the door to ZBB

Currently, the spotlight within the artificial intelligence domain is on finding use cases for AI to solve real business problems. Organizations have been at the forefront of this endeavor for several years through an approach we term “autonomous sourcing.”

Specifically, organizations using an autonomous spend management approach source can purchase as many new services and vendors as they need within a given budgetary cycle. However, this process is underpinned by not just genuine and up-to-date market data, but also with the benefit of a corporate knowledge bank.  This knowledge base facilitates multidimensional comparisons, enabling organizations to evaluate purchases not only longitudinally (against previous periods) but also orthogonally, meaning across different business units within the enterprise. 

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This may not be the precise dictionary definition of ZBB. But it represents a radical change from the lack of data and visibility CFOs have struggled with and a way to open the door to the underlying vision of ZBB: data-driven financial accuracy.

This autonomous spend management approach resonates with organizations seeking to rationalize and optimize their budgeting processes, often commencing with their procurement operations. These forward-thinking entities inherently grasp the transformative potential of leveraging machine learning and generative AI capabilities to tackle the sourcing problem.

And the convergence of machine learning, generative AI and autonomous sourcing platforms presents organizations with the ability to realize approximately 90% of the ZBB ideal in the present day. That’s happening via organizations using autonomous sourcing to consciously and strictly seek to rationalize every purchase and make data-driven decisions on every vendor relationship.

The commitment to data-driven evaluation of vendor relationships is actually super-important on the path to any form of zero-based decision-making basis. Why? Because it’s your best way of ensuring that you’re not locked into any partnerships or contractual arrangements that aren’t continuing to add value.

Even starting to explore this area of spend with proper data and analytical tools can move organizations off the proverbial sandbar of inefficiency. Last year, for instance, the Mays Business School published research that concluded the simple act of tracking a single category of expenditure can catalyze a reduction in overall spending.

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The exciting prospect lies in the potential for modern businesses with diverse spending categories like marketing, HR, sales, IT, finance, and others to capitalize on significant cost-saving opportunities through AI-powered procurement solutions, e.g., accurate supplier sourcing and matching, e-negotiation and automated awarding capabilities.

ZBB’s future is now, not 30 years off

President Carter’s administration wanted to achieve such objectives and possibly on paper could have done — if they had all the time in the world, and exclusive access to the entire computing power of the United States at the time.

But even under those circumstances ZBB might not have worked — as without the efficiencies afforded by AI, ZBB would require manual sourcing, selecting, bidding, negotiating and awarding for every single purchase and vendor relationship in the business. 

The truth is, fulfilling every aspect of ZBB manually, as envisioned by its originator, Pete Phyrr, is an insurmountable task for humans. However, using the power of AI to automate numerous processes, alongside giving  individual business units the autonomy to source and complete their own purchases through autonomous sourcing, means ZBB becomes not just practicable, but essential in today’s dynamic business landscape.

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Weighing it all up, maybe we can retire the notion that ZBB is the accounting industry’s version of fusion.

Instead, we can use the power of autonomous sourcing to perform the equivalent of fusion in the back office.

Finance

SRG Housing Finance Q4 Results Live : profit rise by 45.65% YOY

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SRG Housing Finance Q4 Results Live : profit rise by 45.65% YOY

SRG Housing Finance Q4 Results Live : SRG Housing Finance announced their Q4 results on 23 May, 2024, showcasing a significant growth in their financial performance.

The company reported a 38.64% increase in revenue and a 45.65% rise in profit year-over-year.

Quarter-on-quarter comparison also revealed positive growth, with revenue growing by 13.89% and profit increasing by 14.46%.

However, the Selling, general & administrative expenses saw a noticeable increase, rising by 8.82% sequentially and 43.86% year-on-year.

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Similarly, the operating income also showed a positive trend, with an 18.1% increase quarter-on-quarter and a 42.73% rise year-on-year.

The Earnings Per Share (EPS) for Q4 stood at 4.72, marking a 29.67% increase year-on-year.

In terms of market performance, SRG Housing Finance delivered a 2.84% return in the last week, 0.87% return in the last 6 months, and a 1.99% year-to-date return.

The company currently holds a market cap of 378.12 Cr, with a 52-week high/low of 336.75 and 230 respectively.

SRG Housing Finance Financials
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Period Q4 Q3 Q-o-Q Growth Q4 Y-o-Y Growth
Total Revenue 36.15 31.74 +13.89% 26.07 +38.64%
Selling/ General/ Admin Expenses Total 7.64 7.02 +8.82% 5.31 +43.86%
Depreciation/ Amortization 1.71 1.58 +7.86% 0.97 +76.31%
Total Operating Expense 28.79 25.51 +12.86% 20.92 +37.63%
Operating Income 7.35 6.23 +18.1% 5.15 +42.73%
Net Income Before Taxes 7.61 6.7 +13.64% 5.37 +41.65%
Net Income 6.09 5.32 +14.46% 4.18 +45.65%
Diluted Normalized EPS 4.72 4.09 +15.33% 3.64 +29.67%

FAQs

Question : What is the Q4 profit/Loss as per company?

