Operational research in development banking in India

Operational research in develc,pment banki.ng in India R. BANDY:~gPADItYAY National lnstitt te o f Bat, k Management, Bombay, India Received 22 January 1976 Revised 20 April 1977 The paper teFmes development banking as practised by major Indian commercitl banks since 1969. It then goes on to discuss how OR can be useful in tackling problems of development tanking. Planning, operational and organisational design problems in relation to development banking are discussed. Several ease studies in each area where OR has been applied are discus;cal. Potential areas of application of OR in each problem clats are also identified. The paper then summarizes the experience, gained so far and recommends the action to be taken 'or the more effective application of OR in developi lg economies.

1. Introduction Development banldng in the traditional sense was mostly concerned ~ith the problems of industrial development. In the case of developing economies, development banking has a wider connotation. It means creative assist~nce in all forms of development - industrial, agricultural and others - for the growth of the economy. Fmthermore, development banking so directs its efforts ':hat the disparities in respect of developmenL both ,egional and sectoral are minimised. In the cot text of the Indian economy, the nationalised banks are experimenting with development banking in the wider sense. The Indian experience is relevant to nanny o:her developing economies and The author wishes t~ tl~ank all his colleagues in the National [nstitute of Bank Management who helped him ha preparation of this paper. He would also ~ e to express his gratitude to M,-. J.M. WiUiamson of Inter Bank Research Organisafion, U.K., for carefuliy going through the draft of the paper and su~esting a nlLrnber of improvements.

O Nor|h-Hollarfd Publishing Compaziy European Journal of Operational Research 2 (1978) 8 - 2 5 .

considerable attention is being focussed in the world on this experiment in development banking in India. The paper tries to analyse the basic problems of development banking (as defined above) with special reference to India. It then sets out to examine the role that Operational Research can play in such development banking activities. The paper describes a few actual ,:ase studies where Operational Research methodology and models were applied in the solution of development banking problems in India, indicating also the difficulties faced in applying these methodologies and in constructing these models. Ille r,lethodo1ogjcal issues involved are also briefly discussed. It then describes the various areas where Operational Research can be successfully applied. The paper, therefore, is divided into two parts: (a) The first part sets out the background of the type of development banking practised in India and the 0asic nature of the problems that the Indian economy faces. (b) the second part, then goes on to elaborate the application of Operational Research in the solution of some of the problems. It indicates the various methodological problems faced and the ways adopted to circumvent these problems. The paper also outlines potential areas for the application of Operational Research in development banking and suggests new areas for research in methodology and model building.

2. Indian banking scene Banking in India was modelled on Scottish Banking. Its main concern was trade and commerce. During the 1950's, industry also came into the fold of banking activities. Till 1969, bank branch networks were unevenly distributed. Most of the branches were in metropolitan and urban centres, metropolitan centres having a large proportion of the total number of branches. The lending of banks was also concentrated in metropolitan centres. No bank finance was advanced to agriculture. Mostly, bank finance flowed to large commercial/industrial houses. However, in the 1950's and 1960's it was increasingly felt that banks were not being adequately utilised as instruments of development of a poor country like India and in 1969, major banks were nationalised with a view to ~sing banks as instruments in the effective development of the economy. A deliberate change of policy was felt necessary

R. Bandyopadhyay /OR in development banking in Ind&

after ~ationalisation. Specifically: (a) more stress had to be placed on extending banking to rural and semi-urban areas with the result that banks must have more branches in states relatively under-developed and undeveloped, in respect of branch networks, (b) more bank finance should flow to agriculture, small scale industry and exports, (e) banks should become catalysts in initiating a process of total development in a region. With this end in view each of the districts of the country (a total of about 350) is allocated to a different bank. The bank to which a particular district is allocated will act as the leader of the consortium of banks engaged in the development of the district. The lead bank will thus act as co.ordinator of the banking and development activities initiated by banks operating in the district. In view of their changed roles, banks are becoming more and more concerned with regional development and in meshing each bank's development planning with the national, state and regional development plans. At first, banks had very little experience in this and they turned for help to modern methods of planning and implementation. The situation, therefore, was one where the decision-makers, because of their relative inexperience in the new situation, have been more prepared to adopt new methods and models provided the same can effectively deliver results.

3. OR in banking OR applications in banking and finance are relatively new ew;n in devdoped econorn/es. Judging from the list of titles of papers in the First International Conference of OR Applications in Banking and Finance held at Montreal, in October 1971, it can be seen that apart from studies of porttblio planning very few new areas of application have been reported recently. Planning, branch location and scoring models have been reported in Eilon and Fowkes [12]. Similar applications in the U.S.A. are reported in Jessup [ 16]. As pointed out earlier, the nature and complexity of the problems of development banking are quite different from those of similar types of problems in developed economies. Models and techniques used for solving problems in banking in developed countries may not, therefore, be relevant and it is often neces-

9

saW to devele,p appropriate models and techniques from first principles. However, it is found that the basic scientific methodology of problem formulation and solution is not different [4,5]. In India, before 1970 no application of GR methodology was attempted in banks [ 11 ]. Even now, it is felt that no individual bank except the largest bank (the State Bank of India) can afford to have fullyfledged teams on OR or Management Science on a permanent basis. However, the National Institute of Bank Management set up by all the banks in the country has built up a team of experts in various disciplines including OR, Statistics, Economics and Behavioural Sciences to tackle the problems of development banking with the aid t,f scientific methodologies and models. In view of the unexplored areas in which banking activities were launched in 1969, the nature of the problems and their relative priorities were not dear to the decision-makers, both at the policy and operational levels. The clear specification of the objectives of new banking was also not forthcoming. The National Institute of Bank Management as a body of expert problem solvers, therefore, organised first a series of seminars and workshops at policy level; to specify the objectives dearly, to identify the various problem areas and to indicate their relative priorities. The problems identified by the National Institute seminars can be convenJ ~ ,tly classified fi~r the purpose of our discussion into the following three groups: (a) planning problems; (b) operational problems (standards, procedures, etc.) including development of methodology and criteria of appraisal of various types of projects for bank financing; (c) organisational design problems. They are discussed in turn in the follcwing paragraphs.

4. Planning problems and planning models 4.1. Two types o f model

Studies of planning problems led to models being developed in this area of two types: (a) industry-~vide planning models dealing with planning problems of the banking industry as a whole; (b) corporate level planning models dealing with planning problems withha a bank.

tO

R. Bandyopadhyay / OR in development banMng in India

All the mc~deh under (a) and (b) are multi-level in

chanct~r [6,18]. 4.Z Industry-wide planning models ...............

In view of the new role o f the banks as set out in Section 2 o f this paper, the need for integrating banking development plans w~th the national development plan is being ~creash~gly felt. The case for such integration has been argued in detail in Bandyopadhyay and Mampilly [6]. The first step in the process of integration is to evolve a five year banking plan consonant with the objectives a n t priorities set out in the five year plan of national economic development (Sth Five Year Plan of India) [29]. The plan basically concentrates on ensuring an adequate banking presence in all parts of the c o u n t ~ to enable banks to play their role in the implementation of the national economic development plan. The objec:ives of branch expansion planning can be specified a; follow~.,. [31]: To evolve a scheme for the allocation of the branches to be oper~ed during the planning period (January 1974-March 1979) so as to effect the max. imum possible reduction in the currently existing disparities in respect of tanking presence (i) among various districts of the country, and (ii) between the under-de,veloped areas and more developed areas w i t ~ l each district. To achieve the above objectives the following measures for identifying disparities are used: (a) To measure banking presence in a ¢'~istrict or in an area w i ~ a district, the criterion of population served by a branch is used. ! (b) Because criterion (a) may not at all be a relevant measure for rural areas it is felt that in addition to criterion O) we should use a measure for banking presence in raral areas in terms of the gross cropped area served ~ r rural branch in the district. The existing situation of the various districts as regards the ~fiteria .of population served/branch is shown in Table 1. Table 2 shows the existing distribution with respect to the gross cropped area served per rural branch. Frequenc) curves are shown in Fig. I of the numI One can righzfully qu,~xtel with this criterion. In fact for location models the criterion was found inadequate and had to be supplemented by micro level detailed studies. Problems of criteria require further reseaxch.

Table 1 Population/branch ('000s) 1.

0-10

2. 3. 4. 5. 6. 7.

10-20 20-30 30-40 40-50 50-60 60-70 8. 70-100 9. Beyond 100

Number of districts 8

30 56 38

33 34 30 54 55

ber of districts versus the population per branch for commercial banks in December 1973 and at the end of the planning period following the use of the branch alioeation model which was developed. The methodology followed in developing the model mainly depends on: (i) the specification of feasible policies regarding branch allocation in districts, and (ii) the specification of feasible policies regarding branch allocation in rural areas. At the end of 1979 a national average of population served/branch of 25 500 should be achieved. How far removed will we allow any district to be from this average figure? To bring all the districts below average to the average figure would require a vast number of branches to be opened in relatively undeveloped areas and many branches cannot be economically viable in those areas. Here, therefore, we have to strike a balance between the objectives of homogeneous banking development and economic feasibility. Basically for any district we have to relate the final number of branches to the existing number of branches. If/~i) = the population served per branch at the end of the planning period in the ith district, and P
Table 2

1. 2. 3. 4. 5. 6. 7. 8.

Gross cropped area/branch (kin2)

Number of districts

r-a~ 50-100 100-150 150-200 200-250

15 39 31 22

250-400

65 65 73

400-600 Beyond 600

28

R. Bandyopadhyay / OR in development banking in India

11

Table 3 14o

_12o

x'°°l •

X

I/

15

30

45

60

75

90 1,051,201,351,501,650,80

Population/branch at the end of plan

Range in re/ation to national average

Number of distriers

Below 25 500

Below national average

145

43.4

25 000 to 50 000

Between national average and 2 times national average

142

42

51 000 to 76 500

Between 2 times national average and 3 times national average

50

Above 76 500

Beyond 3 times national average

0

0

337

100

Population per branch (in thousands)

Fig. 1. Frequency curve of population per branch o ~ scheduled commercial banks.

the beginning of the period, then p~i) = f(P(oi)). Identification of functional relationship f i s crucial to the solution of the allocation problem. To fix f, we feel that the additional 9 000 2 (an increase of 55% on the basis of about 16 500 branches as of December 1973 for the banking system) branches to be opened in the planning period should be so allocated that at the end of the planning period no district has a population served per branch more than 3 times the national average of population served per branch. Similarly, at the end of the planning period, no district should have a number of rural branches such that the figure of gross cropped area served per rural branch in any district will be greater than 1.25 times the national average figure of gross cropped area served per rural branch. Having specified these limits it is seen that no district will have a population per branch of 76 500 or more. The revised frequency curve will thus have its centre only a little to the r i o t of the net average of 25 500 and will have equal arms spreading from about 5 000 to 50 000 (maximum distance between arms has been reduced to 45 000) only a few districts will lie between 50 000 to 76 500. Thus, at the end of the plan period we get the allocation as shown in Table 3. Similarly the distribution is substantially altered with respect to rural branches. The transition curve relating the 1979 position to the 1973 position which is heuristically determined is shown in Fig. 2. From the curve we can easily read off how a district in 1973 should move in 1979 with 2 This is the total number of branches which are proposed to be opened in the whole country in the p a n n i n g period. The problem is of allocating these branches among various districts consistent with objectives specifi, d.

Total

Percenrage

1,1,.6

respect to population served per branch. Interested readers can find an excdlent exposition of the mendel oa which this curve is based in Varde et al. [31]. In summary, the mathematical formulation is as follows: p i) = K a

.

Taking log log/~l) = log K + (log a) bP~i) .

(2)

Where log K is the location parameter, log a is the scale parameter, and b is the shape parameter. In our model (i) log a is negative, (~) 0 < b < 1, (iii) antilog (log K + log a) is the ordinate of the first point of inflexion on the curve, (iv) K is the ordinate of the upper asymptote of ' the curve.

It may be seen that it is a Gompertz type model. o~

,.°°[

~ 8o4°°

2o i 0 o.

e o do 1,001,201.401.601.80 2.0~ 2,20 2,4o

Population per branch-Dec. 1972 (in thousands)

Fig. 2. The transition curve for total number of branches in a district.

12

R. Bandyopadhyay / OR in development banking in India

In view o f Sl~;cial cut off points selected and the national average Pt = 25 500 we have (i) antilog (log K + log a) = 25 500

(3)

(ii) K = 76 500 + 5

(4)

where 5 is a small positive number

Hence~ in this case location parameter K = 76 500 + ~ ,

(5)

scale parameter a = 25 500/(76 500 + 5) -~ 0 ~3.

(6)

Now saape parameter b is heuristically determined so that the desired distribution of the Table 3 is satisfied. The allocation of rural branches to districts is tackled in a similar manner. 4.3. Industry-wide planning model for a state