Ans : ₹6.09Cr

Question : What is Q4 revenue?

Ans : ₹36.15Cr

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Published: 26 May 2024, 02:27 AM IST

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G7 finance ministers back plan to use Russian assets for Ukraine funding – the FT

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G7 finance ministers back plan to use Russian assets for Ukraine funding – the FT

Stock photo: Getty Images

The G7 finance ministers supported the idea of providing Ukraine with a loan secured by profits from frozen Russian assets to ensure funding for Kyiv after 2024.

Source: Financial Times, citing the draft communiqué of the ministers’ meeting, as reported by European Pravda 

The ministers’ discussions were based on a US proposal, which was circulated before the meeting in the Italian city of Stresa, to issue Ukraine a loan of about US$50 billion, to be repaid from the profits of the Russian central bank’s assets amounting to around €190 billion. 

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The ministers stated that they were “making progress” in working out options to “bring forward” the profits, according to the draft communiqué. They added that options for structuring the loan would be presented to the G7 leaders before the June summit.

They also promised to continue pressuring China to reduce industrial subsidies that they believe are driving Western competitors out of business, and stated that implementing the most significant global tax agreement in more than a century is a “top priority”.

The G7, a group of advanced economies that includes all major Western allies of Ukraine, aims to ensure funding for Kyiv in the long term, even after this year when crucial elections will take place on both sides of the Atlantic. 

According to people familiar with the negotiations, many details of the loan are yet to be agreed upon, including the amount, who will issue it, and how it will be guaranteed in case of Ukraine’s default or if the profits do not materialise. 

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One official mentioned that Europeans are particularly concerned about “fair-risk sharing”, fearing that Europe will bear the brunt of the financial and legal risks and potential retaliatory actions from Russia, as most of the assets are located on the continent.

This week, the EU officially approved a plan to use interest from frozen Russian assets, which, according to estimates, could bring up to three billion euros per year to Ukraine.

Background:

  • In February, the United States argued that G7 countries should fully seize frozen assets, but later abandoned this idea due to concerns from allies that it could set a dangerous legal precedent and prompt retaliatory measures from Russia.
  • Earlier, Minister of Foreign Affairs Dmytro Kuleba stated that Ukraine insists on the confiscation and transfer to Ukraine of all frozen assets of the Russian Federation held in the West.

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Big Players Maneuver In Global Finance And Industry

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Big Players Maneuver In Global Finance And Industry

What’s going on here?

From hostile takeovers to strategic acquisitions, major financial and industrial players are making bold moves to bolster their market positions. Spanish bank BBVA, Swiss private bank Julius Baer, and British IT services group Redcentric are all in high-stakes negotiations for potential mergers.

What does this mean?

BBVA’s €12.23 billion hostile takeover bid for Sabadell marks a major potential consolidation in the Spanish banking sector, despite opposition from Madrid. Julius Baer’s talks with EFG International highlighted competition in Swiss private banking, though discussions have ceased. In IT services, Redcentric’s negotiations with Milan-listed Wiit SpA could lead to a substantial acquisition. Additionally, private equity firm Carlyle is preparing to sell aerospace manufacturer Forgital, signaling increased activity in the aerospace sector. Also, Deutsche Bahn is advancing in the bidding process for its logistics subsidiary Schenker, with four contenders still vying for it.

Why should I care?

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For markets: Strategic consolidations and divestments.

These moves reflect broader trends of consolidation and strategic realignment across industries. BBVA’s bold bid for Sabadell and Criteria’s acquisition of a 9.4% stake in ACS for €983 million signify aggressive strategies to capitalize on market opportunities. Carlyle’s plan to sell Forgital and Saudi Aramco’s in Repsol’s renewable energy division highlight the growing focus on portfolio diversification and sustainability.

The bigger picture: Global shifts in financial and industrial landscapes.

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These developments indicate profound changes in the global financial and industrial sectors. KKR’s likely approval to acquire Telecom Italia’s fixed-line network without EU antitrust conditions signals a favorable regulatory climate for strategic deals. On the flip side, the Italian government’s decree for state broadcaster RAI to possibly merge its tower unit, RaiWay, with EI Towers shows the fluidity of managing national strategic assets. Meanwhile, Coventry Building Society’s £780 million purchase of Co-operative Bank underscores ongoing consolidation in the British banking sector.

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