The model described in Section 4.2 is a model for the allocation of branches to districts. However, considerable problems exist after the allocation process in deciding the location of branches. Without an appropriate location model, location decisions are often nade on an ad hoe basis and may not be consistent with the objectives of the programme of branch expan:~ion for economic development. The removal of regional disparities can dominate such locational decisions. Furthermore, the opening of a branch requires a lot , f preparatory work before the event (such as preparing premises, familiarising staff with the locality). Ad hoe location decisions ,50 not allow adequate time for preparation. Planning the location of branches as well as the allocation of branches is very important but branch locational models available in the literature axe not found to be very relevant in respee~ of the problem at hand. The consideration of serving the rural areas as homo/~eneously as possible guides model construction. On the basis of pure economic and business considerations or followin~ traditional demand centre analysis, the chances are that all the branches would be located in district headquarters and important business centres even though these are already adequarry served by branches. Here is a situation where we have to adopt the policy o f creating an adequate enviro::u-aent to support a branch. It is a case of locati~:g a branch with a view to developing a demand for banking services rather than locating it in a centre of existing demand. Thi~ is a specific problem relevant to developing

economies and existing models in the literature are of little value in this respect. Padwal [24] was the first to make a serious attempt in developing an appropriate model for these situations (see also [27]). The location model developed here is a laodification of the model developed in Padwal [24]. The essential steps are shown in the flow chart Gf Fig. 3. It may ~z. seen that given that n* rural branches are to be opened in a district, deliberate strategies need to be adopted to reduce disparities between different areas of the district. We have, therefore, attempted detailed locational planning at the block level (a block is the smallest administrative division within a district; a block consists of a number of villages within its jurisdiction). It may be further noted that the model requires the calculation of an interaction index viz., I, =

i

x pj

a,/k

(6)

where Pi is the population of the ith village in the block, p] the population of the ]th village in the block, di] is the distance between i and L k a suitable index to be empirically determined, Ii is the interaction index of the ith village in the block. In case of a tie, i.e. same value of index, connectivity of competing places needs to be determined. Among other things the model highlights the need for co-operation among various development agencies in rural areas. If infra-structural facilities include health centres, high schools, roads, drinking water supplies etc. various government agencies respop.sible for development of these facilities must be consulted to prepare a feasible branch location plan over the planning period. The ,nodel helps to identify the infra-structural developments needed for the branch expansion programme in the rural areas and development agencies' plans can then be suitably cast to take care of these needs. Locational decisions must take into consideration also the question of profitability. In our flow chart model, this has been omitted in order to keep the diagram relatively simple. For assessing profitability, the likely future business of the branch in terms of depe?;" ~, ~,~eOltS, oil!s, etc. needs to be estimated. The starting point in this is the assessment of deposits. An attempt has been made to relate prominent economic variables to deposits of rural branches by regression analysis but the results are quite disappointing. We know that D = f(a, s, E, e)

(7)

R. Bandyopadhyay / OR in development banking in b,dia

[' I

Identify & draw command areas of existing bank branches

,denti~Gaps

j Identify block cad quarters I in gaps with adequate infraLstructural facilities (nl)

i

i--,o I

I

|

No

No

I

those segments wi,h ,,only one centre (ris)

I

Find

Allocate brt riches (nO to b!ock head q uarters

J

Find m,=,n*-n,

J

I

Allocate requic;te number of branches to places in order of ranking

J,

)

n4=n2-na

J

Redraw command areas of na branches allocated

iI

,J Rank places according J ' 1 to interaction-index J | in case of tie, rank J ~ l t i e d places accor¢ing I ],to connectivity ..J

Yes q

J

13

I

Identif,Oaps I segments .

~ No [ identify Segments I | without even one J I such centre (n7) J

Redraw expected command areas of n~ branches allocated

[.

l

ld.nti,, aps

l

' Identify market places in the J gaps having infrastruclural facilities needed (n3) <~.

I Su-enderrem~o I

"~"~'77"")"

I branches to non rural[ J areas of the district ]

.,,~Yes

Yes

/-

J Allocate-branchesto-i

'No

I n, places where faci- I J lities can be built ]

,No Allocate ~ranchesto n3 market places

y ! [

Allocate n7 branches

! ]

]

I Fig. 3. Flow chart model of rural branch location.

where D = deposit accretion; a = age o f the branch; E = a vector representing the total socio-economic environment in which the branch operates; s = saving habit o f the people in the area; e = effort expanded on business growth, It may be seen that measurement o f some o f these variables is quite difficult. How to measure s? Elaborate research may be required to evaluate s. s varies from place to place and from time to time. Is the

elaborate research cost commensurate with the gains of the analysis? How to measure e? Somc of the factors constituting E are also quite difficult to measure. Even if all the factors are separately measurable, their combined effects on deposits may not be easy to determine. One is here faced with the very important secondary decision problem [32] of striPdng a balance between the modelling cost with improved measures and data, and the corresponding gain. Furthermore, the time available must also be considered in deciding

14

K Bandyopadhyay /OR in development banking in India

whether or not to attempt to solve basic methodological problems of measurement and data gaps. In practice relative improvements in modelling are best sacrificed in the interests of less sophisticated feasible models which can be quickly constructed and solved and whose ~esults can be implemented usefully. The simplicity of the model and the measures used are likely to increase the use and implementation of the model. Cor~plex and sophisticated methodologies should therefore, be deliberately avoided. Since no ~f'mite relationships could be established between deposits and environmental factors; and as we had little past data of bankLrtg behaviour in the areas where branches would be opened, it was felt necessary to study banking behaviour in similar areas elsewhere where branches existed already. With this end in view, the areas were grouped into similar agroclimatic re~ons and in each region the growth of rural deposhs over time were studied. Three sets of figures in e~ch region for each age group were obtained - these were the maximum, average and rain. hnum figures of deposits. It was found that the maximum and rr~inimum obtained in branches of the same age group in the same agro-climotic regions differ substantially. If one assumed that the environment (socio-econcmic) was the same, the difference could be explained only in terms of intangible factors like the creation of goodwill through effort and dynamism etc. One could have assumed a beta distribution and could Lave estimated the expected deposit business for a Lranch of particular age group. However, we felt that such expected value would be less useful operationally than the three figures together. It was left to the vranagement to decide whether they would plan to achieve the maximum or the average; in no case they s~ould expect less than the minimum. This discretion t~ig~ered more plan~ed action and dynam-

\,

60 50

ism, than a single figure of expected business on the assumption of beta distribution would have done. Moreover, decision-makers both at policy level and operational levels understood these three measures perfectly and felt at home in translating the models into practice [30]. Based on the deposit figures, the economics of newly opened branches (proposed) were worked out in detail. Nomographs were developed which indicated (for a given transfer rate practised by a bank and for a particular level of annual operating cost for a branch) the various combinations of de,osits and advances leading to earnings equivalent to, or more than annual operating costs of a branch. Fig. 4 shows a series of such iso-income curves. Mathematics involved in drawing these curves is relatively simple and school-level.knowledge of algebra would be adequate in understanding the method. Though simple, the nomograph models developed for profitability assessment found wide acceptance among bankers. Curves give instant help to the policy makers to assess (based on their cost estimates and estimates of likely deposits and advances) when a branch is likely to break-even or to know whether the branch can break-even at all within the plan period (see Fig. 5). The decision-makers can then make a conscious decision whether to open a branch in the place under consideration in view of its distributional and other desirable social effects. These provide useful aids to integrate experience and judgement with some scientific analysis to arrive at branch opening decisions, and make the trade-off between business

.#//

$.of~

t "L/ Income figure is cWuri~t"n ~ea,°ng the

/

'°°-'" 1~ yearcost

/ i

i

1

~

"- 20 ~t

Thelevelof depositsis written

J l 10Lt (0.5,0)

1.0

I15 2".0 Deposits (Rs. in millions)

2.5

Fig. 4. Iso-incomecurvesfor transfer rates of 6.5% and 8.0%.

:

;

:

:

:

:

-:

._ :

10 20 30 40 50 60 70 80 ~0 ~Wancm (%) Fig. 5. Graph showing income lines for vaxious levels of advances and for transfer rates of 6.5% and 8.l~o.

R. Bandyopadhyay / OR in development banking in liadia

profit (or loss) and social objectives more explicit and dear.

4.4. Credit planning models Having decided the total number of branches and their appropriate locations, it is desirable to channel the credit available to appropriate productive activities so that the desired objectives of development banking can be achieved. Credit may be channeled to maximise a social-benefit function subject to various business and organisational constraints like minimum acceptable level of profit, maximum number of staff available for manning new branches, etc. Alternatively credit can be so channelled as to maxhnise profit subject to various social and organisational constraints. Various alternative models having different objective functions and constraints within a linear programming framework can be suggested. Policy makers can be offered the opportunity of selecting the model which best corresponds to his preferred ob-

Table 4 Summary of models Model

Objective function Constraints a

Model I

Maximise deposits through credit

(a) Minimum level of credit (b) Bank's growth

(c) Spatial spread (d) Liquidity requirements (e) Maximum permissible servicing cost Model il

Minimise servicing cost

(b), (c) and (d) above (f) Minimum credit to vari-

ous sectors (g) Maximum limit of credit Model II!

Maximisation of profit

(b) (e) (d) (e) (f) and (g)

above (h) Minimum level of social benefit to a region/sector (a) to (h) above

Model IV

Maximisation of GNP

Model V

Maximisation of net social benefit

(a) to (g) above

Model VI

Maximisation of employment

(a) to (h) above (i) Max/mum permissible level of uneraployment cost

(j) R~-sourceconstraints a Constraint spech"/cationsare only indicative and not exhaustive.

15

jective function. Table 4 lists the various alternative models constructed [7]. Some of these models are now being tested empirically. These models may in future greatly help in rationalising credit allocation decisions to various produc. tire activities to serve the twin goal of economic development and removal of regional and sectoral disparities. In solving these models, and in evaluating the co-efficients difficult problems of measurement are being faced. Problems of measurement of social cost of unemployment (specially the cost of frustration arising out of a long period of unemploymerlt) in the employment maximisation model have been discussed elsewhere [7].

4. 5. Corporate planning models The planning models so far discussed are industrywide models; though the credit planning models discussed in Section 4.4 can be used both at the industry level and also at the corporate level. Industry-wide models become operational only through action programmes of individual banks constituting the industry. Thus, corporate plans for individual banks for the planning period (considered in the industry-level planning) need also to be developed. Up until 1970, formal planning in Indian commercial banks was conspicuous by its absence. However, in view of the new roles assigned and complexities involved in efficient discharge of these roles, integrated and planned development of vari~'Js banking functions and the appropriate allocation of resources in discharge of these functions soon became an urgent necessity. Hanning efforts were initiated in banks and annual business plans were drawn up. However, these plans often did not take into consideration all important functional inter-linkages explicitly. To correct this, a corporate planning model was cleveloped [3]. Basically the model developed was concerned with the development of annual corporate plans and long term corporate planning models were not constructed. Along with the development of htdustry-wide planning models for a period of five years to integrate with the five year development plan, the need for con. strutting long term (five yearz) corporate plans is being strongly felt. In what follows we shall ve~' briefly describe the methodology adopted in drawing up a five year corporate plan for a bank. Recent literature in Operational Research has

16

tL Bandyopadhyay / OR in development banking in India

many references to long term corporate planning models. An excellent summary of the work done so far can be found in Cantley [10]. Relevant long term corporate planning models suitable for banks engaged in development banking activities cannot be found in the literature. One of the basic problems faced is the relatively greater degree of uncertainty of the environment. Further, no p~anning exercise in the context of development banking can be based on a trend projection or forecastL'lg type of exercise. There are various reasons for this. One technical reason is that often timeseries data for trend projection or forecasting are simply not a~ailable, in addition, there is a deeper philosophical reason for rejecting trend projection types of model for planning studies at corporate level of banks engaged in development banking. We define ~lanning as a process of willed change and through banking activities we want to initiate deliberate processes of change in the desired direction - thus trend projection can be of little help. In view of the above, it is strongly felt that more care should be taken to get the desired end states under various dimensions of growth appropriately specified by the top management. Profiles of growth connecting the initial states to desired states can then be constructe~ under assumptions of different environmental conditions [1 ]. The steps in formulating a five year corporate plan can thus be enunciated as follows: (a) specification of objectives (desired end states); (b) working out of feasibility of various objectives specified; (c) identification of areas of con~ct; (d) respecification of objectives on rite basis of consideration of various trade-offs involved; (e) construc~g feasible growth profflcg under various environmeatal conditions for achievi~Lg~ e specified objectives; (f) selection of an appropriate growfi, arof'tle considered best on the assumption of a speciiic environ. mental condition. In working out feasible strategies for acheving the various objecti',~es specified, detailed depo:~it, credit and branch expansion plans in the entire a~ea of the bank's present and future operations are ~rawn up. Manpower plans consistent with these are alst~ worked out and feasibility of the manpower plans is assessed. The c,rganisational implications of the long term plan and the effects of developing new expertise on the existing hierarchical structure are also exam-

ined. The annual cost and benefit implications of the ,oral planned programme are also worked out and whether the satisfaction of other non-profit objectives also satisfies the minimum profit objectives, is carefully checked. Thus formulated, the plan cannot be called an optimal plan. In fact seldom one can construct a corporate plan by adopting techniques of optimisation [i4,i71. Even this plan is multi-level in character - as the total plan at corporate ievel has to be decomposed into zonal and re~onal plans. Moreover, the annual plans of the bank and performance budgets of the branches should mesh with the long term plan of the bank. Komai [18] fists three types of information flow in real planning in an organisation. Information flows at the same hierarchical level among various decisionmakers planning fo~ various functions, thus at the central office level information flows between heads of operational and personnel departments for drawing up deposit, credit and manpower plans at corporate level. Such a flow of information has been described as horizontal flow by Kornai. Information also flows between various hierarchical levels having "super or subordinate relationships with each other". Such a flow is defined as vertical flow. In addition to the above two flows - inform~tion flows are neither hierarddcal nor horizontal in the sense described above. Thus, environmental information may flow in an undetermined manner. All these three types of information flows cannot be taken care of in a large scale programming type of model with decomposition procedure. The planning, therefore, is basically a process of search and exploration. The planning models developed at all levels (here at corporate, zonal and regional levels) help the decision-makers to find out about various growth possibilities and to clarify for themselves the priorities of their interests and allows them to consciously work out trade-offs in case of conflicting interests, Thus, the cognitive process of planning allows decision-makers to modify their own objectives and value judgement with the aid of specified alternatives and their likely outcomes worked out. The corporate plan developed by us only attempts to do this. However a sub part of the model even in this frame-work can use programming techniques (e.g. use of L.P. models for developing credit plans). The final plan that emerges is a product of a finite number of itera-

R. Bandyopadhyay / OR in development banking in India

Table

17

5

Goals against alternatives Goals a

Level of deposit

Alternatives

(/9 a)

Level o f p r o f i t over 5 years (It a)

x a % of total advances to priority sector

A c c e p t a b l e level of minimum p o p u l a t i o n served per branch

y a % of total branches to be opened outside eastern region

(pa)

Minimum acceptable number of rural branches opened

(R B a)

1.

--

4-

4-

--

+

2.

-

-

+

-

+

-

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-

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4-

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--

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6. 7.

-

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E x p l a n a t i o n : + m e a n s t h e goals are s a t i s f i e d ; - m e a n s t h e g o a l s r e m a i n u n f u l f i l l e d . a G o a l p r o g r a m m i n g m o d e l s r e p o r t e d in l i t e r a t u r e o v e r - s i m p l i f y t h e p r o b l e m s o f s p e c i f i c a t i o n o f goals, p e n a l t y r e w a r d for F:osit i r e a n d n e g a t i v e d e v i a t i o n s a n d t h e i r relative w e i g h t s .

tions. In each iteration the conscious matching of plans at various functional areas and at various hierarchical levels takes place. The top management of a nationalised bank is concerned with developing its all-India image and also in developing branch network in its lead districts which are relatively underdeveloped in terms of banking networks. However, management wants also to earn a minimum level of profit and to give a certain acceptable percentage of credit to priority sector activities like agriculture, small industry and small trade. When the acceptable levels of various goals are specified, alternative strategies of branch expansion and their ability to fulfil the various goals are worked out. This is shown in Table 5. It may be seen that no alternative growth strategy fulfils all the goal levels simultaneously, as such the whole question of goal specification is examined afresh and this starts the process of next cycle of iterations. The process has to be continued till a satisfactory picture from the points of view of all the desirable goals emerges (see [9]).

4.6. Method of meshing of various plans Planning models discussed so far are dearly interlgnked. There should be consistency in plans drawn fol individual banks and the industry-wide banking plans at state and national levels. Let us take the branch expansion plan as an illustrative case. Matching and consistency will be ensured if the following are satisfied:

Let

nij = the number of branches to be opened by the ith individual bank in the/th region (state); the number of branches to be opened by the ith bank in all regions of the country; n~ = the number of bank branches to be opened by all banks operating in the region/: N = total number of branches t ~ be opened in the country as a whole. Then we must have,

ni

=

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The achievement of matching is often more difficult in practice and may require a number of iterations. The iterative process of effective matching in respect of a branch expansion plan is shown in Fig. 6; the process in respect of credit plans is shown in Fig. 7.

4. Z Unexplored potential areas There are a number of areas where OR and Management Science can be usefully applied. At present, no scientific basis exists for determination of nil. Such a model must take into consideration strength and weaknesses of banks operating in the area, orga-

R. Bandyopadhyay / OR in development banking in India

18

! Banking

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Fig. 6. Flow chart depicting process of matching and interlinkage of branch expansion plan of banks at various levels.

Fig. 7. Flow chart depicting process of reconciliation and

nisational structures of the banks, problems of control and degree of acceptability of a particular bank by the community ~s a whole in a particular region. This is a useful area 'or research and wil! involve understanding behavio~lral problems along with the technical problems. It may be n(,:ed that most of the models developed are very simple. Further refinements of these models are callec for, Basic problems of determining the appropriate ,:riteria for various policy level decisions need to b~ investigated. Better modelling of relevant aspects of the environment and their effects on banking decisions require further research. What is the effect of a 3ranch on the surrounding environment? What are Lhe spread effects of various banking activities? Do these effects vary with branch size and with the degree of effectiveness of the organisation? If so, how do we measure these for inclusior, in our planning models.~ These, and many o~her complex questions need [urther probing. Paucity of data and relatively underdeveloped infrastructural facilities

make the problem of OR modelling a much more challenging exercise in case of planning studies connected with development banking.

inter-linkagesof credit plans of banks at various levels.

5. Operational problems 5.1. Areas of application of OR We have briefly sketched some of the planning studies where OR modelling has been applied. There are a number of operational areas in relation to stall. dard banking functions where OR can be successfully applied. Such areas are: (a) cash management; (b) costing models; (c) stationery management; (d) information systems; (e) project appraisal. These are discussed in turn below:

R. Bandyopadhyay / OR in development bank;ag & India 5.2. Cash management Problems of cash management in branches can be treated as an inventory problem and OR has been applied in th~ area. Problems o f cash-transfer in a network of rural branches are different. In view of the problems of communication, large amounts o f cash in rural branches may accumulate. This in addition to creating problems of idle unutflised resource: ann create great security risks. The problem needs to be tackled for a network of branches operating in rural areas. This will essentially be a transportation cure storage type of problem, though it is eomplieated by security implications. This area is likely to be investigated in the nem" future.

5.3. Problems o f designing appropriate costing models for various banking services These require appropriate modelling efforts to include all relevant variables in an Indian situation for a particular type of service provided. We face problems of segregation of variables and measuring them separately. Later on, we also face the problem of aggregation of these measures and expressing them in money terms to arrive at the correct pricing pc,l.icy for a particular service rendered. Modelling for ::he purpose of costing a safe-deposit locker service has been completed and pricing policies pursued by banks in respect of safe deposit locker service are being reexamined in the light of the results of the model (see 1211).

5.4. Problem o f stationery management Stationery and printing costs form a substantial part of the bank's operating cost apart from salary cost. Simple inventory models may be quite useful in cutting cost. However, her: generally more resistance has been experienced by the OR team from operating management than the ~esistance faced m undertaking other studi:s (including planning studies discussed in Section 4 c f this paper).

J.9

based. Banks throughout the wortd generate lots of data but how effectively they use their data, is, of course, an open question. The situation in India is relatively worse compared to the situation in banks in developed countries. An overload of various types of returns is absorbing a lot of the time of branch staff in f'dling and submitting returns. At the same tm~e major decisions of policy are made without adequate relevant information. The information that comes to the desk of the top management is not quite adequate. Many banks are, therefore, keen to examine the total information system within the banks,. It may be pointed out here that the study of information systems cuts across "all hierarchical levels and all problem areas m a bank. Thus, this study can as well be classified as a planning study or as an organisatior, al design study, because organisation design, delegation and decentraiisafion are largely influenced by the information system design. A thorough study of the i~fformation systems of banks has been undertaken, ~pecial stress has been placed on determining the relevance of information systems and on making new systems more in tune with the new types of decisions that bankers at various levels are likely to make in the discharge of their new roles as development bankers. There are no set methods or techniques that can be used for analysing and designing information systems within an ~rganis~tion. Cor~truO:;~g adequate taxonomic models of information aad decision systems and matching the two is found to be useful in practice. Essential s t e ~ of the study are shown in the fl~w chart diagram of Fig. 8 (see also [25]). The rationalisation of returns has been completed already and the recommendations of the study are being implemented. Considerable savings in terms of the decision makers' time, the improveme~d of overall decision-making and also in the direct cost of information provision have resulted. Organisations where new returns systems have been implemented are now keen to initiate studies in all aspects of information system. This is a clear demonstration of how a simple but successful study of a sub-system can generate Iavourable environment for more tholough and complex studies of the total system.

5.5. Probl,,ms o f designing appropriate information S.vstems

5.6. Problems o f pro/ect appraisal

The in-provement of the decision-system at operational levels is largely dependent on the improvement of information systems on which the decisions are

Project appraisal is conz~dered to be the most important area within the banldng operations. Success of development banking hinges on using appropriate

ZO

~. Bandyopadhyay / OR in development banking in India

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project evaluation methods that would enable bank executives to s~;lect projects (f'manceable schemes and activities) cont:ibuting towards objectives of development banking. No credit planning, however, efficiently or imaginatively formulated to allocate the scarce resource of credit to various sectors can become successful without lJroper methods of project appraisal (consonant with objectives of planned allocation). Under traditional method,., credit decisions are mainly based on the value of the security offered. The method does not pay adequate attention to the income and production generating capacities of the project and to the contributicn of the project towards desired objective of growth ~ t h distributive justice. The OR type of analysis of plojects (this takes into consideration the entire relevant system within the frame of znaiysis) will provide "scientific information on the effectiveness of the av~able means of

action in relation to the stated ends in a given (socio/ econorrdc/institutional) enviromaent" [19]. Such analysis will correct undesirable effects of a purely steek-based security approach adopted by bankers. We can discuss the OR approach to problems of appraisal under three sub-groups: (i) problems of appraisal of area development projects; (Li) problems of appraisal of requests fo; provision of working capital to various industrial production units; (~) problems of appraisal of large number of small borrowers requ~dng small amounts of money for a short period for productive purposes. In case (i) traditional method of analysis is inade~ quate: total development of the areas should be considered. Various alternatives available for this and likely effects (in terms of costs, benefits, etc.) of each of the available alternatives should be carefully

R. Bar~dyopadhyay / OR in development banking in tndta

assessed. Even non-conventional alternatives (altemarives that are not immediately available but can be made available by suitable efforts) should be brought within the chain of means and end analysis. In estimating the inputs, the supporting infrastructure (if any) required for the suecessfui operation of the project must be considered. If the generation of certain supporting economic actMties is considered prerequisite for project success, this should be considered in evaluating costs and benefits. For example, a project for rural electrification by a state electricity board involving several million rupees is fouud an attractive banking proposition because the income to be generated by the sale of electricity to the rural areas (on the basis of assumed demands projected by the State electricity board for the rural areas of the district as a whole) is adequate for repayment of bank loans. However, the project is actually not generating any surplus and is Iunning into loss. On modelling the relevant development problem taking a :~ystem approach it is found that rural dectrification in itself will not generate adequate demand for electt Jetty to make the project viable. Most of the demand {tan only be through operation of electricafly driven ptmpsets for well irrigation. This demand cannot bec0ime effective because of the following two reasons: (i) Many electrified villages tall under the command area of a canal and in these villages canal irrigation will be relatively convenient and cheap. (it) Villages that fall on the opposite side of the command area of the canal (higher in level) are in the drought region. Some of the existing wells are overdrawn. Water levels have gone down further and deeper wells are to be dug. Cropping pattern here is such that small farmers who often have to make distress sales cannot get economic prices tbr their crops to pay for pumps required for well irrigation. A total model of development of the area is needed to minimise chances of such unfulfilled demand. A model so constructed [28] includes in its analytical framework alternatives like provision of lift irrigation to pump up water from the canal to irrigate areas where well irrigation is not profitable (consideration of lift cum flow as opposed to flow irrigation). Further change of cropping pattern (as another feasible alternative) to make caltivation profitable even with pump irrigation in the area (~ot within the command area of canals) should also be considered, This alternative will require provision of (i) extension agents to educate the farmers and (ii) seeds, manures

21

and appropriate farm techniques and tools to farmeis. In the cost estimates these should be included. Feasibility of these provisions within tB.e planning horizon of the project should also be assessed. The model includes in its set of alternatives, alternative of extensive irrigation as opposed to intensive irrigation of a particular area. Extensive irrigation uses available water resources (canal and ground water) ovel wider areas. The model ensures optimal use of the scarce resource of water to increase production and to reduce distributional imbalances as far as possiN~. This so, dy, therefore, stresses the need for re ~:xamination of some of the basic policy issues related to rural development. As regards the bank's method of appraisal of area development projects, study demonstrates clearly the need for total systems approach in analysing such projects. More and more models of this nature are likely to be built in the near future and it is hoped that OR will make a significant contribution in evolving appropriate methodology lbr project appraisal for area development In sub-class (i1), the problem of determining the adequate working capital needs for a particular unit in an industry has assumed vital importance m view of the p, esent inflationary situation of the country. It is observed that there is very little linkage with growth of credit w:}tume and growth of volume of production. Bank c,edit is used in inventory buiMing and speculative hoarding, thus pu.~,hingprices all along the line. Under these conditions monetary authoritie~ would like to restrict credit for unnecessary inventory building and speculative activities. However, at the same time it is necessary to ensure that credit poficy pursued should not in any way ~ffect the productive activities for want of adequate cash. The problem is eminently suitable for an OR type of approach. Basically, it will consist in determining the demand, the likely level of in-process stock~ consistent with production levels and optimal inventory !evels of raw materials to ensure uninterrupted flow of production. All the relevant factors like transpo:t bottlenecks, rea]isation of s~es proceeds, condition of dernar~d generaOr~g activities, industrial relations climate in the industry and also in those kn.dustfies supplying raw materials to it should be included in the medet. All important urdts of important industries need to be studied and unit-wise models for an industry can be constructed for determination of appropriate norms of inventory and working capital requirements. As conditions change, the parameter values of the

22

IL Bandyopadhyay / OR in development banking in India

model will undergo change but by feeding the new values of parame~-ers, new norms can be obtained by quickly solving tl-_emodel in a computer. This type of study will require team work. A team should consist of engineers/teclmologists hav~ngexpert technological knowledge for tk; industry studies, financial analysts, OR or systems scientists. Budding a number of such teams (one team for one industry) with the available talents in banks and in different research institutions in the country seems to be feasible. This proposal has been very broadly discussed v,,i~ a few senior level bankers. Details are yet to be worked out. Launching such a project in a few selecIed industrial units to start with w~2l be immensely useful in tackling the problem of w.~rklng capital finance. Problems of sab-dass (iii), ar'm~ mainly because a large number of ,mall farmers are to be financed during the cropping season. If finance is not given in time, it is not likely to be used for productive purposes and poor fvxmers may use the finance for consumption. Methods of appraisal for these types of loan applications should be quick and simple but at the same time such methods should not be unduly risky. Credit scoring models which allow some salient characteristics of ~he borrowers to be rated quickly to arrive at acceptheject type of decisions are ideally suited for such situations. Construction of such scoring wodels are nothing new. A number of such models have been reported in the literature. We have built scoring models for crop loans [22]. The first results of the models are very encouraging. Similar models have beer developed for small traders [26]. The models will be field tested before being adopted finally as methods of credit appraisal for small loans. We have seen in this section that a number of operational problems can be and should be tackled by using an OR approach. A small but determined beginning has beer, ma ~c in some problem areas and payoffs already obtair~ed are quite encouraging.

6. Problems of org3misation design Most of the Indian cormnercial banks developed as urban banks. Today, they have been entrasted with the task of re#3nal economic development. The banks are expanding into several fu:~ctional areas. Geographically, # e spread of branches is also very rapid. Often bran~=hes are spread out far away from the centr~ office. Transport and communication

facilities to these b~anches (particularly rural branches) are often ill-developed. This raises special problems of control and effective implementation of plans and policies. Certain decisions to be effective must be taken quicldy and have to be made locally. Are such systems of local decision making consistent with overall objectives of the bank? What organisational design measures can be taken to ensure this? Large numbers of specialists are being recruited to discharge the various new functions of the bank. Their positions in the organisational set up (horizontal and v~rtical kderarchical relations) including their career paths need to be carefully developed [23]. Thus, the old organisational structures of banks are under severe strains in the face of the new challenges because of rapid spatial and industrial growth. As these challenges are not of short term nature, serious attempts are being made to re-shape the organisation to make it suitable to face the emerging challenges effectively [8]. Applications of OR in organisational design are relatively rare. Some conceptual literature is available [2,13], but very few implemented real life case studies have been reported. Organisations suitable for the twin purpose of area development and generating acceptable level of profit have not been discussed in the literature. Kulp [20] stresses the need for proper organisation for the successful implementation of programmes in developing economies without giving any idea how such organisations should be designed. lsard [15] deals with the problem only partially. However, his ideas, even though incomplete, are very relevant for developing appropriate systems of decen. tralised decision making for rural development. Organisational design problems of a number of Indian banks of different sizes have beer, studied. In these studies the OR approach has been found to be very useful. Studies have been conducted by inter. disciplinary teams comprising organisation theorists, statisticians, regional planners, financial analysts, and OR scientists. The results have been the integration of the various views and the multi-disciplinary analysis of problems after taking into consideration all relevant variables within the framework of a single model for analysis. Basically, the total problem of design can be divided into a number of steps: (a) Deciding the number of spatial decision making tiers and numbe~ of units of such tiers (i.e. number of zones, regions, etc.). (b) listing ",ill the activities of the organisation

17. Bandyopadhyay / OR in development banking in India

irrespective of the Ievels where such activities take place. (c) Listing all the information needed (including knowledge and skill) for performing the activities. (d) Ascertaining the sources of information. (e) Ascertaining the permissible lag between ,.he generation of need and the performance of various activities. (0Determining the need for local decisionmaking, taking (a) to (e) into consideration. (g) Determining the activities that should go to various control levels (matching of activities with information needs). (h) Preparation of the final activity allocation taking (b) to (g) into consideration. (i) Designing appropriate information and control systems to suppert the activities at various levels. The logical design of an organisation cannot sometimes be effected due to certain behavioural problems. As such we include these variables within the model and if necessary phase out the proposed changes to take care of such behavioural problems during the period of phased implementation. Determination of the number of tiers and number of units in each tier (step (a) above) and demarcation of the boundaries of action and control of various units are the problems to be tackled first. The model developed for the purpose is partly heuristic and is partly algorithnuc. In fixing the number of re~ons and the number of bank branches to be controlled and supervised by each r e , o n , factors like transport and communication facilities, geographical contiguity, homogeneous nature of the area from a socio-economic environment point of view, nature of business activities, size of branches and the likely reaction of the concerned people towards re.demarcation of area of control, are taken into consideration. The problem is different from the "districting" problem discussed widely in literature. The basic difficulty here lies in determining appropriate criteria linking different region~ structures and boundaries with achievement o f organisational goals. Throughout the design exercise, every alternative form of design has to be related to its ability to fulf'd the objectives of the organisation. Thus, here again the aim is not to work out a single design; a number of alternative designs (total design including all subsystems) should be worked out in detail and likely effectiveness of the~e designs over a v.umber of years in fulf'dling not only the objectives as specified for the present but also the likely future objectives which

23

the organisation would be obliged to specify should be assessed. Thus, every organisational design exercise should include some elements of technological forecasting. These forecasting exercises may be normative in character. The desirable growth of the community/society that we wish to achieve in another 10-15 years should be broadly spelt out and the role that the bank, as an organisation should play in this process, should be assigned with as much clarity as possible. Once this is done, alternative structures and systa;,~s can be evaluated keeping it in view. Thus, oaganis~tional systems design should not only be adaptive but it should also be capable of aiding in the creation of the desirable environment. While we have gained useful experience in applying the scientific methodology of OR in designing organisations, there are a number of problem areas (under the general heading of organisational design) where further research is called for. For example, research in the area of technological forecasting relevant to organisational desigq may prove to be very useful. This is required to relate various structural forms with the likely environment and likely roles to be played by the organisation in that environment. Further, we have the agemld problems of motiva. tion. We should know how to relate organisational environment with motivation of employees. Do ~ocio° economic environments influence motivation along with organisafional environmems? If the two influences are not re-inforcing, which of the two effect~ prevails? We do not know answers to such questions, very little research (either at conceptual or at empirical levels) has been done in thes~ areas. If motivation Js solely related to work technology, then the problem is relatively simple and we can design an optimal work technology tak;ng into consideration the realities of the situation m a cou,~try like India. Here OR modelling can be directly useful. However, if motivation ks infiuer~ced by other variables, mainly behavioural (this view is widely accepted), we should examiae, given a congenial work environment and an optimal work technolo~ how behaviourat variables arc to be dealt with, to maxkmise motivation for etficient work. Such research has to be multi-disciplinary. OR can make valuable contribution in developing an appropriate model lh~k_mg work techn~logy, behavi o u r J and work environmental variables.

24

17,. Bandyopadhyay / OR in devet..ymeat banking in India

7. Summary and co~lusions We have ;discussed in this paper a number of applications o f OR in v~rious areas of development banking. Though for eaze of discussion, we have divided the problem areas Late three groups, clearly the problems are intercom~ected. Our experience suggests that, in spite of paucity of data, relative deal th of finance for research studies, quite useful work can be done in a developing country like India. Indian experience may be relevant for other developing countries also. A few general remarks regarding OR in developing economies may not be out of place here based on our experience in the field of OR in banking and also in some other fields. Case studies on development banking are only illustrative; similar fruitful areas of study can be identified in other spheres of national developmental activities: (a) Quite appreciable pay-offs can be obtained even with simple models. (b) Many decision-makers (including those at the policy making levels) both in government and private organisations consider OR or other modern management science approaches as costly methods to obtain trivial common-some soJutions. In a developing country like India, where resources are scarce, costly model building can be often viewed as a luxury which a poor country camlot afford. For this, often OR scientists themselves are to be blamed. Large scale simulation models of regional economy for region~ development or for ~owth centre locations have been suggested. Costs of such model solution and eorrespon~ag benefits have not been explicitly coesidered. In a grewth centre model t'manced and sponsored by an international agency, a large amount of money is spent; however, the model does little better in identifying growth centres compared to a model of interaction index cheaply constructed. If some OR is done on the appropriate approach to be adopted for solving problems of developing economies (taking the resources and other relevant constraints into consideration), we may ourselves f'md that simple (though imperfect) models wI'fich improve decisions, but do not involve high cos~ should be built to maydmise chances of application of OR in solving various problems of developing economy. One criterion for model selection should be ea.~e of replicability. (c) At present, very little OR is used excep~ in industria| units controlled by foreign managements. There are a large number of areas like education,

heaRh, transport, cornmunieafion, research and develoFmcat, water resource planning, rural development, etc. which e ~ benefit immensely by the application of OR. Deveiopment banking is only one such area where usefulness of OR has been demonstrated. Similar demonstrations are required in other areas. (d) For the above, we require OR scientists with the correct type of attitude and education. They should be inclined to devise new problem solution procedures instead of trying to use existing models of apparently similar problems of western economies. It is, therefore, essential that OR scientists should be thoroughly trained in scientific methodologies of problem formulation and solution. Further, scientists willing to work in developing economies must be prepared to work w i t ~ the constraints and conditions obtained in a developing economy. They should not demand unrealistic conditions for successful work. (e) V e ~ few universities in developing countries have developed OR courses. More and more universities should develop OR courses. These courses should be designed so that these become more relevant for problems of developing economies. And university OR departments should get involved in identifying and solving problems considered vital to the development of society and community at large. (f) In various research institutions set up for specialised areas (like small scale industries, community development, health administration etc.) effective OR groups should be established. Problems of development in a country like India require urgent and effective solutions. It is unfortunate that in solving these problems, the powerful approach of OR is used very little. Some beginnings have been made in certain areas (as described in this paper), however, much more needs to be done by all of us to strengthen these experiments and to make OR an effective instrument of growth and prosperity of the developing countries. References [1] R.L. Ackoff, Concept of Corporate Planning (Wiley, New York, 1970). [2] H.I. Ansoff and R.G. Brendenburg, A language for organisation design, in: E. Jantseh (ed.), Perspectivesof Planning~OECD,Pmis, 1969). [3] R. Bandyopadhiay, Planning in commercial banks, Chartered Accountant 21 (Par: 2) (1972). [4] R. Bandyopadhyay, OR modelsin developed and developing economies - Relationship between theory and practice, P~et pte~ented at F~st Re~eazcnConfezence on OR held at Chesters, U.K. (September 1973).

R. Band)'opadhyay / OR in development banking in India [5] R. Bandyopadhyay, On approaches to OR modelling, Omega 3 (1) (1975). [6] R. Bandyopadhyay and P. Mampiily~ Regional planning and commercial banks - A systems approach, Paper presented at Regional Planning Seminar held at Ahmedabad (Match 1973). [7] R. Bandyopadhyay and R.M. Ranga Row, Regional developmen~ and credit planning, Prajnan I (2) (1972). [8] Banking Commission, Report of the Banking Commission (Goverr~ment of India, New Delhi, 1972). [9] H. BhukP,anwala, S. Palav, R. Tarkat and R. Bandyopadhyay, Corporate plan for a bank, Prajnan 4 (2) (1975). [ 10] M.F. Cantley, Corporate planning - A review of questions and answers, Omega 1 (1) (1973). [11] T.K. Das, Operations Research for Decision Making in Commercial Banks (National Institute of Bank Management, Bombay, 1972). [12] S. Eilson and T.R. Fowkes, Applications of Management Science in Banking and Finance (Gower Press, London, 1972). [13] D. Garwin and W. Christoffel, Organisational structure and technology: A computer model approach, Management Sci. 20 (21) (1974). [ 14] W.K. Hall, Some design and development considerations in strategic bank planning models, Paper presented at First International Conference on OR as Applied to Banking and Financial Institutions, Montreal (October 1971). [15] W. lsard, Spatial organisatiort and regional planning. Some hypotheses for econometric analysis, in: The Econometric Approach to Development Planning (North-Holland, Amsterdam, 1965). 116] P.I:. Jessup, Innovations in Bank Management (Holt, Rinehart and Winston, New York, 1969). !I 7] J. Kornai, A general descriptive model of planning processes, Econ. Planning 10 (1-2) (1970). [ 181 J. Kornai, Multi-level planning systems, in: L.M. Goreux and A.S. Manne (eds.), Multi-level Planning: Case Studies in Mexico (North-Holland, Amsterdam, 1973).

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[ 19] T.E. Kuhn, Evaluation of industrial and infra-structure methodology and practical experience, Industrial]safion and Productivity, BuU. No. 18, New York (1971). [20] E.M. Kulp, Rural Dev-lopment Planning - Systems Analysis and Working Method (Praeger, New York, t970). [211 P. Mampilly, Pricing of safe deposit locker service, Unpublished R#search Note, National Institute of Bank Management, Bombay (1973). [22] C.A.S. Naidu and R. Bandyo:adhyay, Risk assessment in agricultural cred't - A scoring method, in: N.C. Mehta az~d V.A. Pai Panandiker (eds.), Rural Banking (National Institute of Bank Management, Bombay, 1974). [23] National Institute of Bank Management, Rep~:~ ot the Task Force on Career Path (National Ip.stRute of Bank ?,lanagement, Bombay, 1973). [24] S.M. Padwal, Heuristic model for bank branch iocafion in rural areas, Thesis, University of Strathclyde, Giasgow, 1972 (unpublished). [251 S.M. Padwal, Informatio~ system in Indian commercial hanks, Unpubl]shed Research Note, National lnstit',te of Bank Management, Bomba7 (1974). [261 S.M. Padwfl, A scoring model for small borrowers, Unpublished Research Note, National institute of Bank Management, Bombay (1974). [27] S.M. Padwal and R. Bandyopadhyay, Branch location i.a rural areas - An OR approach, Prajnan 2 (2) (1973). [28] R.K. Patil, K.R. Datye and S.B. Bhide, &ppraisal of Rural Development Projects through Systems Approach Case Study of Rural Electrification Projcc', (Naticma! Institute of Bank Management, Bombay, 1975). [29] Planning Commission, Draft Fifth Five Year Plan (Government of India, New D,.ih~, 1973L [30] B.R. Sreedat, R.K. Patti and R. BandyGpadhyay, [~anking plan for a state - A case study in Bihar, Praj,~an ,~ (2) (1975). [31] S. Varde, S. Polar and S. Muthu~amy. ~ranch c/~pansion planning, Prajnan 4 (2) (1975). [32] D.J. White, Decision Theory ~Allel; and Unwin. London, 1969).